Developing an optimal plan to improve irrigation efficiency using a risk-based central force algorithm

Abstract

Abstract Losses in surface irrigation include deep percolation and runoff, which is one of the ways to increase the efficiency of furrow irrigation, using a closed-end mode in irrigation systems. This research was conducted to evaluate the effects of geometrical variables (slope and length of furrow) and flow control (inflow rate and cut-off time) on application efficiency (AE) and the uniformity of water distribution in a closed-end furrow irrigation system. The length, slope, inflow rate, and cut-off time are considered as the decision-making variables for developing the multi-objective genetic algorithm based on the non-dominated sorting. For this purpose, three irrigation furrows with the closed-end system were considered. The optimization algorithm for calculating the objective functions involves maximizing the minimum water depth and minimizing the infiltration depth in a modeling loop. The optimization algorithm was linked to the WinSRFR software to calculate the objective functions. The results showed that the best combination of inflow rate and the cut-off time for 75 mm of required water depth was 1.9 L/s/m and 150 min, respectively, which increased AE and distribution uniformity to 79 and 78%. Furthermore, the AE in the closed-end furrow irrigation system is higher (30–50%) than the open-end method in different scenarios.