Climate Change Model as a Decision Support Tool for Water Resources Management in Northern Iraq

The northern region of Iraq heavily depends on rivers, such as the Greater Zab, for water supply and irrigation. Thus, river water management in light of future climate change is of paramount importance in the region. In this study, daily rainfall and temperature obtained from the Greater Zab catchment, for 1961 – 2008, were used in building rainfall and evapotranspiration models using LARS-WG and multiple linear regressions, respectively. A rainfall – runoff model, in the form of autoregressive model with exogenous factors, has been developed using observed ﬂ ow, rainfall and evapotranspiration data. The calibrated rainfall – runoff model was subsequently used to investigate the impacts of climate change on the Greater Zab ﬂ ows for the near (2011 – 2030), medium (2046 – 2065), and far (2080 – 2099) futures. Results from the impacts model showed that the catchment is projected to suffer a signi ﬁ cant reduction in total annual ﬂ ow in the far future; with more severe drop during the winter and spring seasons in the range of 25 to 65%. This would have serious rami ﬁ cations for the current agricultural activities in the catchment. The results could be of signi ﬁ cant bene ﬁ ts for water management planners in the catchment as they can be used in allocating water for different users in the catchment.


INTRODUCTION
Greenhouse gases contributed a global mean surface warming likely to be in the range of 0.5 C to 1.3 C over the period 1951 to 2010, with the contributions from other anthropogenic forcings, including the cooling effect of aerosols, likely to be in the range of À0.6 C to 0.1 C. The contribution from natural forcings is likely to be in the range of À0.1 C to 0.1 C, and from natural internal variability is likely to be in the range of À0.1 C to 0.1 C.
Together these assessed contributions are consistent with the observed warming of approximately 0.6 C to 0.7 C over this period (IPCC ). Global surface temperature will continue to change by the end of the 21st century and is likely to exceed 1.5 C relative to 1850 to 1900 for most climate model scenarios.
Unlike temperature, which has increased almost everywhere on the planet, precipitation has increased in some parts of the world and decreased in others (Archer & Rahmstorf ). Changes in precipitation and temperature lead to changes in runoff and water availability. Runoff is projected with high confidence to decrease by 10 to 30% over some dry regions, due to decreases in rainfall and higher rates of evapotranspiration (IPCC ). Precipitation has indeed decreased in Middle East countries which has caused problems of water shortage (Biswas ; Roger & Lydon ; Al-Ansari , ; Allan ), where at least 12 countries have acute water scarcity problems with less than 500 m 3 of renewable water resources per capita available (Barr et al. ; Cherfane & Kim ). The supply of water is essential to life, socioeconomic development, and political stability in this region. In 1985, UN Secretary General Boutros Boutrous-Ghali said that the next war in the Near East would not be about politics, but over water (Venter ). In view of this situation, a number of research works has been conducted on water scarcity in the region. Most of the work was based on future water demand which in turn was based on population growth rate and water projects in the region (Barton ; Osman ; Strategic Foresight Group ; Türkeşet al. ; Hydropolitic Academy ). In addition, the Middle East seems to be one of the areas in the world most vulnerable to the potential impacts of climate change (Bazzaz ; AFED ; Hamdy ; Yildiz ). Moreover, the Mediterranean has been identified as one of the hot spots of climate change (Giorgi ). Cudennec et al. () have shown that the Mediterranean region is particularly sensitive to changes brought about by human pressure on hydrological processes. Collet et al. () found that the annual water balance at a studied catchment scale showed that the decrease in runoff was due primarily to lower annual precipitation and increased AET. The seasonal analysis identified the causes of the annual hydrological changes at the catchment scale. The substantial decrease in winter precipitation (À45%) seems to explain most of the reduction in discharge at the catchment outlet. Moreover, the joint rise in summer temperature and summer withdrawals is the main factor explaining the decrease in low-flow period discharge (À50%). These changes in winter precipitation and summer temperatures were also observed in this region by Stahl et al. (). In South and East Asia, climate change will increase runoff, although these increases may not be very beneficial because they tend to occur during the wet season and so the excess water may not be available during the dry season when it is most needed (Arnell ). There are a great number of studies and investigations on climate change effects for water resources which have shown that regions with decreasing runoff (by 10 to 30%), and a rather strong agreement between climate models, include the Mediterranean, southern Africa, and western USA/northern Mexico (IPCC ).
Specifically, rivers in Iraq face a severe risk that has an effect on Iraqi water resources, and this risk mainly comes from global warming. Rainfall occurs between October and May with the highest precipitation levels between December and February reaching 1,000 mm in the north-eastern part of Iraq. The winters are cool and the coldest month is January, with temperatures ranging from 5 C to 10 C; summers are hot resulting in a high rate of evaporation in the southern plains (UNDP ). Daily temperatures can be very hot; on some days temperatures can reach easily 45 C or more, especially in the Iraqi desert areas and this causes a danger of heat exhaustion. The IAU Report () indicated that the water level in the Tigris and Euphrates -Iraq's main sources of surface waterhave fallen to less than a third of normal capacity. The critical issue is that this trend is expected to continue in the future.
Despite all these problems, very little work has been done (Issa et al. ) to determine detailed future expectations of river flows in the region. In this paper, an attempt has been made to predict the future flow of one of the main tributaries of the River Tigris in Iraq. The objective is to investigate the impacts of climate change on future flows of the Greater Zab River and its implications on the water use in the catchment. It is believed that such work will help decision-makers to take prudent measures to minimize or overcome the water shortage problems in the studied catchment and perhaps the Middle East at large.
Estimation of the magnitude of future flows in a river catchment is always required for efficient design, planning, and management of projects that deal with conservation and utilization of water for various purposes. In order to accurately determine the quantity of surface runoff that takes place in any river catchment, it is necessary to understand the complex relationship between rainfall and runoff processes, which depends upon many geomorphological and climatic factors (Beven ). Thus, in the present paper, a rainfall-runoff model in the shape of AutoRegressive with eXogeneours factors was used. The model was developed using observed rainfall and evapotranspiration data for the purpose of calibration and projection of future river flow.
The paper is organized as follows. In the next section, a description of the catchment and data used are given. This is followed by a methodology section, in which all models used are described. Results and a discussion of the model applications and future impact follows, and finally, concluding remarks from the study are presented.

