Hydrological impact simulations of climate change on

Hydrological Sciences–Journal–des Sciences Hydrologiques, 52(6) December 2007 Special Section: Dryland Hydrology in Mediterranean Regions

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Hydrological impact simulations of climate change on Lebanese coastal rivers ANTOINE HREICHE, WAJDI NAJEM & CLAUDE BOCQUILLON CREEN,ESIB, Université Saint Joseph, BP 11-0514 Riad-el-Solh, 1107 2050 Beirut, Lebanon [email protected]

Abstract The significance of predicted climatic changes is still uncertain. The hydrological consequences of climatic changes on Lebanese catchments are analysed by means of different scenarios of rainfall variability and temperature increase. The conceptual rainfall–runoff model MEDOR, coupled to a stochastic model of rainfall and temperature, is used to estimate change in runoff by simulation of six scenarios. These test the response to the rainfall structure, to the duration of rainy events, their frequency, and the duration of the rainy season. The climate–runoff model is used to determine the impact of a temperature increase of 2 degrees on the flow characteristics of a watershed affected by seasonal snow cover. The modifications of the hydrological regimes are significant: droughts are predicted to occur 15 days to one month earlier; snowmelt floods are often replaced by rainfall floods; and the peak flow occurs two months earlier. These changes could have a great impact on water resources management in the future. Key words climate change; simulations; streamflow impact; snow; Mediterranean

Simulations des impacts hydrologiques du changement climatique sur les fleuves côtiers Libanais Résumé La significativité des changements climatiques prévus reste incertaine. Les conséquences hydrologiques des changements climatiques sur des bassins versants Libanais sont analysées au moyen de différents scénarios de variabilité de la pluie et d’augmentation de la température. Le modèle pluie– débit conceptuel MEDOR, couplé à un modèle stochastique de pluie et de température, est utilisé pour estimer le changement dans l’écoulement via la simulation de six scénarios. Ceci permet de tester la réponse à la structure de la pluie, à la durée et la fréquence des événements pluvieux, et à la durée de la saison pluvieuse. Le modèle climat–débit est utilisé pour déterminer l’impact d’une augmentation de la température de 2 degrés sur les caractéristiques de l’écoulement d’un bassin versant présentant un couvert neigeux saisonnier. Les modifications des régimes hydrologiques sont significatives: les étiages sont plus précoces de 15 jours à un mois; les crues nivales sont souvent remplacées par des crues pluviales; et les écoulements extrêmes apparaissent deux mois plus tôt. Ces changements pourraient avoir un grand impact sur la gestion des ressources en eau dans le futur. Mots clefs changement climatique; simulations; impact sur les écoulements; neige; Méditerranée

INTRODUCTION In February 2007, in its Fourth Assessment Report, the Intergovernmental Panel on Climate Change (IPCC, 2007) issued an alarming warning concerning global warming: temperatures are probably going to increase by 1.8–4°C by the end of the 21st century, if no measures are taken to counter this evolution. Warming of the climate system is unequivocal, as is now evident from observations of increases in global average air and ocean temperatures, widespread melting of snow and ice, and rising global average sea level. The scientific report is completed by a Summary for Policymakers recommending measures aiming to limit this global evolution on two levels: at the global level to establish governmental agreements limiting carbon dioxide emissions, and at the local level to integrate the regional impacts into planning policy. Indeed, global warming is going to be felt in very different ways according to the local context: a warming of 2°C might be rather favourable to the development of Canada, or Siberia, but catastrophic for Sahelian countries; a rise of 40 cm of the sea level will have minimal consequences in Lebanon, but will require the displacement of millions of

