Deep Learning Techniques for Automation and Industrial Applications

9Making Invisible Bluewater Visible Using Machine and Deep Learning Techniques–A Review

Dineshkumar Singh^1* and Vishnu Sharma²

¹Department of Computer Science and Engineering FCE, Poornima University, Jaipur, India

²Department of Computer Science and Application FCE, Poornima University, Jaipur, India

Abstract

Two billion people across the globe are still far from a viable source of potable water and rely on rain and groundwater for daily living and farming. The supply of groundwater is limited. In India itself, groundwater abstraction beyond the safe limit is causing rapid groundwater table depletion at a rate of 1–2 m/year in many districts. Uncontained and unplanned usage may affect food production by 20%. Due to the significant impact of this imperceptible resource on various aspects of life—the economy, the environment, and society—there is a pressing need to enhance the scientific comprehension, estimation, and administration of groundwater management. A scientific framework for the demarcation of its potential storage and recharge zonal maps, i.e., groundwater potential storage zone (GWPSZ) and groundwater potential recharge zone (GWRZ), can be instrumental in this regard to help urban and rural water committees objectively manage the resources at the regional level.

This article examines the endeavors of multiple researchers who have employed statistical modeling and GIS-remote sensing alongside the analytical hierarchy process, or multi-influencing factors techniques ...