MATERIAL AND DATA
The major water resources in Iraq are the Tigris and the

METHODOLOGY
The usual methodology followed to study impacts of climate change on river flow is first, establish a relationship (rainfall-runoff model) between the causes of flow (rainfall and evapotranspiration) and the effect (flows) for a baseline condition, assuming that this relationship is constant in the future. Second, future forecasts of the causes are obtained by means of models and then used to obtain the corresponding future effects (flows) using the established relationship.
In the present research two separate models have been used to estimate each of the future rainfall and evapotranspiration in the catchment, and a third model was developed to relate them to the river flow. For the purpose of this study, the WG has been used to generate future projections of rainfall, maximum and minimum temperatures for three periods (2020s, 2050s, and 2080s). For more information on LARS-WG and how the model works readers can refer to materials in Semenov & Stratonovitch ().

Evaporation model
As LARS-WG simulates future minimum and maximum temperature based on observed time series, the model developed to estimate future evaporation in this study is a temperature-based one. A multiple linear regression (MLR) model for daily evaporation (ET 0 ) is developed using daily minimum (T min ) and maximum (T max ) temperatures as predictors, which takes the form: where β 0,1,2 are model parameters estimated using SPSS software and ε ∼ N(0, σ 2 ) is a Gaussian error term with variance σ 2 .

Rainfall-runoff model
Different rainfall-runoff models have been used before to study the impacts of climate change on stream flows.
Among them are conceptual rainfall-runoff models (e.g.,  (2): where Q t , R t , ET 0t , and ε t represents the river flow, the rainfall, the evapotranspiration, and the noise, respectively, at time t. ϴ i and β 1,2 are model parameters estimated using SPSS software.

Fitting measures of models
where k is number of regression parameters excluding constant terms used to fit the model. The residual variance in Equation (3) is referred to as the mean-squared-error of the model.
Other fitting measures used in the present study for linear regression models are coefficient of determination R 2 and for rainfall-runoff model the Nash & Sutcliffe () efficiency criteria, E f , defined as: The test calculates a p-value, which is used to accept or reject the hypotheses that the two sets of data could have come from the same distribution (i.e., when there is no difference between the observed and simulated climate for that variable). A very low p-value, and a corresponding high K-S value, means the simulated climate is unlikely to be the same as the observed climate; and hence must be rejected. Table 1 shows the statistical analyses results of the model's performance in simulating the seasonal observed data and Table 2 shows the model performance for simulating the daily rain in each month. In both tables, the letter 'N' represents the number of tests carried out.
From the results in Tables 1 and 2, it can be noted that LARS-WG is more capable in simulating the seasonal To increase confidence in LARS-WG capability for predicting future precipitation, comparisons between statistics calculated from simulated precipitation with the corresponding ones calculated from the observed data are carried out here. Figure 2 shows a comparison between the monthly mean rainfalls yielded by the two series. LARS-WG's perfect performance in fitting rainfall and temperature as evidenced by the discussion above, give reasonable confidence in using it to simulate future rainfall and temperature.   The coefficient of determination, R 2 , for the model in Equation (6) was found to be 0.977 for the calibration period and 0.99 for the verification period. These high values of R 2 provide confidence that this model can be used to predict evapotranspiration in the region.

