Rainfall Analysis for the Northern Wadis of United Arab Emirates: A Case Study

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1 Rainfall Analysis for the Northern s of United Arab Emirates: A Case Study Mohsen Sherif 1 ; Salem Akram 2 ; and Amapr Shetty 3 Downloaded from ascelibrary.org by United Arab Emirates University on 10/22/17. Copyright ASCE. For personal use only; all rights reserved. Abstract: The rainfall distribution in space and time, its consistency, probability of occurrences, and drought conditions in three selected wadis in the northern area of the United Arab Emirates UAE have been investigated. Like other arid and semi-arid regions, rainfall in the selected wadis is limited, scattered, and random. The standard deviation and coefficient of asymmetry of the rainfall patterns are relatively high. The three wadis have similar rainfall patterns based on the monthly, annual, and 24-h maximum rainfalls. Empirical equations were developed to estimate the annual and 24-h maximum rainfalls. A probability analysis is carried out for the annual and 24-h maximum rainfalls and probability graphs are developed with a confidence level of 95%. Intensity duration frequency curves are developed for the three wadis. A conceptual model is used in drought characterization. The available rainfall data of the three wadis are analyzed for drought intensity, duration, and frequency. Based on the drought characterization, the study region is classified as arid. The present study constitutes the first comprehensive analysis for rainfall in UAE. DOI: / ASCE HE CE Database subject headings: Rainfall; Droughts; United Arab Emirates; Case reports. Introduction The United Arab Emirates UAE lies in the southeastern part of the Arabian peninsula between latitudes and North and longitudes and East. It is bounded from the north by the Arabian Gulf, on the east by the Sultanate of Oman and the Gulf of Oman, and on the south and the west by the Kingdom of Saudi Arabia, Fig. 1. The total area of the UAE is about 83,600 km 2. Most of the land is desert and is characterized by the predominance of Aeolian landform system. Its geomorphologic features include mountains, gravel plains, sand dunes, coastal zones, and drainage basins. The land of UAE is divided into two distinct zones: the larger low-lying zone and the mountains zone. The first covers over 90% of the country s area, extending from the northwest to the eastern part of the country where it is truncated by the mountains zone Al Hammady The low-lying zone ranges in altitude from sea level up to 300 m. Its major part is characterized by the presence of sand dunes which rise gradually from the coastal plain reaching their highest elevation of 250 m above sea level asl. Along the coast of the Arabian Gulf, the low-lying land is punctuated by ancient raised beaches and isolated hills which may reach up to 40 m asl in some locations Baghdady The UAE is known for its arid conditions. A long hot summer 1 Professor of Water Resources, Civil and Environmental Engineering Dept., College of Engineering, UAE Univ., P.O. Box Al Ain, UAE. 2 Director, Water and Dams Division, Ministry of Environment and Water, P.O. Box 1509, Dubai, UAE. 3 Hydrologist, Water and Dams Division, Ministry of Environment and Water, P.O. Box 1509, Dubai, UAE. Note. This manuscript was submitted on November 29, 2006; approved on August 12, 2008; published online on February 18, Discussion period open until November 1, 2009; separate discussions must be submitted for individual papers. This paper is part of the Journal of Hydrologic Engineering, Vol. 14, No. 6, June 1, ASCE, ISSN /2009/ /$ and short mild winter characterize its climate. The mean annual temperatures are approximately uniform throughout the country with slight local variations. The principal rain in UAE falls between November and March, with maximum intensity during February and March. Rainfall is very scarce, random, and infrequent. The mean annual rainfall is about 110 mm with extreme variability in space and time. Rainfall and runoff deficits have been observed in UAE and other neighboring Gulf Cooperation Council Countries, including Bahrain, Kuwait, Qatar, Saudi Arabia, and Sultanate of Oman Al Rashed and Sherif The annual rainfall in the Arabian Gulf region has dropped significantly since Based on the records of the last 8 years, the annual rainfall in UAE is in the order of 40 mm only. Therefore, more reliance has been placed on groundwater resources that are mostly nonrenewable and on the desalination of seawater. The recharge from the bed of ephemeral wadis and subsurface flow in valley bed in mountainous areas constitute an important element for the proper management of water resources in arid and semi-arid regions Khazei et al The successful implementation of water resources management requires knowledge of space, time, and