Using GIS Technology to assess the Impact of Change on Water Resources in Faisal Macci Al Zawad

Presidency of Meteorology and Environment, 31911 Saudi Arabia, [email protected] , (+966)38571428 1. ABSTRACT An attempt to use GIS technology (ArcGIS 9.2) to compare the present climate to the future is carried out using local meteorological data and output data from an advanced climate model. Surface temperature, precipitation, surface evaporation, surface wind speeds, and runoff will be studied to gain insight on the impacts of climate change on water resources of Saudi Arabia. Historical data from various meteorological stations is provided by the Presidency of Meteorology and Environment (PME). The United Kingdom Meteorological Office provided future General Circulation Model (GCM) data, reanalysis griddled data that best represent the actual observation (ERA40), and a software called “PRECIS” stands for “Providing Regional for Impact Studies” that can be run on a personal computer. The results of running PRECIS by using GCM and reanalysis data will provide high resolution information (50 km) about various climate fields. Precipitation, surface evaporation, wind speed and near surface temperature (1.5 m height) are investigated. The subtractions of evaporation from precipitation will lead to identifying the sensitive locations affected by climate change with respect to water resources perspective. Adapting A 2 scenario which is described by the United Nations Intergovernmental Panel of Climate Change (IPCC), an increase of more than 4 degrees Celsius of the daily mean temperature over Saudi Arabia is apparent. The results of precipitation, winds, and evaporation vary, but a dominant increase of both precipitation and evaporation, and a decrease in wind speed at the surface are common. Substantial percentages increases in runoff are detected from 100 to 350 percents. Saudi Arabia is divided into six regions and thirty seven locations to be analyzed in this study. GIS technology presented an excellent opportunity to present my findings, and help me achieve my objectives with relative ease. In short, GIS made the results of my research look good, and helped me in validating the climate model I am using and assisted in analyzing the selected climate fields. Key wards: GIS, Climate Change, Water Resources, Saudi Arabia

1 2. Introduction

Climate change issues are discussed widely around the world. Many scientists relate global warming and its consequences to human activities and not to natural fluctuations. The reasoning of this approach is the time scale of climate change. Recent warming of the earth is considered to be abrupt compared to the time scale usually accompanied with natural climate change episodes. Earth’s natural climate changes happen gradually in a long period of time (tens of thousands to millions of years), but we are witnessing an abrupt change over the past 200 years. The industrial revolution with fossil fuels as its main source of energy is setting a steady emission increase of Carbon dioxide and other greenhouse gases which trap heat causing an increase of temperature in the lower atmosphere. Climate change is recognized as an important issue, and international communities through the United Nations created special groups to focus on climate change effects and initiated protocols to organize a global response to deal with its consequences. Unusually strong tropical storms, heavy precipitations causing a devastating floods, more frequent heat waves, frequents drought and other similar events are connected to a modern climate change. The UN Secretary-General Ban Ki-moon, refer to climate change as the “defining issue of our era,” and the government of Saudi Arabia has recognized that by signing Kyoto Protocol. This calls, among others, for implementation of commitment to stabilize greenhouse emissions and furnish a report about the current status of climate change to the UN Framework Convention on Climate Change (UNFCCC) on the status of greenhouse gases and climate change impacts and mitigation.

2.1 Climate Change and Hydrology: C limate is a complex system (Figure 1a); it involves air, water, ice, land and various interactions like water cycle and greenhouse effects. Water is the bond that brings climate and hydrology together.

Figure 1a Figure 1b Figure 1a shows the climate system’s interactions. Any changes in solar inputs, the atmosphere, or the hydrological cycle will affect the interactions among the atmosphere, the hydrosphere, the cryosphere and the biosphere. The impacts of climate change will be devastating to rivers, lakes, sea level, vegetation, ecosystems and many others. Figure 1b represents published studies showing the increase in global mean surface temperature’s. The studies point to a steady increase in temperature during the 20 th century and unprecedented increase in the last 50 years. The source is (Treut, and et al, AR4WG1, 2007).

