A Simple-Structured Framework for Decision Support System in Irrigation Water Management: Tool Description and Preliminary Testing

Abstract In the context of climate change, where precipitation is decreasing and poorly distributed over time, and the cost of irrigation water is increasing, an efficient and sensible water supply system is critical to reduce water waste without compromising crop productivity. To achieve this, a system that assists farmers in irrigation scheduling and management must be easy to understand, apply, and interpret, and be highly adaptable to the practices actually used by farmers in the field. This paper describes an irrigation scheduling decision support system that uses limited algorithms and computational routines to formalize a few parameters related to crop development, productivity, and water use for irrigation scheduling. The system predicts when and how much to irrigate based on three methods for determining crop water requirements and their effects on crop development and yield performance. The system was calibrated and tested on tomato plants grown in a Mediterranean environment. In this first benchmark, it has shown high robustness and reliability in replicating the studied cropping system and optimizing the use of irrigation resources.