Estimating groundwater dynamics from artificial intelligence and InSAR

Groundwater represents about a third of global water withdrawals, and approximately half of global irrigation water. In many arid and semi-arid regions, groundwater is rapidly being depleted, which is affecting agricultural productivity over the long term. The over-exploitation of groundwater due to the current drought episode in South-Western U.S. has already led farmers to fallow hundreds of thousands of acres of farmland.Informed assessments and policies related to groundwater supplies can only be made on the basis of large-scale, precise estimates of depletion and recharge. However, current technologies have poor resolution in time and/or in space. We propose to leverage very recent advances in artificial intelligence applied to Interferometric Synthetic Aperture Radar (InSAR) in order to study groundwater depletion and recharge. Variations in groundwater levels induce deformation at the surface of the Earth, which can be captured by satellite-based InSAR measurements. Our technology allows to lower the detection threshold of surface deformation in InSAR time series by about an order of magnitude compared to the state-of-the-art; the associated resolution in space is a few km with a time resolution of roughly a week, thereby potentially offering a new tool for groundwater management decisions.