2 The mean earth temperature has been on the rise for the past 150 years in an abrupt manner (Figure 1b), and expected to increase further by the end of the twenty first century with the doubling of the current atmospheric carbon dioxide. Climate change interacts with various natural processes in the atmosphere, the hydrosphere, the cryosphere and the biosphere. There is an increasing evidence that anthropogenic (caused by human’s activities) gases are to blame in causing the climate change (Treut, and et al, AR4WG1, 2007). Studying the future state of water resources in a changing climate requires a common ground of approximation. The hydrologist would like to get specific information about future precipitation, temperature, evaporation, runoff and others on a specific location like an aquifer or a watershed which is mostly on a scale of less than 10 5 km 2 (Loaiciga 1997). On the other hand Climatologist run global climate models (GCMs) with a resolution around 300 km to predict the future. From here the need to run a Regional Climate Model (RCM) arise, to include topographical and higher resolution to give more precise reading for the hydrologist. This technique is called nesting and presented in figure 2.

Figure 2: nesting from GCM to RCM to a watershed (Loa´iciga, 2007). Using précis as the RCM with grid resolution of 50 km, it was possible to assess the regional changes in temperature, precipitations, and other climate fields, and assign highly accurate values for each station in this study.

Climate change is a global issue, but knowing its effect on water resources in a small area requires a great deal of information and analysis. The climate of Saudi Arabia is arid with insignificant contribution to water recharging. Overexploitation of fossil groundwater is apparent everywhere in the Kingdom. No matter what will the future bring, being aware of the state of climate change and its impacts on water resources can be of a great benefit to the nation and consist of essential information to aid in protecting and managing the water resources.

3. Problem Statement

The importance of water and air in our daily life is clear to everyone, though they represent fragile earth resources that can change abruptly at times. Understanding the mechanics of climate change provide us with an essential need to prepare for the future. Saudi Arabia has huge ancient groundwater

3 reserves that are continuously under increasing demand. The total number of wells in Saudi Arabia increased by more than 100 % from 1982 to 1990, and the total irrigation demand in 1997 was 22933.4 million cubic meters (Rasheeduddin, Abderrahman, Lloyd, 2001). This type of research is applied over Saudi Arabia for the first time and will open many opportunities to investigate the effects of climate change on various sectors and resources in Saudi Arabia. In this study we will shed a light on what is expected to face us with regards to precipitation, wind speeds, runoff, temperature and evaporation. This information can point the sensitive areas that might be affected by climate change, and help in designing a proper plan to manage our water resources. This research will provide future climate variables for scenario A2 which calls for high emission of Carbon Dioxide and explosion of the world population (Treut, and et al, AR4WG1, 2007). Those climate variables can be used by hydrologist to predict the effects of climate change on the recharge of aquifers, and consequently the future status of aquifers in terms of storage and yields by implementing available hydrologic models.

4. PRECIS

GCM data covering the region of Saudi Arabia are provided by United Kingdom Met Office. Those data will be used to run a licensed RCM called “PRECIS” that can be initiated at a resolution of 50 km or 25 km. The resolution of 50 km is chosen. because a 25 km run will take 6 times the amount of times needed to run experiments with 50 km resolution. PRECIS (Providing Regional Climates for Impact Studies) is a regional climate modeling system that can be run on a PC. The United Kingdom Met Office’s Hadley Center for Climate Prediction and Research is the provider and the developer of this software. The data for the boundary condition is supplied by the Hadley Center Global Climate Model (GCM), UK Met Office. PRECIS comes with a user interface to carry on climate experiments (Jones, and etal, 2004). Prediction of future climate change is done globally with world wide support through United Nations organizations. Very few countries have the capability to designate a dedicated group of highly trained scientists and provide extremely fast computers to run GCMs’ models to generate climate change scenarios, and perform the necessary analysis to investigate the regional impacts of climate change on their specific regions. The United Nations Development Program (UNDP), The UK Department for Environment, Food and Rural Affairs (DEFRA), and the UK Department of International Development started funding PRECIS to be available to developing countries to generate their own climate change scenarios with using a personal computer only. The UK Met Office’s Hadley Centre will supply the software, the boundary conditions and other fields of global quantities required to run PRECIS (Jones, 2004). Emission scenarios describing population, energy, and economics are taken from IPCC SRES (A1T, A1FI, A1B, A2, B1 and B2). Concentration estimation of Carbon dioxide, methane, sulphates, and other gases are done by carbon cycle and chemistry models. PRECIS will be used to enhance the relatively large-scale output of HadAM3P, a 150 km resolution Hadley Center’s global atmospheric model to get fine detailed information of climatic predictions.

