Climate change impacts in Romania: Vulnerability and adaptation options

Transcription

1 GeoJournal 57: , Kluwer Academic Publishers. Printed in the Netherlands. 203 Climate change impacts in Romania: Vulnerability and adaptation options Vasile Cuculeanu 1, Paul Tuinea 1 &DanBălteanu 2 1 National Institute of Meteorology and Hydrology, Sos.Bucuresti-Ploiesti 97, Bucharest, Romania; 2 Institute of Geography, Str. D. Racovita 12, Sector 2, RO 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 carbon dioxide 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 in atmospheric concentrations of greenhouse gases may lead to irreversible changes in the climate (Houghton et al., 1996). Sufficient evidence indicates that climate change could have a significant impact on agriculture, forests, and water resources, particularly in regions with high presentday vulnerability and little potential for adaptation (Tegart et al., 1990). The United Nations Framework Convention on Climate Change (UNFCCC, UNEP/WMO) calls upon all countries to assess the impact of climate change on different economic sectors so that the most vulnerable areas can be assessed and adaptation responses for climate change can be developed. The majority of the results presented in this paper have been collected within the framework of the Romanian Country Study on Climate Change, which was established under the US Country Studies Program (Cuculeanu, 1997). The basic principles behind the methodology used to assess the impact of climate change are further explained in the book Guidance for Vulnerability and Adaptation Assessment (US Country Studies Management Team, 1994). This study contributes to current estimations of climate change at the regional scale. Climate change scenarios General Circulation Models (GCMs) are the most widely used tools to develop climate change scenarios for impact assessment. The output of four equilibrium GCMs were analyzed in order to select the models that best describe the current climate in Romania. These four GCMs include: the GISS (Godard Institute for Space Studies), the GFDL R- 30 (Geophysical Fluid Dynamics Laboratory, referred to as GFD3), the UK (United Kingdom Meteorological Office, referred to as UK 89), and the CCCM (Canadian Climate Center Model, referred to as CCCM) (Hansen et al., 1983; Mitchell et al., 1990; Phillips, 1994). The transient GCM used in this analysis was the GFDL model (referred to as GFD1) (Manabe and Stouffer, 1993). The model output necessary for impact assessment consisted of long-term monthly mean temperature and precipitation data derived by assuming the present level of carbon dioxide (referred to as 1xCO 2 ) and a doubling of the present level of carbon dioxide (referred to as 2xCO 2 ). Ten-year statistics for each month were also included in the transient model runs as well. The baseline climate was defined as the long term ( ) monthly averages of precipitation and surface air temperature from one hundred meteorological stations uniformly distributed over the Romanian territory. In order to select GCMs that best depict the climate in Romania, the 1xCO 2 runs were compared to the observed climate (monthly mean temperatures and precipitation) over a large area that included Romania, as well as to the country s baseline climate. In regards to temperature, the CCCM and GISS models best reproduce the climate in Romania, but the resolution of the GISS model is too low to represent the country s geographically extensive territory. The UK and GFD3 models simulate a much colder climate than the baseline. However, the GFD3 simulates a warmer climate than the baseline for some warm months of the year. The annual trends in temperature simulated by GCMs are generally similar to the baseline except for the GFD3, which simulates August temperatures warmer than July temperatures, and the UK 89, which simulates February temperatures cooler than January temperatures. On the whole, all models simulate a climate with more continental characteristics than the actual observed temperatures reflect. In regards to precipitation, a more complex situation occurred. Certain models better simulate precipitation in some

2 204 months than others. However, the UK89 and the GFD3 give the most extreme differences between modeled and observed precipitation trends. The UK89 most drastically overestimates and the GFD3 most drastically underestimates. The annual precipitation trends in Romania are not accurately simulated by any model. Generally, precipitation is overestimated for the cold months and underestimated for warm months. CCCM gives the lowest differences between modeled and observed precipitation trends. Therefore, it has been concluded that this model best describes the current climate in Romania both for temperature and precipitation. All climate models show that a doubling of the CO 2 concentration leads to the same climate signal, namely, increased air temperature in Romania. Thus, CCCM and GISS anticipate the increase of temperature ranging between C and C, correspondingly, depending on the month. With regard to precipitation, CCCM simulates an increase (20% on average over the country s territory) during the cold season and a decrease (20%) during the warm season. GISS generally shows an increase in precipitation for all months (except for September), the maximum increase being in October (40%). The new climate scenarios were constructed by adjusting the baseline data by the differences (for temperature) and by using a ratio (for