An analysis framework to evaluate irrigation decisions using short-term ensemble weather forecasts

Abstract Irrigation water is an expensive and limited resource optimal scheduling can boost efficiency. Scheduling decisions often need to be made several days prior irrigation event, so a key aspect of the accurate prediction crop use soil status ahead time. This relies on inputs including initial status, conditions weather. Since each input subject uncertainty, it important understand how these uncertainties impact subsequent decisions. study aims develop uncertainty-based analysis framework for evaluating under with focus uncertainty arising from short-term rainfall forecasts. To achieve this, biophysical process-based model, APSIM (The Agricultural Production Systems sIMulator), was used simulate root-zone content field in south-eastern Australia. Through simulation, we evaluated different using ensemble modelling produced simulations content, as well runoff drainage. enabled quantification risks over- under-irrigation. These estimates were interpreted inform timing next event minimize both stressing and/or wasting uncertain future With extension include other sources (e.g., evapotranspiration forecasts, coefficient), plan build comprehensive support on-farm decision-making.