AI Reveals High Mountain Asia Losing 24.2 Billion Tonnes of Groundwater Annually
GS3Economy · S&T · Environment · Security· IT, AI, semiconductors & computing· Prelims + Mains·
Why in news
Researchers used an AI-powered model to reveal a massive annual groundwater loss of 24.2 billion tonnes in High Mountain Asia due to climate change and human activity.
Background
Prof. Shudong Wang and the Aerospace Information Research Institute of the Chinese Academy of Science (AIRCAS) conducted the study. The research found that two-thirds of High Mountain Asia (HMA) is experiencing decreasing groundwater storage, specifically impacting the Ganges-Brahmaputra, Indus, and Amu Darya basins.
Facts for Prelims
- S&TAI-powered models are being utilized to monitor and predict groundwater depletion and climate impacts.
- FactHigh Mountain Asia loses approximately 24.2 billion tonnes of groundwater annually.
- PlaceThe Ganges-Brahmaputra, Indus, and Amu Darya basins are identified as critical areas of groundwater depletion.
For Mains
Q. Discuss how AI and machine learning can enhance climate change adaptation and resource management in transboundary water-stressed regions like High Mountain Asia.
Dimensions to cover in your answer
- Technological intervention in resource monitoring
- Transboundary water security
- Impact on downstream agriculture
- Climate-human nexus
Keywords: Groundwater depletion · AI-driven modeling · Climate change · Transboundary water · Resource sustainability
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