frequency distribution of rainfall and its characteristics. Apart from the quantum of rainfall, its distribution in space and time plays a vital role in the planning and management of water resources. Risk analysis of rainfall events and design of water structures are generally based on extreme precipitation events. Therefore, evaluation of rainfall extremes through intensity duration frequency curves and intensity duration area frequency curves has been considered by many researchers for several decades Eaglson 1970; Chow et al. 1988; Willems 2000; Veneziano and Furcolo 2002; Veneziano et al. 2006, and others. This paper presents the first comprehensive study for the characterization and analysis of rainfall in the northern area of UAE. To that end, three main catchments were selected, namely Bih, Tawiyean, and Ham. Empirical relations JOURNAL OF HYDROLOGIC ENGINEERING ASCE / JUNE 2009 / 535

2 for the estimation of annual rainfall and maximum daily rainfall with different return periods are developed. Intensity duration curves are presented and a drought analysis is conducted. Although rainfall and occasional water floods may not be of significant contribution to the water budget in UAE, their assessment and analysis are vital for design of dams and mitigation of possible flood hazardous. Physical Settings of the Selected Catchments The three investigated catchment areas of Bih, Tawiyean, and Ham are located in the northern part of the UAE, Fig. 2. These areas were selected based on the availability of relatively long and accurate rainfall records. However, it should be noted that the annual rainfall in the northern areas is relatively higher than in the middle and southern regions of the country. Many detention and retention dams have been constructed across the main wadis within the selected areas for surface water harvesting and groundwater recharge. Bih, in Ras Al Khaimah Emirtae, is a large southwesterly Fig. 1. Location map of the United Arab Emirates flowing wadi complex comprising parts of the Jibal Ruus mountains of Oman in its eastern section and alluvial plains to the west and southwest around Ras Al Khaimah Emirate. The wadi topography consists of three major land forms namely, mountains, alluvial terrace, and low land. The maximum elevation of the catchment is 2,087 m above mean sea level amsl. The catchment area of Bih is about 483 km 2. Tawiyean, also in Ras Al Khaimah Emirate, is arising in the Jibal Ruus mountains and flowing west to the coastal plain. The boundary of the watershed is in common with southern boundary of Naqab. The wadi topography consists of mountains, alluvial terrace, and low land of three distinct land forms. The maximum elevation of the catchment is 1,527 m above mean sea level. The catchment area of Tawiyean dam is about 198 km 2. Ham, in Fujairah Emirates, rises in the mountains at an elevation 1,109 m amsl immediately south and south east of the Musafi, draining southeastward into the Gulf of Oman between Fujairah and Kalbha. The wadi complex comprises parts of Musafi Mountain in its northwestern portion and alluvial plains to the east around Fujairah. The catchment area of this wadi is approximately 195 km 2 Sherif et al. 2005; Halcrow / JOURNAL OF HYDROLOGIC ENGINEERING ASCE / JUNE 2009

3 Fig. 2. Location map of the three selected wadis and available rain gauges Rainfall Pattern and Characterization Rainfall forms the input of all hydrological studies. Apart from the quantum of rainfall, its time distribution plays a critical role in the planning and management of water resources. Understanding rainfall pattern of a given catchment is fundamental for any proper runoff flood investigations. The analysis of daily, monthly, annual rainfall, and 1-day maximum annual rainfall is useful to predict rainfall amount in a season for desired recurrence interval with a certain level of confidence. Methods of calculating average areal rainfall include, but are not limited to, the arithmetic average of gauged quantiles, the isohyetal map method, and the Thiessen method Singh The number of rain gauges available in the selected wadis is not sufficient to develop isohyetal maps. The Thiessan polygon method was used in this investigation to calculate the average areal precipitation over the selected catchements. Observations of rainfall within and around the selected basins were used. The Ministry of Environment and Water, MEW formerly, Ministry of Agriculture and Fisheries has been responsible for the hydrmeteorological network in the United Arab Emirates UAE since Three stations of daily data for Ham, three stations for Tawiyean, and three stations for the Bih were used. Fig. 2 presents the locations of these rain gauges. The length of data records, Thiessen weightage, and rain gauges considered for the three wadis are given in Table 1. No record of precipitation