4 5. Methodology:

5.1 Developing a plan There are three parts for this research. First is to set up the regional climate model (PRECIS) and run the three experiments. Second is to do basic analysis to the output data to get specific information about climate fields and calculate the predicted state of the future from the simulation and the historical data. Third is to use ArcGIS 9.2 to present the climate variables outputs and do further analysis.

5.1.1 Setting up and running PRECIS

I installed the Linux operational system (open SUSE 10.2) and Precis (version 1.4.6) into three separate personal computers. Two of them have processors (CPU): Intel® Pentium® 4 with speed 3.2 GHz. The third one is with an Intel centrino core duo processor with speed of 2.16 GHz (figure 3). Three experiments were designed to perform present, future and reanalysis data (see section 5.2) in order to get proper statistical information. Present and future experiments were based on Hadley Center’s GCM data. The final experiment is dedicated to get a high resolution of ECMWF reanalysis data (ERA40). Each experiment took approximately three months of continuous run.

Figure 3: The three personal computers used to carry out the experiments.

5.1.2 Basic Analysis

The science of climate change requires running huge amount of world wide data, and presently few places conduct climate modeling for a hundred years of the future which is regarded as climatologists’ common sense of research. It is widely accepted to take the period spanning 30 years from 1961 to 1990 as a baseline in carrying out model simulations. The future climate fields are determined from the results of the regional climate model simulation of present day carbon dioxide concentration value and the future when the concentration of CO 2 is doubled. The following are the calculations carried out by this research modified after (Loa´iciga, 2007):

2 2 Tscenario = Thistorical + (T f 2xCO – Tb1xCO ) (5.1)

2 2 Wscenario = W historical + (W f 2xCO – Wb1xCO ) (5.2)

5 2 2 Pscenario = P historical * (P f 2xCO / P b1xCO ) (5.3)

2 2 Escenario = E historical * (E f 2xCO / E b1xCO ) (5.4)

2 2 (P-E) scenario = (P-E) historical * {(P-E) f 2xCO / (P-E) b1xCO } (5.5)

2 2 Qscenario = Q historical * (Q f 2xCO / Q b1xCO ) (5.6)

Where T, W, P, E, (P-E) and Q accordingly represent temperatures in degrees Celsius, wind speeds in meters per seconds, total precipitation, surface evaporation in millimeters per day, the resultant of subtraction of surface evaporation from total precipitation in millimeters per day, and the mean runoff in millimeters per day. The subscript (f) is for future simulation, and the subscript (b) is for the baseline simulation.

5.1.3 Using GIS technology

An approach to use GIS in reading meteorological data as features, points, or polygons, and carrying basic statistical operations on the resultant layers were performed repeatedly for temperature, precipitation, evaporation, runoff and wind speeds. Points represent cities and meteorological stations, while the polygons represent defined regions of Saudi Arabia. The defined six regions and thirty seven locations scattered all over Saudi Arabia were studied separately. This part of research is my main focus in this project to establish a procedure in which GIS capability is explored and implemented to enrich and emphasize research findings. I do not conceder myself an expert in GIS, but I learned in a previous university introductory course enough guidance to implement very useful techniques. I am sure that GIS has much bigger role to play in climate change studies and I will be satisfied to nook gently on this door. This work stands alone in Saudi Arabia, and can initiate further interests among the scientific communities. I started by utilizing GIS data for Saudi Arabia’s political boundaries, coastal shores and others provided by Presidency of Meteorology and Environment (PME). The chosen six regions of Saudi Arabia were communicated to GIS by using x and y values for the vortices of each region and then connecting the vortices. Similarly, main cities and meteorological stations were located from their latitudes and longitudes. Some enhancement to the appearance of the map was done, and then tested several ways to get the output data from the climate model to GIS. I was able to get the data to GIS by joining features from Microsoft Office access’ data base that was created from an Excel file, but I found it simpler just to copy the desired column of data from Excel and paste it on the desired layer using ArcMap’s editors after creating the corresponding field in ArcCatalog. The means of climate fields were created as features in every region and every meteorological station. Historical, predicted, and percentages of climate change results were viewed as multi variable bar charts by implementing “symbology” in layer’s properties. The technique of applying “Spatial Analyst” from “Toolbars”, interpolating the data to Raster, and using Kriging option to produce filled contours was carried out on climate variables for comparison and study.