Open for discussion until 1 June 2008

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people in Bangladesh. It is necessary to consider the local consequences of the local climatic changes, in particular the two main components: rainfall and temperature. The impacts of climatic changes on hydrological processes and water resources at regional and local levels are particularly important, especially in the geographical areas where the water resource is the limiting factor for development. Many studies have been undertaken in this direction: in a global way (e.g. Gleick, 1987; Dooge et al., 1999), and in a more applied way on a given area, for example: Northern Europe (Menzel & Burger, 2002), Canada (Cunderlik & Burn, 2002), USA (Milly, 1994; Dooge et al., 1999), Australia (Chiew et al., 1995; Franks & Kuczera, 2002), and China (Yu et al., 2002). Few analyses have been done for the Mediterranean basin. Ragab & Prudhomme (2002) developed temperature and precipitation variation maps for the whole Mediterranean basin using the global climate model HadCM2; they show for 2050 an increase in temperature of between 1.5 and 3°C and a decrease in the mean precipitation of 3–15%. However, those global values mask significant variations within the regional distribution with increases or decreases, uncertain inter-annual variations, and various seasonal evolutions. General circulation models (GCM) have a spatial resolution of about 200 km × 200 km. A grid cell corresponds to 3.8 times the surface of Lebanon. Such a grid resolution is not suited to mountainous regions. Downscaling techniques allow the transfer of global results to a local scale (Burger, 1996; Bàrdossy, 1997), but add their own uncertainties to the uncertainty of the GCM. Finally, these methods have not been applied to the eastern Mediterranean area. Only lumped information is available on a grid, whereas both desert and rainy areas exist in this region. Moreover, for Lebanon, the evolution of precipitation as a result of a future potential increase in temperature is totally unknown. Under these conditions, the research of hydrological evolution related to climatic changes appears particularly difficult. Most of the attention is given to the impact of climate change on the increase in temperature from global warming. However, the most severe impacts of climate change are expected from changes in runoff, and in particular the extremes: droughts and floods. In fact, the impact of temperature rise is particularly strong on those mechanisms with thermal thresholds, such as the melting of snow and ice. This is already visible on the polar ice caps, which constitute the best evidence for warming (Oerlemans, 1994; Haeberli & Beniston, 1998). In the areas where the variation in precipitation is small, the influence of temperature is important and the disappearance of snow cover can be rapid (Hodge et al., 1998; Brown, 2000). In the Mediterranean area, the 32nd parallel marks the limit of significant snow cover (annual and sustainable) on Mount Lebanon and in the southern Moroccan Atlas. In the coastal zone of Mount Lebanon, and at mid- to high elevations, snow constitutes a substantial part of precipitation, accumulating throughout the winter and melting during spring. Thus, most of the Lebanese coastal watersheds are affected by a significant seasonal snow cover. Snowfall and the resulting seasonal snow cover accumulated at altitude (between 1200 and 3000 m a.m.s.l.) represent an important source of water, especially in spring when the rainy season ends. This mechanism illustrates flow regulation during the year and in particular sustaining streamflow during the recession period. More than 50% of the annual streamflow discharge of the Lebanese coastal rivers is from snowmelt runoff. Snowmelt is also an important contributor to groundwater recharge.


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Several attempts at applying traditional rainfall–runoff models on mountain catchments gave poor results, as evaluated by the Nash criterion (Nash & Sutcliffe, 1970), since accumulation and snowmelt phenomena are not taken into consideration. The presence of the snow cover, which stores and releases a significant volume of water in the form of snowmelt at different time steps, directly affects the hydrology of mountain catchments (Jansson et al., 2003) and, consequently, renders the conventional rainfall–runoff models unsuitable under these conditions (Rothlisberger & Lang, 1987). Therefore, research efforts were directed towards specific models of catchments affected by snow cover, such as CROCUS (Martin & Lejeune, 1996) and VSAS2 (Barry & Prévost, 1990). These models, of physical type, integrate the catchment characteristics and proceed to a distributed approach of the snowpack thermodynamics. Thus they require a significant amount of input data (complete radiative balance, topographic data, etc.), which is incompatible with the requirements of operational hydrology (Beven, 1989). In this context, Ferguson (1999) formulated the most judicious approach by expressing that it was necessary to develop specific tools, called “snow modules” that can be integrated into traditional rainfall–runoff models, in order to extend their applicability to catchments affected by snow cover. The majority of the models most commonly used in hydrology, such as TOPMODEL (Beven & Kirkby; 1979), are equipped with snow modules. However, some models are completely dedicated to the treatment of the snow cover, such as the SRM (Rango & Martinec, 1981). The same types of modelling are found: lumped, distributed, physical, conceptual, stochastic, etc. The physical models are related directly to studying the metamorphism of snow. The inefficiency of physical models led necessarily to a conceptual approach to modelling the snow cover. Nevertheless, two approaches remain possible: a purely empirical method known as the temperature index, or degree-day, and a method with a more physical basis known as the energy budget (Anderson, 1976). This paper first gives an overview of hydrological climate–runoff models that take into account seasonal snow cover, and introduces some that have already been developed and applied. It then describes the hydrological precipitation–runoff model used in this study and its parameterization, and the stochastic model of precipitation and temperature. The primary motive behind the development of the climate stochastic model was to simulate the effects of climate change on the Lebanese watersheds. Next, different scenarios of precipitation change are described, before the impacts of those scenarios on the streamflow characteristics in Lebanon over different periods of time are reviewed and discussed. In the second part of the paper, the hydrological impact of a two-degree warming (under no precipitation change) on a typical Lebanese watershed affected by seasonal snow cover is simulated and the results are discussed.