is available for the Oman region in the case of Bih. One should also recognize the difference between the mean annual rainfall in the three wadis based on the records of years and the mean annual rainfall in UAE based on the records of the last 8 10 years. The average rainfall has decreased significantly over the last 10 years. In addition, the average annual rainfall in the three wadis is relatively high as compared to other areas in the country MAF Table 1. Rain Gauge and Thiessen Weights Area km 2 Statistical Analysis Rain gauges Area km 2 Tieissen weights Period year Ham 195 Masafi Bithna Farah Tawiyean 198 Tawiyean Sinah Khatt Dibba Bih 464 Bih Sham Burayarat The random variability of hydrologic variables such as precipitation and streamflow has been recognized for centuries. The use of statistics in hydrology provides information about various parameters and distribution of random variables of rainfall analysis to design and operate water systems. Hydrologic data are mostly available as samples of limited sizes. Statistics enables the extraction of needed information from the available data and characterization of hydrologic random variables needed for rainfall and runoff analyses. Because of the high randomness and inconsistency in rainfall pattern and intensity, it might not be proper to develop water utilization plans and policies based on statistical analysis of short and medium rainfall records. Nevertheless, such analysis can be used in the design of storage dams and mitigation of flash floods. In data analysis, certain calculations are usually made to determine some of the basic inherent properties of the data. The inferences include information about the central tendency, range, distribution within the range, variability around the central tendency, degree of uncertainty, and frequency of occurrence of values Viessman and Lewis The standard deviation measures the dispersion of sample values around the mean. The skewness coefficient measures the asymmetry of the frequency distribution of the data. It has an important meaning as it gives an indication of the symmetry of the distribution of the data. Symmetrical frequency distributions have very small or negligible sample skewness coefficient C s, whereas asymmetrical frequency dis- Table 2. Statistical Value of Monthly Rainfall Distribution in Ham Month Rainfall range Mean %of normal R fall S.D. October November December January February March April May June July August September JOURNAL OF HYDROLOGIC ENGINEERING ASCE / JUNE 2009 / 537

4 tributions have either positive or negative coefficients. A small value of C s often indicates that frequency distribution of the sample may be approximated by the normal distribution function as C s =0 for this function. The kurtosis coefficient measures the peakedness or the flatness of the frequency distribution near its center. The positive value of an excess coefficient indicates that a frequency distribution is more peaked around its center than the normal distribution. The negative value of an excess coefficient indicates that a given distribution is more flat around its center than the normal. Statistical analyses of monthly and annual mean rainfall for the three selected wadis were carried out. The statistical results of the rainfall in the three wadis are presented in Figs. 3 5 and Tables 2 6. Annual rainfall in Ham ranges from 7.6 to mm indicating a wide variation from one year to another. Average rainfall estimated based on the records of the last 25 years is 151 mm with a standard deviation of mm, a kurtosis coefficient of 1.36, and a coefficient of asymmetry of Fig. 3. Distribution of mean annual rainfall, Ham 1.18, Table 5. The probabilities of occurrence of 75 and 50% of the average rainfall are estimated as 51 and 64%, respectively. It implies that the distribution of rainfall in Ham is highly scattered. Rainfall events in Ham are observed between January and December but are mostly encountered during the months of February and March. More than 50% of annual rainfall normally occurs during these two months. Monthly rainfall values range from 0 to 198 mm, the mean monthly varies from 1 to 41 mm with a standard deviation varying between 2 and 61 mm, Table 2. The monthly standard deviation exceeds the monthly average precipitation revealing that the year-to-year monthly variation in precipitation is quite extreme in the area. The 24-h maximum rainfall values range from 2 to 137 mm and the mean is 50 mm with a standard deviation 34 mm. The kurtosis coefficient is 0.69 and coefficient of asymmetry is 1.06, Table 6. The probabilities of occurrence of 75 and 50% of mean 1-day maximum rainfall are 57 and 79%, respectively. Fig. 4. Distribution of mean annual rainfall, Tawiyean 538 / JOURNAL OF HYDROLOGIC ENGINEERING ASCE / JUNE 2009

