Optimizing Construction Scale of Field Pipe Network Project in Gravity-driven Drip Irrigation System

Abstract

【Background and objective】 Gravity-driven drip irrigation is a technology using water pressure drop generated by natural terrain to deliver water from its source to emitters. The multi-level drip irrigation system uses its first-level pivot as the water source to deliver water to each head pivot in the subsystems by a pipe network. Optimizing the pipe network is hence critical to reducing project cost without compromising its operation. The objective of this paper is to present a new optimization method. 【Method】 We took minimization of the comprehensive cost per unit area of the project as the objective function, and the layout of pipe network, pipe diameter, emitter-flow rate and water pressure as constraints. The optimization model was solved using the atom search optimization. We applied the method to a two-level gravity-drive drip irrigation project in Xinjiang to demonstrate its reliability. 【Result】 The cost per unit area is least when construction area of the pipe network project is 89 hm2, and excellent when the construction area is in the range of 74 to 98 hm2. Optimization of the construction area under different combinations of emitter spacing, capillary pipe spacing, and emitter-flow rate shows that the optimal results vary with their combinations. For length-width ratio of the construction field in the range of 1.00 to 1.30, the minimized cost per unit area decreases with the increase in emitter spacing and capillary-pipe spacing and increases with the increase in emitter-flow rate. 【Conclusion】 The proposed optimization method is able to optimize pipe network for multi-level gravity-driven drip irrigation systems. The method is computationally stable and efficient. It is applicable for designing gravity-driven drip irrigation network systems.

Keywords

• multi-level pivot
• gravity drip irrigation
• field pipe network project
• optimization of construction scale
• atom search optimization