Dr. Khaled Al Ghafli from UAEU Explores Groundwater Storage Dynamics in Abu Dhabi Using AI Technique

Dr. Khaled Al Ghafli, Assistant Professor at the College of Engineering, UAE University, has developed an innovative study aimed at understanding the dynamics of groundwater storage across the Abu Dhabi Emirate and identifying the key factors influencing groundwater level fluctuations. His research integrates hydrological data with satellite-based observations and uses machine learning techniques to develop a model that predicts changes in groundwater storage. This is the first study of its kind in the region to apply artificial intelligence techniques to predict temporal variations in groundwater storage.

A significant aspect of this research is exploring the impact of climate variability, particularly the El Niño Southern Oscillation (ENSO), on groundwater resources. ENSO affects rainfall patterns and characteristics, which in turn influence the rate of groundwater recharge. By incorporating these variables into the model, Dr. Al Ghafli provides valuable insights into how global climate phenomena affect local hydrological systems. This represents a crucial step towards improving water resource management in arid regions like the UAE.

Dr. Khaled Al Ghafli stated, "This research aims to demonstrate the potential of satellite data for cost-effective and scalable monitoring of groundwater storage changes. While traditional groundwater monitoring systems rely on wells—geographically limited, expensive, and requiring continuous maintenance—satellite missions such as GRACE (Gravity Recovery and Climate Experiment) and its successor GRACE-FO enable large-scale, continuous, and remote observation of groundwater storage changes."

By leveraging satellite data, Dr. Al Ghafli has developed an innovative groundwater monitoring algorithm that supports sustainable water management strategies. This approach is particularly critical in regions facing water scarcity, especially with the increasing frequency of extreme weather events due to climate change. Accurate groundwater monitoring systems can help in drought management and climate resilience planning.

Dr. Al Ghafli added, "We collaborated with several institutions during this study, where groundwater well records provided by the Environment Agency - Abu Dhabi (EAD) played a crucial role in validating satellite data and testing the model. Additionally, collaboration with researchers from the University of Glasgow in Scotland and Wageningen University in the Netherlands has further strengthened the research outcomes."

He further stated, "As the accuracy of satellite data continues to improve with new Earth observation missions, future research will focus on updating and retraining the predictive algorithms using high-resolution satellite data. This will improve the spatial accuracy of groundwater storage estimates, making the models more effective for regional and local water resource management. Expanding the application of machine learning models to other regions in the UAE and beyond could provide broader insights into groundwater dynamics under different climatic conditions. We are also working on downscaling the model to represent groundwater storage changes with higher precision."