Artificial intelligence and satellite imagery in the service of sustainable management of groundwater resources
Funding agency: SRA-MECW
The Middle East faces various environmental challenges, including water scarcity. Climate change makes surface waters less reliable and consequently adds up the pressure on groundwater resources, which are already the main supply for agriculture, industry, and drinking sectors. Overexploitation of groundwater leads to the depletion of groundwater resources, possible permanent loss of aquifer storage, land subsidence, and many socio-economic challenges.
1- Using artificial intelligence and remote sensing to determine the long-term variations of ground deformation and extract the meaningful relationships between pumping-induced land subsidence and its driving factors.
2- Inverse modeling of groundwater storage changes using environmental factors, remote sensing data, and artificial intelligence.
This project includes CMES researcher Dr. Hossein Hashemi who has experience working on remote sensing applications in managing groundwater resources.
The project's expected outcomes will help the stakeholders, and water resources managers clearly understand and evaluate their water-related and land use planning strategies.
Groundwater data in the Middle East are not monitored very well, and therefore, there is a lack of data on these essential resources.
The second output of this project will be designing a groundwater monitoring system that can be used to inversely estimate groundwater storage changes over time with the aid of satellite imagery and artificial intelligence. This can benefit the Middle Eastern countries to manage groundwater resources more efficiently and sustainably.
Apart from the technical parts, this project will also provide some interdisciplinary solutions considering the economic, social, and water-related dimensions to improve groundwater resources.