precipitation) between 2xCO 2 and 1xCO 2 experiments. Impacts on agricultural crops In this section the potential impact of climate change on the development, grain yield, and water balance for the key agricultural crops are analyzed for 6 typical sites located in one of the most vulnerable zones in Romania the southern region. In addition, the possible adaptation options for crop management under anticipated climate changes are examined. The vulnerability assessment was focused on winter wheat and maize because of their considerable importance in the agriculture of the area and because of the differences between these crops genetic physiological responses to CO 2 concentration levels (winter wheat being a C 3 crop and maizeac 4 crop). According to the climate change scenarios used in this impact assessment, the annual mean temperature in the southern region of Romania is likely to increase by C, with monthly variations of precipitation ranging between 47% and +81%. Precipitation will increase during 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; Rounsevell et al., 1996; Godwin et al., 1989; Ritchie et al., 1989) were used to estimate the effects of climate change on winter wheat and maize (a late-ripening cultivar). Three levels of management practices were considered in the assessment process (Cuculeanu et al., 1999): (i) no fertilizer stress, water and temperature being the only factors affecting the crop yield; (ii) medium technology, allowing nitrogen and phosphorus to drop to values that are compensated by fertilizer amounts currently applied on most farms in the region of interest; (iii) low input technology with no applied fertilizer. The crop simulation models output were validated at two reference sites Fundulea, cambic chernozem, and Craiova, brown reddish soil where the experimental crop yield data and 30-year climate series were available. In order to assess the biophysical and economic impacts of climate change, CERES models (Godwin et al., 1989; Ritchie et al., 1989) linked with the seasonal analysis program included in appropriate software DSSAT v.3.0 (Tsuji et al., 1994) were run for 30-year baseline and modeled climates. Impact on agricultural crops The results of crop simulation models under equilibrium scenarios showed that the climate change impacts on winter wheat and maize development, grain yield, and water balance depend on the local conditions of each site, the severity of climate parameters changes, and direct physiological effects of the double CO 2 concentration. Wheat and maize have different photosynthetic pathways, so their responses to increased CO 2 are different. Winter wheat could benefit from the combination of CO 2 concentration increases and higher temperatures, while maize appears to be vulnerable to these changes, especially in the case of a warm dry climate, such as simulated by CCCM. Wheat yields increased at all analyzed sites in two climate change scenarios as a result of large direct effects of CO 2 doubling on photosynthesis and water use. In the case of medium agricultural technologies (allowing nitrogen and phosphorus stresses to factor up to 50%), the crop models provided the following results for winter wheat: both experiments (CCCM and GISS) induced grain yield increases in about 0.7 t ha 1 and 0.4 t ha 1, correspondingly; no statistical differences were found between the standard deviation of current yields and climate change projections. Therefore, the yearly variations in the yields under CO 2 doubling will be more or less the same; the length of a growing season decreased by about days; the water use efficiency increased by 47 57% as compared to current conditions, mainly because of the increased CO 2 assimilation rate; the economic risk analysis gives as dominant a nonirrigated agrotechnology, both for the current and changed climates; no significant changes in the yields under climate change conditions (CCCM and GISS) were noted if the sowing date was altered by 30 days before or after the present one; all the selected sites show analogous trends in simulated parameters. The impact on maize differs between the two models and different management practices used. Thus, the following conclusions can be drawn about rain-fed maize:

3 205 the CCCM scenario resulted in a grain yield increase of t ha 1 d.m.; the increase according to GISS was t ha 1 d.m. These data show that the CO 2 assimilation rate reaches its maximum with the GISS projections of climate change ; the length of growing season decreased by 4 32 days with the CCCM and by 2 26 days with the GISS models; compared to the baseline climate, the precipitation sum for a vegetation period decreased by 2 19% according to CCCM and increased by 1 18% according to the GISS scenario; the total evapotranspiration during the growth period slightly 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 the CCCM scenario, depending on location. With the GISS scenario, the yield increased up to 18% at three sites and slightly 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 induced significant water stress in the maize fields especially in the grain filling phase. However, the opposite situation occurred in the GISS scenario; irrigation efficiency increased. Compared to the baseline climate, use of irrigation water decreased at almost every site by an average of 14 29%. Adaptation options The above results show that maize productivity might be vulnerable to climate change. To evaluate alterations in the agricultural practices