STUDY AREA Located on the eastern edge of the Mediterranean, Lebanon has a Mediterranean climate, marked by a long dry season (May–October) and a wet cold season, with precipitation varying from 800 to 2000 mm on the maritime front. The coastal zone of Mount Lebanon is divided into a large number of catchments whose sizes vary from a few tens to a few hundred square kilometres. The catchment of interest in this study is Copyright © 2007 IAHS Press

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Fig. 1 Nahr Ibrahim watershed and the Afqa and Roueiss springs.

Nahr Ibrahim basin (Fig. 1). This watershed was chosen because it is a typical Lebanese watershed where measurement data exist at the spring outlets as well as at the catchment outlet. Nahr Ibrahim has a surface area of 341 km2. This watershed is strongly affected by snow cover for four months of the year. The snowmelt contributes up to about two thirds of the total yearly discharge (Abd-El-Al, 1947). Most snowmelt water infiltrates the limestone plateau whose groundwater discharges at two karst springs, the main springs of the Nahr Ibrahim River: Afqa (1200 m) and Roueiss (1265 m). Daily hydrological data for Afqa, Roueiss and Nahr Ibrahim are available for the period 1965–1974. Precipitation data exist at Qartaba station (1200 m), located within the Nahr Ibrahim watershed, for the period 1965–1971. Moreover, 56 years of rainfall data series exist at Beirut station for the period 1914–1969. Temperature is estimated using the daily data of Beirut gauging station (1965–1970), corrected by a constant gradient of temperature of 0.61°C for every100 m of altitude.

HYDROLOGICAL MODEL The hydrological impacts of a potential climate change on Lebanese coastal rivers are simulated using a streamflow model generator. The climate–runoff model used in this study is a coupling of a stochastic model of rainfall developed by Najem (1988), a stochastic temperature model, and a rainfall–runoff model MEDOR (Hreiche et al., 2003). The rainfall model is an alternation model of first-order Markovian process between dry and wet spells. The process is defined by two parameters: T1 and T2, being the mean duration of the dry and wet spells, both are seasonal functions of date. Daily mean rainfall depths G are drawn from an exponential probability function and are independent. The structure of the model and the parameters T1, T2 and G were validated on 41 stations distributed all over Lebanon (Najem, 1988) and on 36 stations distributed within the Mediterranean basin (Hreiche et al., 2005). The identification of this stochastic structure using long, available daily records allowed the development of a rainfall generator that has the same stochastic characteristics as the measured series. The stochastic temperature model was developed as follows: temperature data from 50-year record at Beirut were seasonally adjusted by taking into account the Copyright © 2007 IAHS Press


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Production function Fig. 2 Structure of the MEDOR model.

