Groundwater Withdrawal Prediction Using Integrated Multitemporal Remote Sensing Data Sets and Machine Learning

Abstract

Key Points Groundwater withdrawals are not actively monitored in most places of the world at a scale necessary to implement sustainable solutions Various multitemporal remote sensing data are integrated into a machine learning framework to effectively predict groundwater withdrawals The results over the High Plains Aquifer, Kansas, USA, show that this approach is applicable to similar regions having sparse in situ data