Understanding the impact of climate change and land use change on the groundwater resources in the future using deep learning models with focus on data scarce regions
Implementing Organization
National Geophysical Research Institute (NGRI)
Principal Investigator
Dr. Maheswaran Rathinasamy
Indian Institute of Technology (IIT)
Principal Investigator
Dr. Surinaidu
National Geophysical Research Institute (NGRI)
Project Overview
Groundwater is a crucial resource, contributing to one-third of the world's available water. However, climate change and human activities like irrigation and excessive pumping are putting pressure on groundwater resources, increasing the risk of droughts. Studies have shown that groundwater levels in Germany are decreasing due to excessive pumping and climate change. The future of groundwater resources development is crucial for sustainable management plans. Climate projections show opposing trends in water availability, with regions dependent on shallow aquifers likely to be severely affected. Machine learning and deep learning-based approaches can help understand the impact of climate change on groundwater availability. However, these models are highly data-intensive and computationally heavy, making them difficult to analyze at a regional level. This study focuses on two aquifers in Canada and India, which are vulnerable to climate change and land use changes. The Ganga River Basin in India, with its diverse hydroclimatology, land use, and aquifer characteristics, is chosen as a test bed for the proposed methodology.