Fig. 3 Measured degree-day at Oyoun e Simane station in 2001.

temporal evolution of the mean and the standard deviation. It was modelled by an ARIMA (2,1) model. This model, calibrated on a series of 25 years of data, was validated on another 25-year record. The CRR model used is the MEDOR model (Hreiche et al., 2003), specific for Mediterranean catchments. It is a daily lumped rainfall–runoff model that uses average basin-wide daily rainfall as input to produce runoff values as close to measured data as possible. The structure of the model is represented in two separate functional modules (Fig. 2): a production module and a transfer module. A third module, representing snow cover, is used for watersheds affected by seasonal snow cover (Hreiche et al., 2006). The model variables are calculated in metres of water equivalent per square metre of snow cover area. The different modules are as follows: – The snow cover management module The intensity of precipitation is determined from rainfall measurements. The intensity of snowmelt is determined by the equation of the degree-day. In the model, the type of precipitation (rainfall or snow) is selected via a temperature threshold: The precipitation is assumed to accumulate as snow when the air temperature drops below T0. When the temperature is higher than T1, snow starts to melt. The evolution of the snowpack was followed for several years at Oyoun e Simane station and on a snow profile to determine the characteristic thresholds and relationships, such as T0, T1, and degree-day values (Fig. 3). Between T1 = 0°C and T0 = 3°C, the two mechanisms are simultaneous and the stock evolves differently according to the intensity of


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precipitation and snowmelt. Local temperature is estimated using climatic gauging stations with a constant gradient of temperature. The volume of snow is stored in a lumped reservoir. With each time step, the theory of the degree-day applied to the snow cover surface allows the loss of snow volume to be calculated. Snow covered area will evolve with the snowpack volume. The function of production transforms rainfall into net rainfall by applying a constant loss. It is represented by a reservoir having a capacity h0 and a variable rate of filling H/h0 (0 < H/h0 < 1). Two outputs are provided: (i) An output proportional to the entry with a coefficient related to the rate of filling: Output = Input × (Rate of filling)2 and (ii) a loss function connected to temperature and proportional to the rate of filling: Loss = F(temp) × (Rate of filling)

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This structure allows the simulation of evaporation in winter and draining of the tank in summer. Thus, the annual balance can be adjusted using the parameter h0. The transfer module The production module feeds the transfer module, which contains two reservoirs: fast drainage (R1) and slow drainage (R2). Net rainfall will be divided between these two reservoirs, with the proportion being controlled by a calibrated coefficient. The two reservoirs have linear exits. The streamflow discharge is the sum of the two exits.

Streamflow simulations The MEDOR model uses rainfall and temperature as inputs and has four parameters that need to be calibrated: two in the production module and two in the transfer module. The semi-physical module based on the degree-day method is used to simulate the snowmelt and is integrated within the MEDOR conceptual model. The criterion chosen is the Nash criterion (Nash & Sutcliffe, 1970), which is an estimator of the difference between measured and model-generated flows. This model was successfully tested on several Mediterranean basins (Hreiche et al., 2004). Using the semiphysical module based on the snowmelt mechanisms with the standard energy balance approach and a degree-day melting model, the two main springs of Nahr Ibrahim— Afqa and Roueiss—could be simulated. The streamflow discharge of Nahr Ibrahim was simulated by coupling the global model, calibrated over six years of data, to the conceptual rainfall–runoff model of the remaining part of the catchment. Comparison of the measured and simulated flows of Afqa Spring shows Nash values in calibration (1965–1968) and validation (1968–1971) of 0.85 and 0.81, respectively. This model represents correctly the recession distribution as well as the peak flows (Fig. 4(a)). Nash values for Roueiss Spring range from 0.86 and 0.72, respectively, in calibration (1965–1968) and in validation (1968–1971). The recession of Roueiss Spring is much faster than that of Afqa Spring. The Nash values for the global model of Nahr Ibrahim, were 0.85 and 0.82 in calibration and validation stages, respectively (Fig. 4(b)).


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Fig. 4 Measured and simulated streamflow: (a) of Afqa Spring and (b) of Nahr Ibrahim (1965–1968).

THE POTENTIAL IMPACT OF PRECIPITATION CHANGE ON LEBANESE RIVER HYDROLOGY Methodology Estimation of the hydrological consequences of changes in climatic variables can be undertaken in several ways: (a) Direct method: in seeking the historical trends of the hydrological characteristics (Cunderlik & Burn, 2002). This method cannot be widely used in regions where the following conditions exist: absence of long streamflow data series, poor quality of the data, many disturbances in the catchment (urbanization, deforestation, pumping, etc.) (b) Mixed method: the rainfall and temperature data are either extrapolated using trends identified in historical series, or generated with a GCM. These data are transformed into streamflow using a conceptual rainfall–runoff (CRR) model. This method is commonly used (Chiew et al., 1995; Mimikou et al., 2000; Yu et al., 2002). However, it cannot be applied to the Eastern Mediterranean rivers, since no significant trends could be detected on 36 long rainfall data series as concluded by Hreiche et al. (2005).


