This study was conducted to investigate the spatiotemporal changes of land use/land cover (LULC) along the eastern coast of the United Arab Emirates (UAE) over a 20-year period using an integration of remote sensing and Geographic Information Systems techniques. The impact of land use change on flooding potential was also investigated through hydrologic model simulations. Landsat images of the years 1996, 2006 and 2016 were processed and analyzed. Change detection was carried out to assess changes in the built-up areas. Furthermore, the impact of urbanization on flooding was assessed using a hydrologic model in two major watersheds of Fujairah Emirate. It was observed that for the period 1996–2006 the vegetation and the built-up areas had increased at a rate of 11.23% and 24.56%, respectively. For the period 2006–2016, this expansion more than doubled in terms of the vegetation class (27.51%) and slightly increased for the built-up class (28.98%). The change detection analysis revealed that urbanization has mostly occurred along the coastal boundary. Hydrologic model simulations quantified the role of urbanization in increasing the flooding potential. The increase depends on watershed characteristics and the rate of change in urbanization and the magnitude of the rainfall event.

Satellite-based precipitation products are becoming available at very high temporal and spatial resolutions, which has accelerated their use in various hydro-meteorological and hydro-climatological applications. Because the quantitative accuracy of such products is affected by numerous factors related to atmospheric and terrain properties, validating them over different regions and environments is needed. This study investigated the performance of two high-resolution global satellite-based precipitation products: the climate prediction center MORPHing technique (CMORPH) and the latest version of the Integrated Multi-SatellitE Retrievals for the Global Precipitation Mission (GPM) algorithm (IMERG), V06, over the United Arab Emirates from 2010 through 2018. The estimates of the products and that of 71 in situ rain gauges distributed across the country were compared by employing several common quantitative, categorical, and graphical statistical measures at daily, event-duration, and annual temporal scales, and at the station and study area spatial scales. Both products perform quite well in rainfall detection (above 70%), but report rainfall not observed by the rain gauges at an alarming rate (more than 30%), especially for light rain (lower quartile). However, for moderate and intense (upper quartiles) rainfall rates, performance is much better. Because both products are highly correlated with rain gauge observations (mostly above 0.7), the satellite rainfall estimates can probably be significantly improved by removing the bias. Overall, the CMORPH and IMERG estimates demonstrate great potential for filling spatial gaps in rainfall observations, in addition to improving the temporal resolution. However, further improvement is required, regarding the overestimation and underestimation of small and large rainfall amounts, respectively.

In mid-April 2024, an extreme rainfall event struck Oman and the United Arab Emirates (UAE), causing unprecedented flooding, significant infrastructure damage, and loss of life. Characterized by intense and sustained rainfall over a few days, this event highlighted the region’s vulnerability to extreme weather phenomena. This study examines the rainfall estimated by two satellite rainfall products during this event, with a detailed analysis focusing on the watershed encompassing the city of Al Ain. A rain gauge in this watershed recorded a historic 24-hour rainfall of 254.8 mm, approximately 75% of the area’s previously estimated probable maximum precipitation (PMP). Other gauges in the watershed also recorded substantial rainfall amounts, breaking previous records, while satellite products significantly underestimated the actual rainfall. A physically-based distributed hydrologic model simulated the resulting flood, indicating a low runoff ratio of about 7.14% due to high infiltration rates. Despite this, significant flooding occurred in urbanized parts of the watershed. This discrepancy highlights the complexity of urban hydrology and the challenges of predicting flood extents in urban areas. The findings underscore the need for improved flood forecasting systems in the UAE, emphasizing enhanced satellite rainfall estimation accuracy and advanced modeling approaches for better urban flood management and mitigation. Integrating new technologies and methodologies in urban flood forecasting is crucial for enhancing resilience against future extreme weather events, ensuring the safety and preparedness of vulnerable regions like the UAE.

