Sub-optimal model-based deficit irrigation scheduling with realistic weather forecasts

This paper analyses the performance of sub-optimal irrigation schedules obtained daily by solving a multi-objective optimization problem with updated weather measurements and forecasts. The approach was tested using five crops at four European locations with contrasting weather conditions. Four- and 6-day Global Forecast System (GFS) forecasts were used at all locations, and comparison with a down-scaled locally tuned model was conducted at one location. Accurate GFS temperature forecasts were observed at all four locations, but the accuracy of the potential evapotranspiration calculated from the GFS forecasts was not as consistent. Precipitations forecasts were very poor at all locations. In Greece, the down-scaled locally tuned forecasts were only marginally better than the GFS ones. In most cases, recomputing the sub-optimal irrigation schedule daily greatly reduced the impact of the imperfect weather forecasts on the final results. Using 4- or 6-day actual forecasts did not yield results appreciably better than those obtained using only historical averages as surrogate forecasts. The main consequence of the imperfect forecasts was that the final yield differed from the target one, but the (yield, irrigation) combination remained close to optimal, unless the target yield was set too high and water availability was not the main factor limiting crop development.