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5.2 Data

Several types of data were used to run the model software (PRECIS) 1. 31-year of boundary data (1960-1990) integration of HadAM3P, a 150 km resolution Hadley Center’s global atmospheric model. 2. 31-year of boundary data (2070-2100) integration of HadAM3P consistent with the SRES A2 emissions scenario. 3. 31 year of boundary data (1960-1990) of {ERA40 (1957-2001)} reanalysis data derived from ECMWF (European Center for Medium-Range Weather Forecasting). 4. Local historical data (1961- 2005) observed by Presidency of Meteorology and Environment (PME) meteorological stations (figure 4a).

Figure 4a Figure 4b Figure 4a shows the locations of the selected 37 stations which include PME Meteorological stations are spread all over Saudi Arabia, while (Figure 7b) represent the chosen six regions covering Saudi Arabia. The boundary of each region is determined by table 2. 5.3 Study Areas

Saudi Arabia is divided to 6 regions as in (Tables 1), and presented in (Figure 4b). The regions are chosen in relation to geological, meteorological and hydrological characteristics as follow:

1. Eastern Region: The area is between 43 and 51 degrees East of longitudes, and between 25 and 30 degrees north of latitudes. Dhahran, Dammam, Hafr Al Batin, Al Ahsa, and are included in this region.

2. Central Region: It is bounded by the longitudes of 43 East and 47 East, and latitudes of 21 North and 25 North. is the major city in this region.

3. Western Region: This is bounded by longitudes 37 East and 43 East, and latitudes 21 North and 25 North. This area includes Makka, Madina, , Taif and Yanbu.

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4. Northern Region: This area is between 35 East and 43 East longitudes and between 25 North and 33 North. Qasim, Hail, Tabuk, Quriyat, Rafha, Traif, Arar, Aljouf and Wejh are among the cities and towns covered by this region.

5. Southern Region: It is bounded between longitudes 40 East and 47 East, and latitudes 15 North and 21 North. This area includes , Khamis Mushait, and Gizan.

6. Empty Quarter Region: It is bounded by longitudes 47 East and 56 East, and by latitudes 17 North and 25 North. Sharoura and Sulayel are included in this region.

Table1: The areas covered by the regions are determined by rectangular shapes bounded by certain degrees of longitudes and latitudes.

Number Name of the Western Southern Eastern Northern region Longitude Latitude Longitude Latitude 1 Eastern 43 E 25 N 51 E 30 N 2 Central 43 E 21 N 47 E 25 N 3 Western 37 E 21 N 43 E 25 N 4 Northern 35 E 25 N 43 E 33 N 5 Southern 40 E 15 N 47 E 21 N 6 Empty 47 E 17 N 56 E 25 N Quarter

5.4 Studied Locations

Thirty seven separate locations (Figure 7a) were chosen to present the spread effects of climate change and to determine the more sensitive areas to changes in climate. There are 28 stations that are supervised by PME and have continuous records of hourly and daily observations. The need arise to adopt other locations to have a beter representation of the area. Reanalysis data (ERA40) is used as a historical data for those stations as will as each of the six regions. PME data is used as historical data for available stations. Table 3 describes the regions in terms of the included PME stations with their corresponding longitudes and latitudes.

6. Results

Temperature

Eastern Province region has the maximum increase in temperature as it registered an increase of 4.5 degrees Celsius (Table 2, Figures 5a, 5b), while the southern region recorded the minimum increase of daily temperature (3.9 degrees Celsius).

