Background: Water is a key input into the rice industry. Water scarcity and increased competition across multiple irrigation industries is raising the interest of the rice industry in irrigation techniques that minimise water application, such as the alternate wetting and drying (AWD) and delayed permanent water (DPW). Moving to a ’Dry Rice’ system, which aims to minimise water application and use, will be critical in ensuring the future of the rice industry in a water-constrained environment. Moving from a traditionally ponded anaerobic watering strategy to a partly ponded or ultimately aerobic rice growing system will need significant advancements in water management for the rice system. Soil moisture, water control, crop stress monitoring and timely irrigation management will be critical to minimally ponded or non-ponded rice cropping systems. Sensing systems capable of sensing soil, water and crop stress, integrated with weather forecasts and automated Internet of Things (IoT) irrigation control structures have the potential to be used in rice-growing systems to improve water productivity and reduce labour cost. In ponded rice, such sensing systems would allow dynamically managed water height through the season to protect the crop from low or high temperatures at sensitive-growth stages to optimise yield and reduce water use.
Objective: The objective of this study would be to investigate and understand the key soil, water and crop sensing, and forecasting parameters in rice cropping systems necessary for the proper implementation of an online-automated irrigation system. This is of paramount importance in order to optimize water management and guarantee a good crop performance when such online-automated systems are implemented. The suitability of proximal sensors (soil and plant-based) as well as remote sensing data for soil water deficit and plant water stress monitoring will be assessed.