5 Annual rainfall in Tawiyean catchment area ranges from 4 to 430 mm. Based on the rainfall records of the last 23 years, the average annual rainfall is estimated as 129 mm with a standard deviation of 115 mm, a kurtosis coefficient of 0.46, and a coefficient of asymmetry of 0.95, Table 5. The probabilities of occurrence of 75 and 50% of the average rainfall are estimated as 57 and 72%, respectively. Again the rainfall is distributed between January and December but mostly encountered during the two months of February and March. Monthly rainfall values range from 0 to 156 mm and mean monthly varies from 0 to 36 mm with variation of the standard deviation from 0 mm, where mean monthly rainfall is zero, to 45 mm, Table 3. The monthly standard deviation exceeds the monthly average precipitation indicating that the year-to-year monthly variation in precipitation is quite high in the area. The 24-h maximum rainfall values range between 2 and 86 mm with a mean value of 36 mm and a standard deviation of 23 mm. The kurtosis coefficient is 0.69 and the coefficient of asymmetry is 0.46, Table 6. The probabilities of occurrence of 75 and 50% of mean 1-day maximum rainfall are 55 and 77%, respectively. Table 3. Statistical Value of Monthly Rainfall Distribution in Tawiyean Month Rainfall range Mean %of normal R-fall S.D. October November December January February March April May June July August September Fig. 5. Distribution of mean annual rainfall, Bih The annual rainfall in Bih ranges from 6 to 414 mm. Based on the records of the last 22 years, the average rainfall is estimated as 119 mm with a standard deviation of 109 mm, a kurtosis coefficient of 0.53, and a coefficient of asymmetry of 0.89, Table 5. The probabilities of occurrence of 75 and 50% of the average rainfall are estimated as 51 and 67%, respectively. Like the other two wadis, this implies that the distribution of rainfall in Bih is scattered and random. Rainfall events are also observed between January and December with about 50% of the annual rainfall occurring in February and March. Monthly rainfall values range between 0 and 176 mm and the mean monthly varies from 0 to 34 mm with a variation of the standard deviation from 0, where the mean rainfall is zero, to 50 mm, Table 4. The monthly standard deviation exceeds the monthly average precipitation. The 24-h maximum rainfall values range between 3 and 105 mm with a mean of 33 mm and a standard deviation of 24 mm. The kurtosis coefficient is 3.26 and the coefficient of asymmetry is 1.50, Table 6. The probabilities of occurrence of 75 and 50% of mean rainfall are 51 and 68%, respectively. Probability is a constant characterizing a given set of objects Table 4. Statistical Value of Monthly Rainfall Distribution in Bih Month Rainfall range Mean %of normal R fall S.D. October November December January February March April May June July August September JOURNAL OF HYDROLOGIC ENGINEERING ASCE / JUNE 2009 / 539

6 Table 5. Statistical Value of Annual Rainfall Distribution Rainfall range Mean S.D. Kurtosis Coefficient of asymmetry Probability of occurrence of 75% average Probability of occurrence of 50% average Ham Tawiyean Bih Downloaded from ascelibrary.org by United Arab Emirates University on 10/22/17. Copyright ASCE. For personal use only; all rights reserved. or incidents in a particular period. The probability can be conveniently estimated if the length of available data is sufficient. The available rainfall data in the three wadis are used to fit probability distribution which is then used to extrapolate design events from the recorded events either graphically or by estimating the parameters of frequency distribution. The 24-h maximum and the mean annual rainfall data for the three selected wadis were analyzed for estimating the expected rainfall at different return periods using Gauss, Lognormal, Gumble, Pearson Type-III, and Weibull distribution formula Singh The formula proposed by Weibull was found to be theoretically suitable for plotting the annual maximum series. It provides estimates that are consistent with experience Hann and Shapiro Weibull formula can be mathematically expressed as F a = m/n where N=total number of data items; m=number of items arranged in descending order of magnitude; and F a =plotting position. In this study, Weibull formula was used to estimate the return periods and the 95% confidence interval was also drawn to indicate the likely range of the true value of the quantile. Usually, an error of 5% is considered acceptable Singh 1992; Helsel and Hirsch Rainfall for different probabilities of 1-day annual maximum and annual mean rainfall were determined from probability graphs and corresponding values were deduced. The estimated annual rainfall and 24-h maximum rainfall for the corresponding return periods are provided in Tables 7 and 8. In Ham, the estimated annual rainfall for a 2-year return period is 112 mm and for 