A research team led by Prof. Shudong Wang of the Chinese Academy of Sciences has identified significant groundwater depletion across High Mountain Asia, a region critical to water security for hundreds of millions of people across more than a dozen countries. Using satellite observations and artificial intelligence, researchers reconstructed approximately 20 years of groundwater storage changes and determined that roughly two-thirds of the region experienced declining reserves between 2003 and 2020.
The largest groundwater losses occurred in heavily populated downstream basins where agricultural irrigation demands are substantial, including the Ganges-Brahmaputra, Indus, and Amu Darya basins. Some elevated inland areas experienced localized increases in groundwater storage during this period. The analysis, published in Environmental Research Letters, identified two primary factors driving the depletion: climate-related changes accounting for nearly half of observed variation, with cryosphere changes playing a particularly important role, and human groundwater withdrawals for irrigation, which became increasingly significant after 2010.
Projections indicate that groundwater losses will continue under current water use patterns. Researchers note that increased glacier melt could temporarily reduce depletion rates around the 2060s, but this effect cannot persist indefinitely and is expected to be followed by accelerated losses. Without changes to existing water use practices, groundwater depletion in agricultural regions relying on these reserves could intensify substantially.
To overcome challenges posed by the region’s mountainous terrain and limited ground-based data, the research team developed an artificial intelligence framework combining multiple satellite sensors, Earth system modeling, and explainable machine learning. The methodology incorporates a lightweight Transformer architecture designed to account for hydrological memory and delayed effects. Researchers validated their findings by comparing results with thousands of groundwater well measurements and independent datasets. The study was funded by China’s National Key R&D Program and the National Natural Science Foundation of China.
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