Properly quantifying the potential exposure of hyper-arid regions to climate extremes is fundamental to developing frameworks that can be used to manage these extremes. In the United Arab Emirates (UAE), rapid growth may exacerbate the impacts of climate extremes through urbanization (increased runoff), population and industrial development (more water demand). Water resources management approaches such as Managed Aquifer Recharge (MAR) application may help mitigate both extremes by storing more water from wet periods for use during droughts. In this study, we quantified the volumes of runoff from coastal watersheds discharging to the Gulf of Oman and the Arabian Gulf that could potentially be captured to replenish depleted aquifers along the coast and help reduce the adverse impacts of urban flooding. To this aim, we first downloaded and processed the Integrated Multi-satellite Retrievals for Global Precipitation Measurement Mission (IMERG) rainfall data for a recent wide-spread storm event. The rainfall product was then used as input to hydrologic models of coastal watersheds for estimating the resulting runoff. A multi-criteria decision analysis technique was used to identify areas most prone to runoff accumulation. Lastly, we quantified the volumes of runoff that could potentially be captured from frequency storms of different return periods and how rapid urbanization in the region may increase these runoff volumes creating more opportunities for the replenishment of depleted aquifers. Our results indicate that the average runoff from watersheds discharging to the ocean ranges between 0.11 km³ and 0.48 km³ for the 5-year and 100-year storms, respectively. We also found that these amounts will substantially increase due to rapid urbanization in the coastal regions of the UAE. In addition to water supply augmentation during droughts, potential benefits of application of MAR techniques in the UAE coastal regions may include flood control, mitigation against sea-level rise through subsidence control, reduction of aquifer salinity, rehabilitation of ecosystems, cleansing polluted runoff and preventing excessive runoff into the Gulf that can contribute to red tide events.

The catastrophic implication of harmful algal bloom (HAB) events in the Arabian Gulf is a strong indication that the study of the spatiotemporal distribution of chlorophyll-a and its relationship with other variables is critical. This study analyzes the relationship between chlorophyll-a (Chl-a) and sea surface temperature (SST) and their trends in the Arabian Gulf and the Gulf of Oman along the United Arab Emirates coast. Additionally, the relationship between bathymetry and Chl-a and SST was examined. The MODIS Aqua product with a resolution of 1 × 1 km² was employed for both chlorophyll-a and SST covering a timeframe from 2003 to 2019. The highest concentration of chlorophyll-a was seen in the Strait of Hormuz with an average of 2.8 mg m⁻³, which is 1.1 mg m⁻³ higher than the average for the entire study area. Three-quarters of the study area showed a significant correlation between the Chl-a and SST. The shallow (deep) areas showed a strong positive (negative) correlation between the Chl-a and SST. The results indicate the presence of trends for both variables across most of the study area. SST significantly increased in more than two-thirds of the study area in the summer with no significant trends detected in the winter.

Current water demands are adequately satisfied in the United Arab Emirates (UAE) with the available water resources. However, the changing climate and growing water demand pose a great challenge for water resources managers in the country. Hence, there is a great need for management strategies and policies to use the most accurate information regarding water availability. Understanding the frequency and the short- and long-term trends of the precipitation by employing high-resolution data in both the spatial and temporal domains can provide invaluable information. This study examines the long-term precipitation trends over the UAE using 17 years of data from three of the most highly cited satellite-based precipitation products and rain gauge data observed at 18 stations. The UAE received, on average, 42, 51, and 120 wet hours in a year in the 21st century as recorded by CMORPH, PERSIANN, and IMERG, respectively. The results show that the areal average annual precipitation of the UAE is significantly lower in the early 21st century than that of the late 20th century, even though it shows an increasing trend by all the products. The Mann–Kendall trend test showed positive trends in six rain gauge stations and negative trends in two stations out of 18 stations, all of which are located in the wetter eastern part of the UAE. Results indicate that satellite products have great potential for improving the spatial aspects of rainfall frequency analysis and can complement rain gauge data to develop rainfall intensity–duration–frequency curves in a very dry region, where the installation of dense rain gauge networks is not feasible.