8 The analysis of stations’ records with the help of GIS shows an increase of 5 degrees Celsius on a tong extending from north towards the middle of Saudi Arabia (Figure 5b).

Table 2: The temperature for each region is presented in this table in degrees Celsius. The present temperature is represented by (T_historical). The future temperature is (T_Scenario). The change in temperature is presented in degrees Celsius by the column (Climate Change) and in percentages by the column (Percentage).

Region T_historical T_Scenario PERCENTAGE Climate Change 1 24.3695 28.8695 18.46571 4.5 2 26.3556 30.5556 15.93589 4.2 3 26.3784 30.4784 15.54302 4.1 4 22.27435 26.47435 18.85577 4.2 5 27.02295 30.92295 14.43218 3.9 6 27.6484 31.8484 15.19075 4.2

Figure 5a Figure 5b Daily average temperatures in degrees Celsius by regions are shown in (Figure 5a), while (Figure 5b) shows daily average temperature by locations.

6.2 Precipitation

Most of the regions of Saudi Arabia show a significant increase in precipitation (30 % or more) except the northern region where it registered a 4 % decrease in average daily precipitation (Table 3, Figures 6a, 6b). The maximum increase of 46 % is owned by the central region of Saudi Arabia. The Empty Quarter’s region shows an increase of 38 % in precipitation which is highly welcomed. In terms of the total amount of precipitation, the southern region stands tall for staying as the region with the maximum amount of daily average of precipitation. The southern region will experience an increase of average daily precipitation from 0.73 to 1.0 millimeter per day. The region with 2 nd in the future amount of precipitation is the Empty Qaurter with 0.47 millimeter per day. Analysis with the thirty seven locations in Saudi Arabia shows a maximum percentage increase of daily average precipitation over eastern coast of Saudi Arabia where Dhahran recorded an increase of 111 % in total average daily precipitation (Figure 6b).

9 Table 3:

The daily average precipitation by regions in millimeter per day. Region Historical Scenario Climate Percentage Change 1 0.25969 0.337141 0.298246 29.82456 2 0.237979 0.348088 0.462687 46.26866 3 0.18016 0.252224 0.4 40 4 0.231123 0.22155 -0.04142 4.142012 5 0.73407 0.995349 0.355932 35.59322 6 0.336428 0.465739 0.384365 38.43648

Figure 6a Figure 6b Figure 6a shows the mean daily precipitation in millimeter per day by regions, the contour analysis of the percentage change of the mean daily precipitation in millimeter per day and the mean daily precipitation for each location are presented in (figure 6b).

6.3 Wind Speeds Surface wind speeds are not expected to change significantly over most of the regions in Saudi Arabia (Table 4, Figure 7a). In fact, Eastern and Northern regions show a slight decrease in wind speeds. The maximum increase is expected over the Empty Quarter with the amount of 8 % in surface wind speed. Analysis of the thirty seven stations in Saudi Arabia shows a similar result as in the regional analysis where Eastern region has a maximum percentage decrease of wind speeds, and insignificant change over various regions of Saudi Arabia (Figure 7b).

Table 4: Wind speeds in meter per seconds for each region in Saudi Arabia

Region Historical Climate Scenario Percentage Change 1 4.2081 -0.05503 4.153074 5.5026 2 4.338153 0.026735 4.364888 2.67354 3 4.396215 0.008368 4.404583 0.83677 4 4.14139 -0.04954 4.091846 4.95432 5 4.079887 0.048915 4.128802 4.89146 6 4.396751 0.080306 4.477057 8.03055

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Figure 7a Figure 7b Figure 7a shows daily average wind speeds in meters per seconds by regions, while the mean wind speed for each location and the contour analysis for the percentage change of the stations’ values are represented by (Figure 7b).

6.4 Evaporation

Surprisingly average daily evaporation is not expected to increase drastically(Table 5, Figure 8a, 8b). Three percent or less of increase is expected over Eastern, Central, Western, and Northern regions. The Southern region has the maximum increase of 15 %, and the Empty Quarter stands happy with an average daily evaporation increase of 11 %. Analysis of evaporation shows a percentage maximum over Central region of Saudi Arabia decreasing circularly towards the rest of the regions in Saudi Arabia (Figure 8b).

