Forecasting and optimizing furrow irrigation management decision variables

Furrow irrigation can be better managed if the management decision variable s (irrigation time and amount; inflow rate and cutoff) can be determined ah ead of time. In this study, these decision variables were forecast and opti mized using 1 day ahead grass reference crop evapotranspiration (ET0) forec asts, based on the ARMA(1,1) time-series model, with a seasonal furrow irri gation model for both homogeneous and heterogeneous infiltration conditions . Heterogeneity in infiltration characteristics was restricted to variation s along the furrow length as opposed to variations between furrows. The res ults obtained were: compared with their counterparts using the observed ET0 , for the same period during the 1992 cropping season. Seasonal performance (application efficiency, inflow, runoff and deep percolation volumes) and economic return to water (yield benefits minus seasonal water related and l abor costs) were affected by infiltration conditions, while irrigation requ irement and bean yield were unchanged. In a given infiltration case, season al performance, irrigation schedules, bean yield and economic return to wat er were. comparable (lower than 4% difference) for the two ET0 conditions. For each ET0 condition, individual irrigation events resulted in different irrigation designs (inflow rate and cutoff time) except inflow rates with h eterogeneous infiltration. Differences in inflow volume were less than 2% a nd 5%, respectively, for homogeneous infiltration and heterogeneous infiltr ation. For the conditions studied, furrow irrigation management decision va riables can be forecast and optimized to better manage the irrigation syste m, because irrigation performance was the same for both (forecast and obser ved) ET0 cases.