The lack of sufficient precipitation data has been a common problem for water resource planning in many arid and semi-arid regions with sparse and limited weather monitoring networks. Satellite-based precipitation products are often used in these regions to improve data availability. This research presents the first validation study in Syria for Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) estimates using in-situ precipitation data. The validation was performed using accuracy and categorical statistics in the semi-arid Barada Basin, Syria, between 2000 and 2020. Multiple temporal scales (daily, pentad, monthly, seasonally, and annual) were utilized to investigate the accuracy of CHIRPS estimates. The CHIRPS results indicated advantages and disadvantages. The main promising result was achieved at the seasonal scale. Implementing CHIRPS for seasonal drought was proven to be suitable for the Barada Basin. Low bias (PB_winter = 2.1%, PB_wet season = 12.7%), high correlation (r_{wet season} = 0.79), and small error (ME = 4.25 mm/winter) support the implementation of CHIRPS in winter and wet seasons for seasonal drought monitoring. However, it was observed that CHIRPS exhibited poor performance (inland pentads) in reproducing precipitation amounts at finer temporal scales (pentad and daily). Underestimation of precipitation event amounts was evident in all accuracy statistics results, and the magnitude of error was higher with more intense events. CHIRPS results better corresponded in wet months than dry months. Additionally, the results showed that CHIRPS had poor detection skill in drylands; on average, only 20% of all in-situ precipitation events were correctly detected by CHIRPS with no effect of topography found on detection skill performance. This research could be valuable for decision-makers in dryland regions (as well as the Barada Basin) for water resource planning and drought early warning systems using CHIRPS.

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.

In Ras Al Khaimah, UAE, groundwater from the alluvial aquifer in Wadi Bih was the only source of freshwater for various uses prior to the construction of a seawater desalination plant in 1998. This study was conducted to evaluate the effect of the Wadi Bih dam on groundwater resources and to increase knowledge of the hydrodynamics of the aquifer. A local-scale numerical groundwater flow model was developed and used to investigate the impacts of different groundwater management options on groundwater resources. The calibrated and validated model was defined as the base case, and subsequently, simulations were performed to analyze different management scenarios. The simulations indicated that maximum recharge occurred during years of high rainfall (1995–1998). Minimum recharge occurred in 2000, 2002, and 2004. The major contribution to the water balance was from subsurface inflows from the upper wadi zone and the two tributaries. Overall, the annual water balance was negative in most years, with an average net decline of 0.6 MCM per year, indicating a slow but continuous depletion of groundwater resources. At the end of the simulation, the total groundwater recharge due to rainfall and water storage in the ponding area was 9.81 MCM.

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 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 2003–2014 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—namely, R2, 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 R2 = 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 rainy 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.