Revisiting border irrigation management: benefits of new in-field sensor-based control compared to conventional cutoff times

Surface irrigation is often described as low performing insofar as its practice is labour intensive and involves the use of large water flows that are difficult to quantify and manage. However, this method remains predominant worldwide, and modernisation towards localised irrigation systems is not always feasible or advisable. To support border irrigation management, we previously developed a low-cost sensor for surface irrigation management, which remotely informs the farmer of water arrival downstream of his or her field and therefore of the moment to stop irrigation. The objectives of this study were: i) to determine the optimal position of this sensor lengthwise in the field throughout the season, and ii) to compare the influence of management scenarios (sensor-based or time-based cutoff) on irrigation performance. To this end, an integrated agro-hydraulic model was developed to simulate surface water flow dynamics throughout the season including variations in infiltration and roughness. The model was fed using monitoring data from the border irrigation of a hay field during a whole season. The results showed that the optimal sensor position can change by 10% over the course of the season, depending on inflow rates, initial soil moisture and Manning’s roughness. Sensor-based irrigation control was found to be more efficient than actual practices, and more effective than an optimised cutoff time in limiting performance gaps induced by variability or uncertainty in the initial conditions. The methods and findings should serve as a basis for larger-scale studies integrating the adoption of sensors and real-time data for surface irrigation management.