100-year return period is 691 mm Table 7. The model for the estimation of annual rainfall for the corresponding return period is R ah = ln T H where R ah =annual rainfall in Ham and T H is the return period. This equation can be expressed in a standard form as T H = e P / where P = annual precipitation in millimeters. The observed values are within the 95% confidence interval of the fitted values with a coefficient of determination of In other words, 98% of the recorded annual rainfall is included in the estimated rainfall. Also, the estimated 24-h maximum rainfall for a 2-year return period is 44 mm and for 100-year return period is 202 mm Table 8. The model for the estimation of the 24 h maximum rainfall for the corresponding return period in Ham is given as R 24H = ln T H where R 24H =24-h maximum rainfall in Ham. The estimated annual rainfall of Tawiyean for the 2-year return period is 116 mm and for 100-year return period is 670 mm. The model for the estimation of annual rainfall in Tawiyean for the corresponding return period is R at = ln T T where R at =24-h maximum rainfall and T T =return period in years for Tawiyean. Eq. 5 can also be expressed in a standard form as T T = e P / where P = annual precipitation in millimeters. The observed values are within 95% confidence interval of the fitted values with a coefficient of determination of On the other hand, the estimated 24-h maximum rainfall for the 2-year return period is 30 mm and for the 100-year return period is 135 mm. The model for the estimation of the 24-h maximum rainfall for the corresponding return period is R 24T = ln T T where R 24T =24-h maximum rainfall in Tawiyean. The observed values are within the 95% confidence interval of the fitted values with a coefficient of determination of about 0.91, i.e., 91% of the observed 24-h maximum rainfall is included in the estimated range of rainfall Table 6. Statistical Value of 1-Day Annual Maximum Rainfall Distribution Rainfall range Mean S.D. Kurtosis Coefficient of asymmetry Probability of occurrence of 75% average Probability of occurrence of 50% average Ham Tawiyean Bih / JOURNAL OF HYDROLOGIC ENGINEERING ASCE / JUNE 2009

7 Table 7. Estimated Return Period of Annual Rainfall Return Estimated rainfall period Ham Tawiyean Bih In Bih, the estimated annual rainfall for the 2-year return period is 97 mm and for the 100-year return period is 614 mm. The model for the estimation of annual rainfall in Bih for the corresponding return period is given as R ab = ln T B where R ab =24-h maximum rainfall and T B =return period in years in Bih. This equation can be expressed in a standard form as T B = e P / The observed values are within the 95% confidence interval of the fitted values with a coefficient of determination of about The estimated 24-h maximum rainfall for the 2-year return period Table 8. Estimated Return Period of 24-h Maximum Rainfall Return Estimated rainfall period Ham Tawiyean Bih Table 9. Range of Rainfall Intensity and Duration Data period Range of duration h is 26 mm and for 100-year return period is 140 mm. The model for the estimation of 24-h maximum rainfall for the corresponding return period is R 24B = ln T B where R 24B =24-h maximum rainfall in Bih. The observed values are within the 95% confidence interval of the fitted values with a coefficient of determination of about As the standard deviations are invariably more than the mean monthly rainfall, the occurrence of rainfall is highly nonuniform, empirical equations and probability estimators may not satisfactorily forecast future rainfall occurrence. Nevertheless, empirical equations that are based on statistical analysis of rainfall in arid regions can be used for long-term predictions, e.g., maximum rainfall in 100 years, which are needed for design of storage dams and mitigation of floods. Intensity Duration Frequency Analysis Range of intensity mm/h Ham Tawiyean Bih Rainfall intensity is one of the most important factors affecting the generation of surface water runoff especially from mountainous watersheds. The average intensity, peak intensity, and duration are mainly dependent on the interevent time considered during the isolation of storm events. The rainfall events are isolated with minimum interevent time of 1 h. The durations of rainfall events and rainfall intensities have been calculated. Ranges of storm durations and intensities in the three selected wadis are presented in Table 9. It is evident from the available data that shorter duration rainfalls have higher intensity. Intensity duration curves have been developed as pre- Fig. 6. Smoothened intensity duration curve, Ham JOURNAL OF HYDROLOGIC ENGINEERING ASCE / JUNE 2009 / 541