Calibration of the rainfall-runoff model
The ARX (p) model described in Equation (2)  ciency (E f ), described in Equation (5), for each tested model was also calculated. Figure 6 shows plots of AIC c and E f up to p ¼ 5 for the AR combined with the exogenous factors. In Figure 6, the minimum AIC c and highest E f occurs at p ¼ 1, suggesting that an ARX (1) is the most suitable rainfall-runoff model in this case. The ARX (1) model found is then calibrated using the observed flow, rainfall, and evapotranspiration data for the period 1961-2000. The calibrated linear model is: Efficiency (E f ) of the rainfall-runoff model was evaluated for the calibration period as 0.8. The standard error of estimate, representing the noise term in Equation (2) above, was estimated at 3.319 cumec for the calibration period, which is insignificant compared to the river daily  Table 3, are generated by using LARS-WG (ver-  for the same period as in Equation (8.2). The SF is applied to the simulated runoff at the (L þ 1)th time point before using it to calculate the runoff at (L þ 2)th time point.
The generated future maximum and minimum temperatures were used as inputs to the calibrated model in Equation (6) to generate future evapotranspiration. The generated future evapotranspiration (ET 0 ) and rainfall (R) were then used together with a historical value for the runoff to generate a future value of flow for the Greater Zab River.
The obtained future daily flows were analyzed to investigate the impact of climate change on the catchment. Seven series of future flows were generated using the seven GCMs in Table 3. Ensemble average of the generated series was then taken to reduce the amount of uncertainty in the results. To investigate which seasons would be most affected by the climate change, a comparative graph for the difference between the average seasonal flow in the baseline period and that of each of the three future periods is presented in Figure 10. The graphs in Figure 10 indicate that the winter and spring seasonal flows are projected to suffer a significant reduction in the future. The reduction is predicted to be in the order of 25 to 65% of their corresponding observed seasonal flow for the three future periods. The seasonal flow of  the summer season is projected to show no significant changes from the corresponding observed summer seasonal flow. Conversely, the autumn seasonal flow is projected to significantly increase, to more than 60%, over the corresponding observed seasonal flow.
Further, Figure 11 shows comparative plots for the average monthly flow in the baseline period and the three future periods. The average monthly flows for the months July to November are projected to increase, whereas those for the months January to June are projected to significantly decrease in all future periods with maximum reduction associated with 2080-2099. The reduction in the flows is much greater than the increase, which ultimately is reflected in the amount of total annual flow as presented in Figure 9.  the river yield for their agricultural activities. The objective is to assess the impacts of climate change in the near, medium, and future periods to inform the water management authority in the catchment for their future plans.
Three models were developed, one for the rainfall and temperature using LARS-WG, another for the evapotranspiration using MLR, and a third for transforming rainfall into runoff using an AR with rainfall and evapotranspiration exogenous factors. Daily rainfall and potential evapotranspiration data from the weather station in the catchment together with flow measurements from a downstream end river gauging station, for the period 1961-2008 were used for calibration and verification of the three models.
The calibrated models were then used to project future flows in the river, using A2 climate scenario emission and three future periods. The results can be summarized as follows: • LARS-WG was very skillful in describing rainfall and temperature distribution and magnitude in the catchment; this would increase confidence in the current research results.
• The autoregressive, with exogenous factors, model developed for transforming rainfall and evapotranspiration into runoff or river flow was also very efficient. This model could also be used for flow forecasting in the river.
• The impacts' results obtained with the developed models show that climate change would have significant impacts on the Greater Zab River flows. Annual flows are projected to generally decrease below the current average annual flow.
• The negative impacts would be very much apparent in the winter and spring flows as the reduction is predicted to be in the order of 25 to 65%, whereas positive impacts are projected to occur in the autumn seasons with significant increase to more than 60%. The negative impacts could have significant consequences on the agricultural activities in the catchment whereas the positive impacts should be treated with care, depending on the river flow capacity as they could result in significant flooding.
The seasonal flow of the summer season is projected to show no significant changes from the corresponding observed summer seasonal flow.
• Results from this study could be beneficial to water management planners in the catchments as they can be used in allocating water for different users.