Field Crop Irrigation - Multi-Objective Optimization and Sensitivity to Weather Forecast Accuracy

Theodor Bughici, Eran Tas, Erick Fredj, Naftali Lazarovitch

Research output: Contribution to conferencePoster


Accurate irrigation and fergaon of field crops are crucial for maximizing crop yield while avoiding overuse of water and fertilizer. Weather forecasts can predict potential evapotranspiration (ET0)but are still far from perfect. We used a case study of sprinkler irrigated spring potatoes in Coastal Israel as a test case in order to define a minimal accuracy level of ET0 predictions for irrigation planning. The working stages of simulation-optimization-sensitivity analysis are described in the workflow. By modeling crop irrigation based on varying forecasted ET0 relative bias ranges as wellas crop and soil parameters we were able to rank the parameters by contribuon to crop-model output variance. Our main findings are (Fig. 4):
ETprediction accuracy dominates the crop model parameters when ETrelative bias (δET0) range <5%.
The soiln parameter dominates model output when δET0 range <5% for all objective functions but transpiration (RMSETa).
The max. root depth is dominating transpiration output (RMSETa) when δET0 range <5%.
This procedure of optimization and sensitivity analysis can be extended to a wide range of case studies and help define what is an adequate weather forecast accuracy suitable to base crop irrigation upon.
Original languageEnglish
StatePublished - 26 Mar 2019


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