Groundwater resource management using artificial intelligence and remote sensing technologies

Groundwater is a critical resource for drinking water, agriculture, and industry. With increasing anthropogenic activities and exponentially increasing population, groundwater in India is facing several challenges, related to quality as well as quantity, due to over-extraction, pollution, and climate change. Over-exploitation of groundwater may impact the availability and quality of groundwater which is not sustainable. Moreover, due to pollution in surface water, groundwater quality is also affected. In most of the cities of India, the quality of groundwater is below standard. Remote sensing and artificial intelligence can play a very vital role in monitoring the quantity as well as quality of groundwater. As, it is clear that presently no remote sensors can directly be used for groundwater observations, but by using surface features anomalies and gravity data obtained by various satellites, optimal groundwater management can be done using remote sensing.
Space4water is one of the best communities addressing water related issues and work towards sustainable solutions. For the last three years, I am following this community, and I find that the community consists of scientists, NGO, policy makers etc. This combination has the potential to resolve issues related to any challenges related to social issues. I am looking for few global research partners who work for groundwater management using space technology. I am equally looking for data driven resource persons who can collaborate with me on real field conditions of various countries, related to groundwater management.
What has been done so far is listed below:
• Worked on GRACE satellite data and used it in field condition to study groundwater anomalies of few cities of India.
• Developed spatio-temporal maps of Standardized Groundwater Index (SGI).
• Worked on water quality of water bodies.
• Used various satellite data to map water spread areas of various water bodies.
• Worked on machine learning models to study in situ remediation of contaminated groundwater.