Machine-learning-based regional-scale groundwater level prediction using GRACE
Pragnaditya Malakar(Indian Institute of Technology Kharagpur), Anwar Zahid(Bangladesh Institute of Development Studies), R.K. Ray(Central Ground Water Board), Sudeshna Sarkar(Indian Institute of Technology Kharagpur), Soumendra N. Bhanja(Athabasca University), Abhijit Mukherjee(Indian Institute of Technology Kharagpur)
Cited by 53
Related Papers
Global water resources and the role of groundwater in a resilient water future
|Nature Reviews Earth & Environment|2023|1.1k
Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges
|Water Resources Research|2019|627
Groundwater quality and depletion in the Indo-Gangetic Basin mapped from in situ observations
|Nature Geoscience|2016|514
Deeper groundwater chemistry and geochemical modeling of the arsenic affected western Bengal basin, West Bengal, India
|Applied Geochemistry|2008|300
Arsenic and other geogenic contaminants in global groundwater
|Nature Reviews Earth & Environment|2024|281