Objective: It is possible to determine the optimal performance of systems using the simulation-optimization models. The surface irrigation in the form of low-pressure irrigation, is one of the modern irrigation methods, and is supported by the government by receiving free credits.
Methods: In this research, a new calibration- simulation- optimization model was developed for furrow irrigation. In this model, the SCS method was used to calibrate parameters of the SCS infiltration equation from infiltration test data. The SCS method was used for hydraulic simulation of surface irrigation (furrow design). The PSO meta-heuristic algorithm solver (particleswarm) was used for optimization. Finally, in this model, the simulation is done after the simulation-optimization of furrow irrigation. To optimize the hydraulic objective function, including the minimization of the linear combination of three performance indicators, the decision variables of flow rate, length and slope were used.
Results: Comparing the results of the SCS infiltration equation with the calibrated parameters with observed infiltration values, with R2=0.99, CRM=-0.002 and NRMSE=0.7%, indicated the proper performance of the calibration. The simulation results in three experimental fields showed over-irrigation with runoff losses, which led to an inappropriate objective function. Although the design reduced the losses by reducing the flow rate and closing the end. After that, optimization with options such as flow rate reduction, length increase and slope reduction, caused reduction (improvement) of the objective function from 1.22 to 0.24 for field 1, from 0.8 to 0.27 for field 2, and from 0.22 to 0.11 for field 3.