Table 5: Average daily evaporation in millimeter per day by regions.

Region Historical Scenario Climate Percentage Change 1 0.741678 0.747427 0.007752 0.775194 2 0.837947 0.866775 0.034404 3.440367 3 0.951588 0.969888 0.019231 1.923077 4 0.751444 0.761134 0.012896 1.289566 5 1.2783 1.472824 0.152174 15.21739 6 0.798388 0.885014 0.108501 10.85011

Figure 8a Figure 8b Mean daily surface evaporation in millimeter per day by regions is presented in (Figure 8a), while Figure 8b shows the mean surface evaporation in millimeter per day by locations and the change in evaporation percentage wise.

11 6.5 Precipitation – Evaporation

This climate field is the determining factor for water resources in Saudi Arabia as there are neither rivers nor lakes in the whole region. The Northern region is worrying because the future resultant (P – E) is 5 % more than the present value. On the other hands the rest of Saudi Arabia’s regions look promising with an 11.5 % better results than the present value in the Southern region (Table 6, Figure 9a, 9b). Most of the locations show a decrease in future (P – E ) as seen in (Figure 13b), and the mean change value for all locations is – 0.02 mm/day which indicates a 20% decrease. Hail has the maximum increase with 0.016 mm/day which translates to 311% increase. Tabuk and Al Qassim come next with 100% and 66% increase respectively. Gizan has the lowest change of 0.25 mm/day but it represents only 12% decrease of the historical value. Southwest of Saudi Arabia has the minimum values of climate change. Those values increase gradually from southwest to the middle to the north of Saudi Arabia.

Table 6: Precipitation – Evaporation in millimeter per day as an indicating factor of the status of water resources in the regions of Saudi Arabia.

Region Historical Scenario Climate Percentage Change 1 -0.48199 -0.46154 -0.04242 8.801936 2 -0.59997 -0.57395 -0.04336 7.227124 3 -0.77143 -0.74614 -0.03279 4.250154 4 -0.52032 -0.53401 0.026316 5.057607 5 -0.54423 -0.51022 -0.0625 11.48412 6 -0.46196 -0.44543 -0.03578 7.744212

Figure 9a Figure 9b Mean daily values of evaporation subtracted from precipitation in millimeter per day by regions as shown in (Figure 13a) with 5% increase on the Northern Region while the rest of the regions experience negative values ranging from 4% to 11.5%. Most of the locations show a decrease in future (P – E ) as seen in (Figure 13b), and the mean change value for all locations is – 0.02 mm/day which indicates a 20% decrease. The minimum values of change are located in the southwest of Saudi Arabia increasing as we are heading towards the middle of Saudi Arabia and further northward.

12 6.6 Runoff

This climate field has the greatest percentage increase among all other considered fields (Table 7, Figure 10). The Western region has an increase of average daily runoff of 353 %, and each of the remaining regions has more than a 100 % increased. This sharp increase might warn us for a greater danger and frequencies of flash flood occurrences.

Figure 10: mean daily runoff in millimeter per day by regions. The drastic increase is apparent in all regions.

Table 7: Historical, scenario and percentages values for each region as produced by the model.

Region Historical Scenario Percentage 1 0.001146 0.003003 162.1271 2 0.001474 0.006072 311.9404 3 0.001168 0.005295 353.3558 4 0.000941 0.001895 101.415 5 0.002016 0.00672 233.3402 6 0.001679 0.004906 192.2703

. 7. Findings and Recommendations We can see that there are definite changes in climate of Saudi Arabia especially runoff, precipitation and temperature (Figures 15a, 15b). Those changes will affect the status of water resources in Saudi Arabia. We conclude that the resultant effect of climate change is mostly positive with respect to water resources management.

