Optimization, Control, and Adoption of Irrigation Decision Support Tools

Dear Colleagues,

Over one billion people are facing severe water scarcity at least one month of the year, and agricultural irrigation accounts for the vast majority (more than 70%) of our freshwater use. Irrigation decision support (IDS) tools have the potential to reduce water consumption and improve crop productivity by optimizing the volume of water delivered and the timing of irrigation events, based on models and measurements of plant physiology, evapotranspiration, soil hydrology, and groundwater recharge. Employing IDS tools can make it easier to integrate with renewable power sources, allowing systems to optimize irrigation timing in a way that maximizes the utilization of the variable power source, reducing battery requirements and minimizing costs. IDS tools can also integrate information from crop and soil sensors, remote sensing equipment, Internet of Things (IoT)-enabled devices, regional databases, and other sources, to produce crop-specific and location-specific water demand predictions. IDS tools have demonstrated significant water savings in theoretical and pilot studies, indicating their potential to address water scarcity. However, initial adoption among farmers has been limited and slow. To understand the current state, unrealized potential, and challenges of this field, this Special Issue invites recent findings related to the optimization, control, and adoption of IDS tools. Relevant literature includes (but is not limited to):

• The creation, validation, and exploration of theory and optimization models to design low-cost and environmentally sustainable irrigation systems, including their integration with renewable power sources;
• The creation, validation, and exploration of theory and optimization models to support operational decisions that minimize water use and maximize crop productivity based on predictive models, inputs from sensors, and other sources;
• The design and validation of the control theory and hardware necessary to implement an IDS strategy in the field; and
• Current implementations and challenges regarding the adoption and use of IDS tools and IDS-enabled systems by farmers in the field.

Dr. Susan Amrose
Guest Editor

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• irrigation decision support
• optimization
• renewable power
• solar
• agricultural sensors
• remote sensing
• agricultural engineering
• sensor applications
• adoption
• irrigation tools and technologies
• water use efficiency
• Internet of Things (IoT)
• controls
• controllers