Groundwater Withdrawal Prediction Using Integrated Multitemporal Remote Sensing Data Sets and Machine Learning
Sayantan Majumdar, Ryan Smith, James J. Butler, V. Lakshmi
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
Topics & Concepts
GroundwaterAquiferScale (ratio)Remote sensingKey (lock)Environmental scienceHydrology (agriculture)Computer scienceGeologyCartographyGeotechnical engineeringGeographyComputer securityHydrology and Watershed Management StudiesGroundwater and Watershed AnalysisFlood Risk Assessment and Management