In a world with growing population and dwindling water resources, precision irrigation holds a vital place in improving agricultural water-use efficiency.

In a world with growing population and dwindling water resources, precision irrigation holds a vital place in improving agricultural water-use efficiency. Irrigation scheduling is usually not precise, as it is based on recouping past evapo-transpiration, assessed by soil water measurements and atmospheric conditions. However, important plant physiologic changes associated with transpiration respond to internal water demands and could be accounted for in an optimal irrigation plan. 

Researchers Dr. Yair Mau from the Department of Soil and Water Sciences at the Hebrew University and Dr. Gil Bohrer from Ohio State University are jointly studying the internal water status in trees in order to optimize irrigation strategies. The researchers’ goal is to devise optimal irrigation strategies based on direct and modelled assessment of plant water stress. They will characterize water stress by measuring stem-water content and sap flow, and use this information to calibrate an advanced, tree-level, plant-hydrodynamic model. This model will serve as the backbone of an irrigation scheme that minimizes water use, while maintaining high agricultural yields by avoiding tree water stress. To accomplish this goal, researchers will install an observation network in two orchards (avocado and mandarin orange) in Israel. They will measure environmental conditions (soil water content, canopy air temperature and relative humidity), and plant hydraulic variables through sap-flow and stem-storage sensors. 

With the measured data, researchers hope to optimize the model parameters for each tree species, aiming at maximizing the prediction accuracy for tree-water content, sap flow, and transpiration. They will also utilize the field observations to characterize early signs of water stress based on stem-water storage and sap-flow dynamics. The optimized model and derived water stress thresholds will then be used as the core of an adaptive decision-support system for irrigation scheduling. Water-use efficiency will be optimized (more yield, less water) by short-term (1-3 days) forecast simulations with the parameterized model, taking into account real-time tree-water status, and constrained by weather forecasts. Researchers will implement this irrigation scheme in a treatment plot and evaluate its performance against control plots with classic and dendrometer-based irrigation schemes. 

The researchers hope this research will advance the understanding of how the internal water status of irrigated mango and navel orange trees influences transpiration regulation. The identification of critical thresholds in the plant hydraulic status associated with drought stress is invaluable in the formulation of optimal irrigation strategies. Finally, because this optimization scheme is based on a plant-hydrodynamic model, it can leverage the understanding of plant water management, and translate it to novel model-predictive control tools for more efficient precision agriculture.  


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