To study the temporal and spatial variations of the groundwater quantity and quality in response to intensive groundwater exploitation from the Quaternary aquifer in UAE, a water budget model with a cell size of one km2 was developed. The available historical records of groundwater levels and salinity have been used to develop the water table and salinity maps of UAE for the years 1969, 2005, 2010, and 2015. The available water resources and soil information system was used to facilitate validity, cogency, and consistency of the groundwater analysis. The spatial analysis module of GIS was used to define the aquifer setting, saturated thickness, aquifer base elevation, effective porosity, and groundwater salinity at each grid cell. The obtained results indicated that the volume of fresh groundwater resources in the Quaternary aquifer in UAE has decreased from 238 km3 in 1969 to around 10 km3 in 2015. A major part of these depleted fresh groundwater resources was replaced by brackish water, and, therefore, the total groundwater storage in this aquifer has only decreased from 977 in 1969 to 922 km3 in 2015, respectively. If the same groundwater exploitation continues, the freshwater storage in the surficial aquifer might be totally depleted in agricultural areas. Most probably, the brackish groundwater resources will be exploited. In such areas, more attention should be devoted to the management of brackish water resources to avoid the exacerbation of the saltwater intrusion problem. Despite the fact that the obtained results indicate the negative impacts of the improper water resources management in a small part of the arid area, the learned lessons are valid for other arid countries, in particular, using the proper steady state boundary conditions for the initial conditions in modeling the available future management alternatives.
Groundwater extraction in most Middle East and North Africa (MENA) countries far exceeds its renewability, which ranges from 6% to 100%. Freshwater resources to support food production are very limited in this region. Future climate predictions include more consistent and longer wet periods with increasing surplus rainfall, which will enhance flood and flash flood occurrences in the MENA. Demand management of groundwater resources and managed aquifer recharge (MAR, also called groundwater replenishment, water banking, and artificial recharge, is the purposeful recharge of water to aquifers for subsequent recovery or environmental benefits) represent essential strategies to overcome the challenges associated with groundwater depletion and climate change impacts. Such strategies would enable the development of groundwater resources in the MENA region by minimizing the stress placed on these resources, as well as reducing deterioration in groundwater quality. Groundwater augmentation through recharge dams is a common practice in different countries around the globe. Most dams in the MENA region were built to enhance groundwater recharge, and even the few protection dams also act as recharge dams in one way or another. However, the operating systems of these dams are mostly dependent on the natural infiltration of the accumulated water in the reservoir area, with limited application of MAR. This review presents analyses of groundwater renewability and the effectiveness of recharge dams on groundwater recharge, as well as the potential of MAR technology. This study indicates that the recharge efficiency of dam’s ranges between 15 to 47% and is clustered more around the lower limit. Efficiency is reduced by the clogging of the reservoir bed with fine materials. Therefore, there is a need to improve the operation of dams using MAR technology.
The Khatt, Madab, and Al Ghmour Springs are important springs in UAE. They are located in the foothills of the Oman Mountains. The water temperature of these springs is relatively high (approximately 39 °C). Overexploitation of fractured aquifers negatively affected the waterflows from these springs. The outflows from these springs are time-dependent and range from 10 to 50 L/s (until 1998) to 1–10 L/s (until 2010). To assess the current conditions of the spring areas, relevant data were carefully reviewed, analyzed, and stored in a GIS database. A 3D-geological model was developed for the Khatt Springs area, which allowed different types of visualizations, calculations, and predictions. In addition, a 2D earth resistivity imaging survey was performed to evaluate the available groundwater resources, characterize the major faults/fractures feeding these springs, and to determine the locations of saturated fractures and karsts and the thicknesses of the unconsolidated materials in the wadis. Borehole and drilling information from observation wells were utilized to enhance the analysis of the earth resistivity imaging data. The described procedures and acquired results indicated that it was possible to determine the locations of two production wells for feeding Al Ghmour Springs with water during drought periods to keep it alive.
<p>Water balance closure using purely remote sensing products was difficult to achieve until the launch of Gravity Recovery and Climate Experiment (GRACE) satellites in 2002. The accurate quantification of<strong> </strong>water cycle components (precipitation, evapotranspiration, runoff, and terrestrial water storage) over a large-scale basin is an important step in improving the understanding of the water balance and the response of the basin to different hydrologic extremes. The Upper Blue Nile (UBN) basin contributes about 60% of the streamflow to the main Nile River annually, and hundreds of millions of people heavily rely on the Nile River. Thus, accurate quantification of the hydrological cycle fluxes will help manage the water resources in an effective, sustainable manner. Hydrometeorological data is lacking; nevertheless, remote sensing data provides an alternative approach to estimating the water cycle components. However, prior to incorporating these products into the water budget calculation, their performance over the studied basin should be assessed. In this study, we aim to estimate runoff from the water budget equation and diagnose the estimated runoff with the Eldiem gauge records at the outlet of the UBN basin for the 2003&#8211;2014 period. We evaluate the water cycle components for seven rainfall products (CHIRPSv2, CRU TS4.06, ERA5, TRMM 3B43 V7, GPM, CFSR, and SM2RAIN-CCI), three evapotranspiration products (GLEAM, MOD16, and PLM), and two terrestrial water storage solutions (GRACE JPL MASCON, and Spherical Harmonic (SH) products). The Overall Unified Metric (OUM) approach is adopted to choose the best performing combination among the 42 combination scenarios. The OUM is an approach based on summing up the rankings given for the error and linear fit metrics&#8212;namely, R<sup>2</sup>, slope, y-intercept, RMSE, MAE, and PBIAS. Among the 42 combinations, the best rainfall, TWS, and ET combination performance products to estimate runoff are SM2RAIN-CCI, GLEAM, and GRACE SH, respectively. The statistical results for the six chosen metrics are R<sup>2</sup> = 0.7, slope = 1.6, y-intercept = - 0.5 cm, RMSE = 3 cm, MAE = 2.8 cm, and PBIAS = 36%. The 95% confidence bound of the combination scenarios was found to be able to bracket the runoff during the dry season, but the runoff was overestimated during the&#160;rainy&#160;season. The uncertainty analysis revealed that all the combinations were able to estimate the seasonal trend variation, but closing the water balance equation was not achieved. This deviation in closing the water budget equation might be attributed to the uncertainty associated with satellites, the limitation of land surface models to account for anthropogenic activities, and the coarse resolution of GRACE. Additionally, the signal processing uncertainties and the different algorithm assumptions of the remote sensing products may also have an influence. Further studies are needed to improve the reliability of the remote sensing product for the water budget closure, especially for applications on ungauged basins. Moreover, advancement in satellites will lead to accurate estimates in the near future.</p>
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