Analysis and optimization of conventional furrow irrigation systems using the WinSRFR simulation model

Surface irrigation systems continue to be the most popular irrigation systems worldwide, owing to their ability to save energy and ease of operation. They do, however, perform poorly as a result of the overall design and ineffective management. Therefore, the study aims to optimize the performance of conventional furrow irrigation systems in water constrained areas. Conventional furrow irrigation was used to collect field data and then to evaluate performance using the WinSRFR simulation model. The sensitivity analysis of WinSRFR revealed that the most sensitive parameters were inflow rate, cut-off time, and furrow spacing, respectively. The WinSRFR simulation model predicted that the conventional furrow design performed better in terms of application efficiency 84%, and achieved flow rates near the minimum allowable which is 0.0025m³/s in our case due to extreme water shortage. Therefore, given minimal runoff and percolation losses, with total maximum losses of around 16%, the best water application efficiency was achieved. Nevertheless, the lower quarter adequacy is 0.74, indicating that the field is under irrigated due to significant water constraints in the farm field. Simulation models of WinSRFR have proved to be an effective model for designing, forecasting, and optimizing the performance of conventional furrow irrigation systems. In earlier studies, researchers used fictitious scenarios to predict how well the furrow systems would perform by designing furrows with various lengths and flow rates on the same plot. The engineering approach used in this study was applied to actual crop fields, which greatly helped us predict the availability of the proper quantities of moisture to the crops and take the necessary action if the field was moisture deficient. Therefore, farmers can use our methodology to get deep insights into the performance of their fields and implement the necessary precautions to ensure the health of the crops.