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(c) Scenario method: This method consists of building a complete model of streamflow generation using a combination of a stochastic model for rainfall generation and a deterministic CRR model. A sensitivity analysis of the hydrometric characteristics to the climatic parameters and those of the CRR model allows the impact of potential climatic changes on streamflow to be quantified. This method has been applied to the southern zone of Taiwan (Yu et al., 2002). The first two methods cannot be applied in Lebanon, since there are many gaps and inhonomeneities in the available Lebanese data due to the war and urbanization, and the long rainfall data series in the region do not show any significant trend. For this reason, the scenario method is chosen and applied to Lebanese coastal rivers. The distribution of parameters T1, T2 and G was determined at Beirut station. These parameters were identified using 56 years of daily rainfall data and are taken as a reference in this work (Scenario 0). Initially, a sensitivity analysis of MEDOR to the rainfall model parameters (T1, T2, G) was carried out. This corresponds to variations from –10% to +10% of the different parameters. Results show that the parameter values which have an effect on the streamflow are those characterizing the wet season (e.g. wet season duration). Since effects of different variations are independent, a simple model structure can be assumed. Six scenarios, which essentially modify parameter values in winter, were considered. These scenarios are induced by variations in the rainfall parameters T1, T2 and G. The first scenario assumes an increase in the duration of wet spells (T2) by a factor of 1.1, i.e. a change in the chronological structure of the rainfall without changing the daily mean of rainy days. The second scenario consists of an increase in the duration of dry spells (T1) by a factor of 1.1, i.e. a change in the structure of the rainfall without changing the daily mean of rainy days. The third scenario consists of a decrease in the mean depth of rainfall (G) by a factor of 1.1, without modifying the rainfall structure (i.e. the durations of wet and dry spells T1 and T2). The fourth scenario supposes an increase in the duration of the rainy spells without influencing the evolution of the various spells. This can be done by increasing the value of T2 by 10%, and by considering that T1 + T2 is constant; so that a variation of T1 is compensated by an opposite variation of T2. The fifth scenario supposes an acceleration of the evolution of phenomena without changing the durations of the rainy spells. This is implemented by a 10% decrease in T1 + T2, and by considering that T2 is a constant; consequently, this will induce a variation of T1. The sixth scenario corresponds to a reduction in the duration of the rainy season. To modify this duration, a scaling affine transformation according to the time direction was made centred over 15 January. This affinity of 0.8 ratio corresponds to a shortening of the rainy season by approximately 1 month. The various scenarios were simulated over 500 years in order to ensure the stability of the results. The quantification and understanding of potential hydrological impacts cannot be achieved by comparing the streamflow data generated by the climate–runoff model to measured series which are not available. Thus, it is necessary to define global indicators of this potential variability. These indicators will be chosen at different (annual, monthly and daily) time steps. At the annual step, the selected indicator is the dimensionless runoff coefficient CR, the ratio of the annual streamflow to the annual rainfall; at a monthly step, the selected indicator is the monthly distribution of



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streamflow; and at a daily step the reference consists of the distribution of discharge normalized by the mean annual discharge. These two curves are considered as references in order to compare their evolution in the sensitivity analysis of the rainfall model parameters. Results and discussion Effects on the runoff coefficient The analysis allows the influence of the different scenarios on the annual runoff coefficient to be studied. The coefficient of variation of streamflow discharge a, according to change in precipitation, as defined in equation (1), was calculated for all the scenarios. dQ dP =a Q P