that could reduce the possible negative effects of climate change on irrigated maize production, four adaptation options were analyzed: changes in crop varieties, sowing dates, crop densities, and fertilization levels. The simulation results and economic risk analysis suggest the following dominant adjustment strategy: application of irrigation, use of late hybrids, sowing in the last 10 days of April plant densities of 5 plants per m 2, and the increase of nitrogen levels up to kg ha 1. The main effects on crop rotation options are: in general, new climate conditions benefited all crop rotations; the greatest benefits occurred in short crop rotations (single crop of wheat, wheat-maize); use of mineral fertilizer increased by about 15 20% under expected climate conditions when applied for the same level of stress factor; the benefit values for the best rain-fed management systems under expected climate conditions were about the same as those for the best irrigated technologies under the baseline climate. Impact on forests Forests in Romania are mainly made up of deciduous species (69.3%). The remaining 30.7% of the forested areas are made up of resinous species. One of the basic principles for 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, it is desirable to have a normal age class structure with equal forested surfaces of each class. The present Romanian forest structure includes an excess of the young age classes (1 60 years) and a deficiency in the middle-age classes (61 80 years), the exploitable stands (over 100 years), and especially in the pre-exploitable stand classes ( years). In order to assess the potential impact of climate change on forests, two approaches were used: the first was based on the Holdridge life zone classification model, and the second, was based on a dynamical model that predicts the temporal evolution of species composition and productivity as a function of climate parameters. Holdridge model The Holdridge model (Holdridge, 1947) relates in a simple way to the vegetation pattern of climate change by using a climate-vegetation classification procedure. By assuming that the broad-scale patterns of vegetation (e.g., biomass) are at equilibrium in the present climate, the distribution of major vegetation types can be correlated with biologically important climate features. The Holdridge life zone method links vegetation distribution with such climatic variables as biotemperature, mean annual precipitation, and the ratio of potential evapotranspiration to precipitation. This model is suitable for examining, on the one hand, broad-scale sensitivity of vegetation to climate and, on the other hand, the influence of climate change on the suitability of a region for different vegetation types. The model does not take into account the specific vegetation processes and as such it cannot be used to predict the dynamics of species composition and stand productivity. The maps and associated databases relying on the Holdridge models for the current climate and projected climates show the changes in land area associated with different categories of vegetation (e.g., forest). The Holdridge life zones, derived by applying the model to the baseline climate of Romania, are quite similar to the existing forest distribution in the country (Figure 1). The maps corresponding to four equilibrium climate change scenarios are illustrated in Figure 2. The comparison of modeled vegetation life zones shows the relative concordance of CCCM, GFD3 and GISS models concerning the ratio between different types of vegetation. All three scenarios assign a share close to 50% of the country s surface to the warm temperate thorn steppes. The warm temperate dry forests rank second in surface area, holding between 16% (GISS) and about 26% (GFD3) of the country s surface. The UK 89 scenario assigns the largest share of the country s surface (55%) to this zone, while the warm steppe, ranking second, occupies about 38% according to this scenario. The cool temperate wet forest ranks third according to all scenarios, with percents between 3.7 (UK 89) and 10 (other three). Regardless of scenario differences, significant climate change will induce dramatic changes in the life zones of Romania. Thus, the present life zones existing in the plain areas will migrate towards higher altitudes and be replaced by life zones specific to warmer climate conditions,

4 206 Figure 1. Holdridge life zones under the baseline climate conditions. perhaps like those existing nowadays in the southern Balkan Peninsula or in Asia Minor. JABOWA model A more advanced model simulating the temporal dynamics of forests in response to environmental changes is JABOWA II (Botkin, 1993). For each plot-year of simulation, the model determines the annual growth increment for each tree, stochastically adding new samplings and deciding which trees die out. The model output consists of the time evolution of the basal area and total biomass for different forest species as the function of both the climate conditions specific to analyzed period, and the plot characteristics. Being a dynamic JABOWA requires a transient scenario to characterize the time evolution of climatic variables. Thus, a transient GFD1 scenario was applied to three points in the country: Bistrita (in a hilly area), Predeal (in the mountains), and Bucharest (in the midddle of a plain). The transient climatic data for each point were obtained by a downscaling procedure (Busuioc, 1996). Beech forests prevail at the