Applying Remote Sensing, Geospatial Information Systems, and Machine Learning Algorithms to Manage Groundwater Resources

Dear Colleagues,

Groundwater resources have been extremely over-used during the past several decades, which has resulted in water table drop, land subsidence, shortage of water resources, and subsequently various socio-economic challenges. Considering the high dependency of governments and stakeholders on groundwater resources, it is highly recommended to use remote sensing (RS) data integrated with geospatial information systems (GIS)-based novel machine learning algorithms and programming languages to provide useful information and tools for water sector managers. The purpose of this Special Issue is to publish papers including original research and review papers on surface and groundwater interactions, groundwater potential, groundwater quality, artificial recharge, and land subsidence by implementing remote-sensing-derived data and advanced machine learning algorithms using spatial tools.

Topics of interest in this Special Issue include but are not limited to:

• Groundwater potential assessment using RS data and machine learning algorithms;
• Artificial recharge site selection using new approaches;
• Spatial modelling of groundwater quality;
• Spatial modelling of land subsidence;
• Groundwater sustainable management using GIS and RS.

Dr. Seyed Amir Naghibi
Prof. Biswajeet Pradhan
Guest Editors

Manuscript Submission Information

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