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where Q is the annual discharge and P the annual precipitation. Figure 5(a) shows this sensitivity coefficient plotted against the runoff coefficient CR. For catchments having a small runoff coefficient, the discharge will decrease more (in proportion) than the variation of the total rainfall. For example, Nahr Beirut catchment has a runoff coefficient of 0.41 (calculated using measured rainfall and runoff data). This corresponds to a multiplying coefficient of 1.7; a reduction in the rainfall of 10% would involve a reduction in the annual discharge of 17%. This coefficient was calculated for a large number of Lebanese catchments (Fig. 5(b)). The values range between 1.5 and 2.2. Nahr Ibrahim shows a runoff coefficient of 1.5. As a result, an average amplifying effect of 2 is demonstrated for Lebanese catchments, i.e. a variation in the annual rainfall will involve a double variation in the annual discharges.

Sensitivity coefficient a

Impacts on monthly and daily distributions The monthly modifications induced by the various scenarios are represented in distribution percentage, normalized by the annual depth (Fig. 6). Moreover, daily modifications are represented by the distribution of the discharges, normalized by the mean (Fig. 7). Scenarios 1, 2 and 3 are

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Fig. 7 Sorted simulated discharge, normalized by the mean: Scenario 0.

slightly different from the reference, i.e. local disturbances in the length of the dry or rainy spells have no significant effects on the dimensionless structures. Scenarios 4 (increase in the rainy durations), 5 (acceleration of the rainfall mechanisms), and 6 (shortening of the rainy season) cause a sharp reduction in the minimum discharge. As a conclusion, scenarios which modify only the structure (length of the spells in scenarios 1, 2 and 3) without modifying the evolution (monthly variation of T1, T2 and G) do not have significant impacts on the monthly and annual distributions. The three remaining scenarios, which increase the duration of the rainy spells, accelerate the rainfall mechanisms and decrease the rainy season, lead to more severe drought.

HYDROLOGICAL IMPACT OF POTENTIAL CLIMATE WARMING ON A LEBANESE COASTAL RIVER Methodology The hydrological regime of rivers having significant snow cover will be affected by an increase in temperature, as the temperature controls the snow formation, accumulation and melt. The following explains the effect of a warmer climate on the snowmelt runoff feeding the two springs Afqa and Roueiss within the Nahr Ibrahim basin, which is affected by significant seasonal snow cover. A reduction in precipitation will lead, as the only effect, to a reduction of the flows and not to the modification of the flow regime. Since Ragab & Prudhomme (2002) showed an increase in temperature Copyright © 2007 IAHS Press

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between 1.5 and 3ºC in 2050 in Lebanon, a scenario of a 2 degree increase in the mean temperature is retained. The decrease in precipitation has already been analysed in the first part of this paper. The simulation based on historical data allows the effects of warming to be analysed, but data series are too short to draw significant conclusions. Therefore, long generated data series will be used. The methodology adopted for studying the impact of potential global warming consists of using a model of streamflow generation with a combination of a stochastic rainfall and temperature model, and the MEDOR model calibrated on the Nahr Ibrahim catchment. The different models were described previously. The climate–runoff model allows a long data series of streamflow discharge to be generated. Fifty years of temperature and rainfall data were generated and used as input for the model of Afqa Spring, Roueiss Spring and Nahr Ibrahim catchment, in order to simulate 50 years of streamflow output for each (Case 1). The same operation is repeated under the constraint of a 2° increase in the mean temperature (Case 2). The impact of global warming is discussed by comparing the results of the two cases. Simulation results Simulation of hydrological variables The evolution of the mean snow width, evaluated in metres of water equivalent (Fig. 8), on the Cenomanian plateau of Nahr Ibrahim at an altitude of 2000 m shows that an increase of 2°C decreases this width tremendously. It can even be insignificant in some years (< 20 cm). Moreover, the maximum volume of the snowpack (Fig. 9) is greatly decreased. Figure 10 shows the evolution of the streamflow of Nahr Ibrahim over three years. The modifications of the river regimes are significant. Drought occurs 15 days to one month earlier. The snowmelt floods of April–May are often replaced by rainfall floods in February–March. 1.5

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Fig. 11 Relationship between maximum snow widths (in metres of water equivalent) (Case 1: reference simulation, Case 2: scenario of an increase by 2°C). Copyright © 2007 IAHS Press

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Fig. 13 Discharge distribution for Nahr Ibrahim (m3/s) (Case 1: reference simulation, Case 2: scenario of an increase by 2°C).