Bistrita station, fir forests at the Predeal station, and oak forests at the Bucharest station. In order to estimate the effect of climate change on forest composition and productivity, particularly on the basal area and total biomass, the JABOWA model was run with the baseline climate parameters, as well as with the transient climatic data for three decades specific to the NCAR- (National Center for Atmospheric Research) supplied data: , , and If the present climate conditions remain constant in the Bistrita area the biomass would display a slight decrease, followed by more obvious growth in the beginning of 2010 and a tendency to stabilize around The same dependence was also obtained for the basal area. The simulations indicate a progressive growth in total biomass from 6.4 kg/msq to 28.3 kg/msq starting in Under future climate scenario conditions the time-dependence of the parameters of forest productivity is quite similar to that of the current climate, until However, in the 2050s a severe decrease in both parameters is anticipated. As a result, biomass will decrease from 27.8 kg/msq in 2040 to 6.6 kg/msq in Such a sharp fall in the forest ecosystem s productivity is due to enhanced aridization of the region caused by temperature increases and precipitation decreases, especially during the summer months. In the plain region (Bucharest station), the basal area and biomass dynamics are very similar to the Bistrita zone. The transient scenario resulted in maximum values for both the basal area (48 cmsq/msq) and the biomass (29.9 kg/msq) in 2040, followed by a decrease in the two parameters (by 20 cmsq and 14.6 kg/msq, respectively) until 2060, and a slight increase in In the mountainous area (Predeal station), small differences occurred in forest productivity between baseline and modeled climates. The spruce and fir forests of the mountainous zones seem to be less affected by climate change. The predominance of these species will be maintained even until The oak forests in the lowest areas of the Romanian Plain near Bucharest as well as the hill area beech forests (e.g., Bistrita) seem to be more sensitive to climate

5 207 Figure 2. Holdridge life zones for different climate scenarios. change. The vulnerability of these forest ecosystems will increase considerably, especially after 2040, as a consequence of temperature increases and associated water stress. Consequently, the productivity and protection capacity of the forest area will decrease. Adaptation measures To examine the possibility of transplanting species from other geographic zones, JABOWA was run for species of North-American flora. The results showed that red maple (Acer rubrum), white pine (Pinus strobus) and red oak (Quercus rubra) seem to have favorable development conditions according to the GFD1 scenario. At present, in order to diminish adverse effects, the following measures should be taken: augment the building of storage lakes and irrigation canals, create forest shelterbelts in the low-forested areas, and achieve ecological rehabilitation of impaired forests. The application of extended adaptation measures in the climate change-affected areas will require huge expenses that exceed the possibilities of silviculture. Impacts on water resources Application of the model to the pilot basins zones. The model was applied to two sets of input data: the first characterizing the actual climate and the second specific to the climate change scenario based on CCCM output. The river flow at the outlets of the pilot basins simulated by the model for actual climate conditions and the climate change scenario were then transferred to several river sections in the analyzed basins by an up-scaling procedure. The VIDRA rainfall runoff model (Serban, 1987) used for the simulation of river flow under different climate conditions is a lumped type model. Consequently, the input meteorological data (precipitation and temperature) and the model parameters should be considered as average values over a basin area. Such a condition may be met provided that a basin area is sufficiently small no more than a couple of hundred square kilometers. Therefore, in order to apply the VIDRA model as a first step in estimating climate change impacts on hydrological resources, representative small basins, named pilot basins, were selected. Three basins ( km 2 ), located in representative mountainous, hilly, and plain areas (Poiana Tapului, Band, and Vartoapele, respectively) were chosen as pilots. The relief categories and pilot basins selected for the assessment of water resource vulnerability and corresponding adaptation measures were found in the basins of the Siret, Arges, and Tarnave Rivers. In order to calibrate the model, the daily flows from were simulated for the pilot basins. In order to estimate the impact of climate change on hydrologic resources, a rainfall-runoff model was applied to three pilot basins, representing mountainous, hilly, and plain

