Water resource management is becoming essential due to many anthropogenic and climatic factors resulting in dwindling water resources. Traditionally, geographic information systems (GIS) and remote sensing (RS) have long been instrumental in water resource assessment and management as the satellites or airborne units are periodically utilized to collect data from large areal extent. However, these platforms have limited computational capability and localized storage systems. Recently, these limitations have been overcome by the application of Google Earth Engine (GEE) that offers a faster and more reliable cloud-based GIS and remote sensing platform that leverages its parallel processing capabilities. Thereby, in recent years, GEE has witnessed rapid and accelerated adoption and usage in a wide variety of domains, including water resource monitoring, assessment and management. However, no systematic studies have been made to review the GEE application in water resource management. This review article is a maiden attempt towards developing an understanding of the functioning of GEE and its application in water resource assessment, covering both of its aspects viz (a) water quantity and (b) water quality. The review further attempts to illustrate its capabilities in real-world utility, through a case study conducted to analyze water quality and quantity of lake mead, a reservoir of Hoover Dam, Nevada (USA), at a monthly scale for a 3-year period spanning from 2021 to 2023. The results of this case study showcase the applicability of GEE to the water resource quantity and quality monitoring, assessment and management problems. The review further discusses the existing challenges with the application of GEE in water resource assessment and the scope for further improvement. In conclusion, after tackling the existing challenges with GEE, the application of GEE in water resources has huge potential for management planning of our water resources by addressing the forthcoming challenges.
Keywords: Geographic information systems; Groundwater; Remote sensing; Surface water; Water quality; Water quantity.
© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.