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Figure 11a Figure 11b Figure 11a represents the climate fields in percentages of climate change without the runoff, while (Figure 11b) includes the runoff. • Global warming will be felt locally in Saudi Arabia and a change of 3–5 degrees Celsius in mean daily temperature can have big effects on agriculture, energy consumptions, and various aspects of daily life. • The mean precipitation amount will increase sharply in some areas which brings concerns about more frequent flash flood. • There is a need to expand the research to include the impacts of climate change in Saudi Arabia, and finding ways to be better prepared to deal with climate change. • I recommend initiating a national center for climate change research that connect with scientists and law makers to design long national development plans that include climate change. • Using RCM includes several uncertainties, but using GIS technology will enhance presenting the results of the model’s runs. I am sure that there are many wonderful features in the GIS that can be used to do further analysis and to build an interface program that allows GIS to convert the model outputs to be read and analyzed by GIS system. • Precis can produce reasonable predictions of the future state of climate over Saudi Arabia, and GIS is an excellent tool to explore the outputs of the model. • Using latest models to predict climate change can produce better data, and more accurate information. This can improve sharply long time management of the water resources.

8. Acknowledgements

We thank the following for their kind cooperation, assistance and support throughout the research period: • Prince Turky bin Nasser, The president of PME. • Dr. Baqer Al Ramadhan and Mr. Mohammed Raziudean from KFUPM. • Dr. Walid Abdulrahman, and Dr. Ahmat Aksakal from RI at KFUPM. • Dr. Abdulaziz Al-shaibani from Earth Science Department at KFUPM. • Mr. Amisu Salam. • Mr. Mustapha Ismail and Mr. Hamza Hallawani from PME. • Dr. Joseph Intsiful and Mr. David Hein from UK Met Office. • UK Met Office for supplying précis system and essential data.

14 9. References

1. Abderrahman, W. A., Rasheeduddin, M.,Lloyd, J., 2001, Management of Groundwater Resources in Eastern Saudi Arabia, International Journal of Water Resources Development, 17, pp. 185-210 2. Lau Chi-Chung, Lee Kwan-Tun, Tung Ching-Pin, Chang Chin-Hsin, 1999, Assessment of Climate-Change Impact on Runoff Using Normalized Difference Vegetation Index, available at (http://www.gisdevelopment.net/aars/acrs/1999/ts2/ts2045pf.htm ). Last accessed 24 January 2008. 3. Le Treut, H., R. Somerville, U. Cubasch, Y. Ding, C. Mauritzen, A. Mokssit, T. Peterson and M. Prather, 2007, Historical Overview of Climate Change. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. 4. Loa´iciga, H. A. 2007, Climate Change and Groundwater, available at http://ncsp.va-network.org/section/resources/resource_water . (Last accessed Jan24th, 2008) 5. Loa´iciga, H. A. 2000, Climate-change impacts in regional-scale aquifers: Principles and field application. In Ground water updates, ed. K. Sato and Y. Iwasa, 247–52. Tokyo: Springer-Verlag. 6. L oa´iciga, H. A. 1997. Runoff scaling in large rivers of the world. The Professional Geographer 49 (3): 356–63.

7. Jones, R. G., Noguer, M., Hassell, D.C., Hudson, D., Wilson, S.S., Jenkins, G.J. and Mitchell, J.F.B., 2004, Generating high resolution climate change scenarios using PRECIS, Met Office Hadley Center, Exeter, UK, 40pp. 8. Nebojsa Nakicenovic, Joseph Alcamo, Gerald Davis, Bert de Vries, Joergen Fenhann, Stuart Gaffin, Kenneth Gregory, Arnulf Grübler, Tae Yong Jung, Tom Kram, Emilio Lebre La Rovere, Laurie Michaelis, Shunsuke Mori, Tsuneyuki Morita, William Pepper, Hugh Pitcher, Lynn Price, Keywan Riahi, Alexander Roehrl, Hans-Holger Rogner, Alexei Sankovski, Michael Schlesinger, Priyadarshi Shukla, Steven Smith, 2000, IPCC Special Report on Emissions Scenarios, available at (http://www.grida.no/climate/ipcc/emission/501.htm ). Last accessed January 24 th 2008. 9. Shdeed S., Shaheen H., Jayyousi A., 2007, GIS-Based KW-GIUH Hydrological Model of Simarid Catchment: The Case study of Faria Catchment, Palestine, The Arabian Journal for Science and Engineering, Volume 32, Number 1C.

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