6 208 Transfer of the simulated monthly flow series from the pilot basins to the runoff-forming basins (reference basins) The Siret and Arges River basins embrace two main zones with different hydrological behaviors: (i) the contributing zone, which supplies most of the total flow of the catchment; the corresponding basin of this zone is mainly hilly or mountainous; and (ii) the routing zone, where the contribution of the basin is minor although its area is significant. In the Tarnave basin, the runoff is gradually formed over the whole catchment area. The reference basin is a catchment corresponding to a contribution zone. An up-scaling procedure for transferring the model output from the pilot basin to the reference basin takes into consideration the relief configuration of the latter, which usually shows a quasi-gradual variation with altitude. For those basins with a complex orography, the mean absolute altitude represents a morphometric characteristic that integrates the influence of all climatic and physiographic factors upon the runoff formation. The river and the basin slopes, the hydrographic network density, soil permeability, vegetation, as well as the main climate factors (temperature and precipitation) are characterized by obvious variations with altitude. Thus, the specific multiannual runoff, defined as the ratio of the multiannual discharge to the basin area, correlates well with the mean basin altitude. In addition, there is a good correlation between the mean altitude and the long-term monthly mean specific discharge. By coupling the hypsographic curves with these statistical relationships, the monthly mean specific runoff for each relief zone of the reference basins were found. Then they were integrated to obtain the total runoff. Impact on the hydrological resources in the reference basins and in different points of the analyzed basins It is important to note that the pilot basins are not located inside the reference basins and only represent the typical relief configurations (mountain, hill, and plain) that are similar to the landscape of the reference basins. Consequently, it must be assumed that the modeled meteorological input data applied to the pilot basins reflect the climate change for reference basins. Therefore, the baseline temperature and precipitation data for pilot basins were corrected in the degree simulated by CCCM for the reference basins. The corrections were performed by averaging the values generated by the CCCM model in certain points of each relief zone. Based on the pilot basin modeling with the up-scaling procedure, the monthly discharge hydrographs at the outlets of reference basins were estimated. The main conclusions that were reached are as follows: for the climate change with CO 2 doubling, a decrease in runoff occurs when compared to the present climate. This effect can be explained by a significant increase in evapotranspiration caused by the increase in air temperature, even though higher precipitation is anticipated in this scenario; with CO 2 doubling, a redistribution of the monthly mean runoff is highlighted, with an increase in the monthly discharges coefficients of variation, as compared to present characteristics; the analysis of the monthly frequency of the discharges that are above normal revealed that April has the highest decrease in maximum runoff; the maximum monthly discharges shift from the spring and summer months to the winter months because of expected winter warming that causes snow cover to melt at an earlier phase than the precipitation maximum (generally occurring April July ); the minimum monthly mean discharges shift from the October January period to August October as a result of air temperature increases (greater evapotranspiration and soil moisture decreases) and because of the marked precipitation decrease in September. Vulnerability and adaptation options In order to assess the vulnerability of water resources under the climate change conditions, the series of mean monthly discharges in several points of the analyzed basins should be tracked. These points refer to the locations of water reservoirs and diversion and restitution works where the water resource-demand budgets are estimated. The assessment of the monthly flows in these points was accomplished by means of a correlation between the stations at the outlets of a reference basin and gauging stations in the analyzed basins. The correlation function was calculated on the basis of year records at the gauging stations located in the analyzed basins. It is assumed that the correlation function between discharges in different points of the analyzed basins for the current climate will be valid in a 2xCO 2 climate. Taking into account the monthly flow estimated on the basis of future demands for agriculture, industry, and water supplies under climate change conditions, a water balance resource-demand model was applied. This model (Amaftiesei, 1988) allowed us to simulate the storage reservoir exploitation according to pre-established scenarios. For each time step the model calculates the balance equation for each storage reservoir in an upstream-to-downstream cascade. Application of this model resulted in the assessment of vulnerability of three studied basins. Taking into account the existing water management, the Arges River basin appears to be the only one sensitive to climate change. Moreover, it is one of the most important water basins from an economic, 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 basin include structural and non-structural measures. To establish structural measures, 15 combinations of the most economical measures were analyzed for a number of reservoirs and water diversion works that could be undertaken in the future. Finally, on the basis of economic criteria three sets of combinations were selected. In regard to structural measures, new operational rules for the strategic Vidraru reservoir were examined. Time evolutions of the users demands were combined with gradual reductions in water losses in the water supply network.

