A Review of the Applications and Benefits of Machine Learning Approaches in Enhancing Water Use Efficiency under the Impact of Climate Change

Articles in Press

Document Type : Review

Authors

1 Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural

2 Department of reclamation of arid and mountainous regions Engineering, Faculty of Natural Resources, University of Tehran, Karaj, Iran.

3 Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj.

10.22059/ijswr.2025.403943.670022

Abstract

Climate change, by inducing severe fluctuations in precipitation patterns, temperature, and evapotranspiration, has increasingly challenged water resource management, particularly in arid and semi-arid regions. Under these critical conditions, enhancing water use efficiency (WUE) in agriculture is recognized as one of the most effective strategies for adapting to water scarcity and ensuring food security. However, assessing and optimizing WUE exceeds the capabilities of traditional models due to the nonlinear and dynamic relationships among climatic, soil, and crop variables. Recent advances in data science and artificial intelligence—particularly the development of machine learning (ML) and deep learning (DL) models—have enabled the analysis of vast volumes of climatic, hydrological, and agricultural data. This comprehensive review explores the role of data-driven approaches in optimizing water use efficiency under climatic uncertainty. By reviewing existing studies, we analyze the application of various models—including Random Forest, Support Vector Machine, and Neural Networks—in key domains such as water demand prediction, accurate evapotranspiration estimation, and irrigation system performance assessment. The literature reveals that the use of hybrid models integrating multi-source data (remote sensing, IoT sensors, and ground observations) significantly enhances decision-making accuracy in water management. This approach not only addresses the challenges posed by climate instability but also paves the way for the development of intelligent and adaptive irrigation systems essential for strengthening water resource resilience.

Keywords

Main Subjects

Iranian Journal of Soil and Water Research

Articles in Press, Accepted Manuscript
Available Online from 09 December 2025

Files

Share

How to cite

Statistics