8 sented in Figs However, it should be noted that the characteristic of intensity duration curve is averaged over the specified duration. The curve represents the smoothed results of different storms. The range of event duration varies from 0.25 to 26 h in Ham, from 0.25 to 39 h in Tawiyean, and from 0.25 to 45 h in Bih. The intensity of rainfall varies from 0.6 to 58 mm/h in Ham. In Tawiyean it varies from 0.3 to 48 mm/h and in the case of Bih it varies between 0.5 and 34 mm/h. Ham has lower durations of storm events and higher rainfall intensities as compared to Tawiyeana and Bih. To the contrary, Bih is distinguished by its longer durations and smaller intensities of rainfall events. In Ham, 96% of rainfall events during the last 25 years had a duration of 6 h or less, Fig. 6. In Tawiyean and Bih rainfall events are generally of longer durations, Figs. 7 and 8. Typical storm durations Fig. 7. Smoothened intensity duration curve, Tawiyean and the corresponding intensity ranges for the three selected wadis are presented in Table 10. The intensity duration frequency curves were developed and are presented in Figs for a frequency ranging from 2 to 250 years. In Ham, the maximum expected intensity for a 2-year return period is about 17 mm/h, whereas for the 250-year return period the maximum expected intensity is about 100 mm/ h. In Tawiyean, the predicted maximum intensity is about 10 mm/h for the 2-year return period and 85 mm/h for the 250-year return period. In the case of Bih, the maximum intensity for a 2-year return period is around 10 and 77 mm/h for the 250-year return period. The variation in the storm intensity for a duration between 0.25 and 0.50 h is relatively small for the cases of Tawiyean and Bih as compared to Ham, Table 10. When the duration of the storm is 2.5 h or more the rainfall intensity for all return periods in the three wadis fall Fig. 8. Smoothened intensity duration curve, Bih 542 / JOURNAL OF HYDROLOGIC ENGINEERING ASCE / JUNE 2009

9 Table 10. Typical Storm Duration and its Intensity Range Intensity range mm/h 0.25 h 0.50 h 1.00 h 2.00 h 3.00 h 5.00 h Ham Tawiyean Bih Downloaded from ascelibrary.org by United Arab Emirates University on 10/22/17. Copyright ASCE. For personal use only; all rights reserved. Table 11. Drought Analysis of the Three Selected s within 20 mm/h. Long rainfall storms are of small intensities in the three wadis. Drought Analysis Number of years Mean annual rainfall Number of events Average intensity Drought is a normal and recurrent feature of the climate. It occurs in virtually all climatic zones and its characteristics vary significantly among regions. Drought differs from aridity in that drought is temporary; aridity is a permanent characteristic of regions with low rainfall. Drought produces a complex web of impacts which spans many sectors. The intensity, duration, and frequency of droughts have a major influence on societies. The relations among drought intensity, duration, and frequency can be analyzed using the conceptual model developed by Ponce et al The conceptual approach is applicable to subtropical and midlatitudinal regions and is limited to meteorological droughts lasting at least 1 year. For any year for which P is the annual precipitation, drought intensity is defined as the ratio of the deficit P ma P to the mean P ma. For any particular year, an intensity of P ma P / P ma =0.25 is classified as moderate, 0.5 is classified as severe, and 0.75 is classified as extreme. For drought events lasting more than 1 year, intensity is the summation of the individual annual intensities. Therefore, extreme drought intensities are generally associated with droughts of long duration. Drought characterizations in Ham, Tawyiyean, and Bih have been performed using the conceptual model of Ponce et al Drought intensity, duration, and frequency for these three wadis were estimated and are presented in Table 11. Drought intensity per event in Ham varies from 0.30 to 4.52, with an average value of Drought duration ranges from 1 to 7 years, with an average value of 2.35 years. The average frequency of the drought is 4.17 years, Table 11. In Tawiyean, the drought intensity per event varies from 0.07 to 5.03, with an average value of Drought duration ranges from 1 to 7 years with an average value of 2.8 years. The average frequency of the drought in Tawiyean is 4.6 years. On the other hand, the drought intensity per event in Bih varies from 0.30 to 5.28 with an average value of Drought duration ranges from 1 to 7 years, with an average value of 2.6 years. The average frequency of the drought in Bih is 4.4 years. The longest mean drought duration 2.8 years occurred at Tawiyean and the shortest 2.35 years occurred at Bih. The average drought duration in the three wadis is about 2.6 years. Conclusions Duration year Average duration year Average frequency year Ham Tawiyean Bih The annual mean rainfall of the three selected wadis in the northern part of UAE ranges between 119 and 151 mm with standard deviations varying between 109 and 126 mm. However, recent rainfall records indicate a remarkable decline in rainfall frequency, intensity, and duration. The probability of occurrence of 75 and 50% of the average annual rainfall varies between 51 57% and 64 72%, respectively. More than 50% of the annual Fig. 9. Intensity duration frequency curve, Ham Fig. 10. Intensity duration frequency curve, Tawiyean JOURNAL OF HYDROLOGIC ENGINEERING ASCE / JUNE 2009 / 543