7 209 Conclusions The results show that climate change could induce significant effects on different environmental and economic sectors of Romania. The ones most affected appear to be maize crops in the southern part of the country, forest species growing in the plains and hilly zones, and water resources where demands could exceed their availability, as in the case of the Arges River basin. In order to increase the reliability of these estimations, it is necessary to apply the outputs of more advanced GCMs and to improve models for describing the physical and biophysical processes specific to impact assessment. Acknowledgements All GCM outputs were supplied by the US National Center for Atmospheric Research. The software DSSAT v3.0 and the computer codes associated with Holdridge and JABOWA models were presented by the US Country Studies Program. We acknowledge the Management Team of this program for excellent their collaboration. The main part of the results represented in this paper have been obtained within the framework of the National Country Study on Climate Change in Romania, developed under the US Country Study Program. We are very grateful to reviewers, particularly, to those who assisted us in editing the paper in proper English. References Amaftiesei R., 1988: ARTIZAN- program for simulating the exploiting of water resource systems, ICPGA (Internal Report). Balteanu D., Ozenda P., Kuhn M., Kerschuner H., Tranquillini W. and Bortenschlager S., 1987: Volume G: Impact analysis of climatic change in the Central European mountain ranges, European Workshop on interrelated bioclimatic and land use changes, Noordwukerhout, The Netherlands. Botkin D.B., 1993: Forest dynamics. An ecological model. Oxford University Press. Busuioc A., 1996: Estimation of the effect of CO 2 concentration doubling upon winter air temperature in Romania. Romanian Journal of Meteorology 3(1), Cuculeanu V. (ed.), 1997: Country study on climate change in Romania. Element 2: Vulnerability assessment and adaptation options. Final Report, August, US Country Studies Program. Cuculeanu V., Marica A. and Simota C., 1999: Climate change impact on agricultural crops and adaptation options in Romania. Climate Research 12, Godwin D.C., Ritchie J.T., Singh U. and Hunt L., 1989: A user s guide to CERES-Wheat v International Fertilizer Development Center, Muscle Shoals, AL. Hansen, J., Russell G., Rind D., Stone P., Lucis A., Lebedeff S., Ruedy R. and Travis L., 1983: Efficient Three-dimensional global models for climate studies: Model I and II. Monthly Weather Review III: Holdridge L.R., 1947: Determination of world plant formation from simple climate data. Science 105: Houghton J.T., Meira Filho L.G., Callander B.A., Harris N., Kattenberg A. and Maskell K. (eds), 1995 Climate Change, The Science of Climate Change, IPCC, Cambridge University Press, Cambridge, U.K. Mitchell J.F.B., Manabe S., Tokioka T. and Meleshko V., 1990: Equilibrium climate change and its implications for the future. In: Thoughton J., Jenkins G.J. and Ephraums J.J. (eds), Climate Change, The IPCC Scientific Assessment, pp Cambridge University Press, Cambridge, U.K. Phillips T.J., 1994: A summary documentation of the AMIP models, Report No. 18, PCMDI. Lawrence Livermore National Laboratory, Livermore, CA, UCRL-ID , 343 pp. Poster J.R., 1993: ARFCWHEAT 2 A model of the growth and development of wheat incorporating responses to water and nitrogen. European Journal of Agronomy 2(2): Ritchie J.T., Singh U., Godwin D.C. and Hunt L., 1989: A user s guide to 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 Rosa D., Legros J.P., Simota C. and Sobczuk H., 1996: ACCESS A spatially distributed soil water and crop development model for climate change research. Aspects of Applied Biology 45. Serban P., 1987: The VIDRA flood simulation and forecasting model. Meteorology and Hydrology 7(2): Tsuji G.I., Uehara G. and Balas S. (eds), 1994: DSSAT v3.0, Vol.1, 2 and 3. University of Hawaii, Honolulu. UNFCCC-United Nations Framework Convention on Climate Change Published by UNEP/WMO Information Unit on Climate Change U.S. Country Studies Management Team (PO-63), 1994: Guidance for Vulnerability and Adaptation Assessment, U.S. Country Studies Program, Washington D.C., U.S.A.