Water Resource Modeling and Computational Technologies - Chapter 2: Demystifying artificial intelligence amidst sustainable agricultural water management

Elsevier, Water Resource Modeling and Computational Technologies, 2022, pp 17-35
Srivastava A., Shubham J., Maity R., Desai V.

The 21st-century agricultural industry is witnessing negative impacts of climate change, land and water scarcity, and more recently, a global COVID-19 pandemic. Consequently, the socioeconomic sustainability of current and future food-supply systems appears to be threatened. To combat issues due to water shortage across agricultural applications, artificial intelligence (AI)-based solutions are appearing as viable alternatives. This review demystifies AI in pre, during, and post-agronomic stages owing to increasing agricultural efficiency amidst decreasing water availability. The potentials of AI are primarily reviewed in a sustainable agricultural water management context, given emerging agricultural applications of artificial neural networks, machine-learning, deep-learning, remote-sensing, digital-image processing, and robotics. From the results of the systematic review, advanced opportunities have been identified, such as real-time assistance to farmers amidst natural disasters and predictive analysis of agromarket-price forecasting. Though challenges exist while transferring technology from experimental to real environments, the review concludes with the promising prospect of AI-powered applications.