WATER USE EFFICIENCY IN IRRIGATED AGRICULTURE: A SYSTEMATIC LITERATURE REVIEW

Abstract

Scarcity of water and increasing agricultural demand has triggered the necessity to have proper irrigation management solutions. It is a systematic literature review that condenses and summarizes the recent trends (2015-2024) in the field of water use efficiency (WUE) within irrigated agricultural systems in which a particular focus will be on the use of Internet of Things (IoT) technologies and machine learning (ML) models to manage smart irrigation management. The 229 peer-reviewed articles that were found and studied during the study were identified and investigated through a PRISMA-based approach to searching large scientific databases that included Scopus, Web of Science, and IEEE Xplore. The review evaluates the capability of decision support systems (DSS) such as those of DSSAT, APSIM, AquaCrop, CropWat, GesCoN, and VegSyst to optimize irrigation schedule particularly with the combination of real time sensor networks, remote sensing data and predictive analytics. The findings indicate that through the irrigation systems based on the Internet of Things and the assistance of the ML algorithms, such as Random Forest, Artificial Neural Networks, Support Vector Machines, Deep Learning, water savings (37 to 70 percent) can be achieved and, at the same time, crop yields may be improved by 30 percent. It is also in the synthesis that the superiority of real-time adaptive irrigation systems over the conventional static scheduling systems come out in the sense that the systems are sensitive to the changes in the environment and water need of crops. Technological innovations have not sorted the barriers to their adoption like high start-up cost, connectivity, data consolidation, and scaling, particularly in regions with limited resources, such as agriculture. In this review the author critiques extensively on the state of the art in intelligent irrigation systems and provides prospects of future research in the field of scalable, cost-effective as well as climate-resilient water management that supports water management in the world.