Potential impact on the snow cover The maximum snow width at the Cenomanian plateau (altitude 2000 m) over 50 years was calculated for the two cases. The relationship between these widths is represented in Fig. 11, which shows that a 2°C warming decreases the width of the snow cover by approximately 50%. Potential impact on the mean daily discharge and the discharge distribution The mean daily streamflow data are obtained by calculating the average values during the same day of the year over 50 years of generated runoff data. Figure 12 represents the mean daily outputs at Nahr Ibrahim outlet. In Case 1, the peak flow is at the end of April and in Case 2, it is at the end of February. Moreover, the flows are more regular. This shows a contradiction of the usual idea which considers that snowmelt has a regulating effect on streamflow discharge. The reason is the speed of the melting mechanism in Lebanon. The 50 years of generated data allow the discharge distribution to be defined in the two cases: the reference simulation and the scenario of an increase of 2°C (Fig. 13). We notice that the distance between the two curves is insignificant. Thus, the modifications in the time of flow occurrence did not modify their probability distribution. Discussion The physical-conceptual model allowed long streamflow data series to be simulated for the current climatic state and for a 2°C climate warming scenario. The modifications of Copyright © 2007 IAHS Press

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the spring regimes are significant. The recession in the springs occur 15 days to one month earlier. Thus, the drought period is prolonged by this duration. Snowmelt floods are often replaced by rainfall floods and the extreme flow occurs two months earlier. The hydrological regime of Nahr Ibrahim is affected in the same way. The consequences of these modifications are several and can be discussed in the context of agriculture, and hydroelectric and water supply: – In terms of agriculture, since the period of water shortage is earlier by about 15 days, production will be shifted back without significant modification in the return/output. This should have no serious consequences for perennial crops, although, for annual crops, farmers will have to plan the sowing earlier. However, this adaptation appears minor, with respect to the inter-annual variations which farmers have to deal with. – In terms of hydroelectric supply: the discharge distribution did not change, so the production will be the same. – In the context of water supply, the consequences are more serious. A longer period of water shortage will affect water supply, which is already complex due to the increase in the population and its needs. Those impacts illustrate increasingly difficult future challenges that water resources management will be faced with.

CONCLUSIONS Taking into account the uncertainties related to rainfall and temperature variability in climate change projections, the results of this work cannot be regarded as a prediction, but rather scenarios spanning the potential impacts of change. The impacts of the precipitation scenarios on streamflow and annual runoff coefficient are rather moderate. The relative decrease in flow is greater due to the low value of the runoff coefficient of the catchment. Moreover, the impact on the water cycle is related to the effect of a temperature increase on the seasonal snow cover. With a 2°C increase, the modifications of the streamflow regimes are significant. Shortage periods are earlier by 15 days to one month and snowmelt floods are often replaced by rainfall floods. This disturbs the hydrological regimes of the rivers such as Nahr Ibrahim and yields important water management problems. The results correspond to the assumptions on which the GCM simulations are based, i.e. evolution of the carbon dioxide concentration to 500 ppm in 2100. The conclusions do not hold for other assumptions, for which the calculations would have to be repeated. REFERENCES Abd-El-Al., I. (1947) Hydrological Study on Ibrahim River, vol. 2. UNESCO. Anderson, E. A. (1976) A point energy and mass balance model of a snow cover. NOAA Technical Report, NWS HYDRO-17 NWS 19. Bàrdossy, A. (1997) Downscaling from GCMs to local climate through stochastic linkages. J. Environ. Manage. 49, 7–17. Barry, R. & Prévost M. (1990) Application of a snow cover energy and mass balance model in a balsam fire forest. Water Resources 26, 1079–1092. Beven, K. J.(1989) Changing ideas in hydrology: the case of physically based models. J. Hydrol. 105, 157–172. Beven, K. J. & Kirkby, M. J. (1979) A physically based variable contributing area model of basin hydrology. Institute of Hydrology, Wallingford, UK.



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Received 8 February 2007; accepted 19 July 2007