10 Dubai, UAE. Several individuals from the MEW and the UAE University have contributed in the field activities and data collections related to this paper. Downloaded from ascelibrary.org by United Arab Emirates University on 10/22/17. Copyright ASCE. For personal use only; all rights reserved. Fig. 11. Intensity duration frequency curve, Bih rainfall occurs in February and March. The values of mean 1-day annual maximum rainfall vary between 33 and 50 mm with standard deviations in the range of mm. The probability of occurrence of 50% of mean 1-day annual maximum rainfall in the three wadis varies between 68 and 79%. Rainfall events with durations of 2.5 h or more have intensities of 20 mm/h or less for all return periods. The developed intensity patterns of the three wadis can be used in the assessment of surface water runoff from various rainfall events of different frequencies. This will be addressed in the writers next paper on the assessment and perdition of surface water runoff in the three wadis. Weibull distribution provided good agreement with the available rainfall records with a 95% confidence level of the estimated quantiles in three wadis. The high values of standard deviations and coefficients of asymmetry are attributed to scattereness and randomness of the rainfall events in the area. The rainfall characteristics in Tawiyean and Bih are relatively similar due to the proximity of the geographical locations of the two wadis. Drought characterization has been performed for the three wadis using the conceptual model of Ponce et al The three wadis are classified as arid with average drought durations of 2.35, 2.8, and 2.6 years in Ham, Tawiyean, and Bih, respectively. The average drought duration in the three wadis is 2.6 years. Acknowledgments The research and results presented in this paper have been completed within the activities of a project entitled Assessment of the Effectiveness of Al Bih, Al Tawyean and Ham Dams in Groundwater Recharge using Numerical Models. The project was support by the Ministry of Environment and Water MEW, References Al Hammadi, M. K Assessment of groundwater resources using remote sensing and GIS. MSc thesis, Water Resources Master Program, UAE Univ., United Arab Emirates. Al-Rashed, M. F., and Sherif, M. M Water resources in the GCC countries: An overview. Water Resour. Manage., 14 1, Baghdady, A. R Petrography, mineralogy and environmental impacts of the sand dune fields of the greater Al Ain area, United Arab Emirates. Ph.D. thesis, Faculty of Science, Ain Shams Univ., Ain Shams, Egypt. Chow, V. T., Maidment, D. R., and Mays, L. W Applied hydrology, McGraw-Hill, New York. Eaglson, P. S Dynamic hydrology, McGraw-Hill, New York. Halcrow International Partnership Dams and recharge facilities site investigation Tawiyean. Geophysical survey, Vol. 3, Pt. A, Ministry of Agriculture and Fisheries currently Ministry of Environment and Water, Dubai, United Arab Emirates. Hann, G. J., and Shapiro, S Statistical models in engineering, Wiley, New York. Helsel, D. R., and Hirsch, R. M Statistical methods in water resources, 4th Ed., Elsevier Science, Amsterdam, The Netherlands. Khazaei, E., Spink, A. E. F., and Warner, J. W A catchment water balance model for estimating groundwater recharge in arid and semiarid regions of southeast Iran. Hydrogeol. J., 11 3, Ministry of Environment and Water MAF Climatological data, Vol. 4, to , United Arab Emirates. Ponce, V. M., Pandey, R. P., and Ercan, S Characterization of drought across the climatic spectrum. J. Hydrol. Eng., 5 2, Sherif, M. M., et al Assessment of the effectiveness of Al Bih, Al Tawiyean and Ham Dams in groundwater recharge using numerical models. Final Rep., Vol. 1: Main report, Ministry of Environment and Water, Dubai, United Arab Emirates. Singh, V. P Elementary hydrology, Prentice-Hall, Englewood Cliffs, N.J. Veneziano, D., and Furcolo, P Multifractality of rainfall and intensity-duration-frequency curves. Water Resour. Res., 38 12, Veneziano, D., Langousis, A., and Furcolo, P Multifractality and rainfall extremes: A review. Water Resour. Res., 42, W06D15. Viessman, W., and Lewis, G. L Introduction to hydrology, 5th Ed., Prentice-Hall, Pearson Education, Inc., Englewood Cliffs, N.J. Willems, P Compound intensity/duration/frequency relationships of extreme precipitation for two seasons and two storm types. J. Hydrol., , / JOURNAL OF HYDROLOGIC ENGINEERING ASCE / JUNE 2009