Optimal irrigation scheduling for sustainable agriculture: Minimising energy costs in rotational management

Water scarcity, intensified by climate change and growing agricultural demand, is a significant challenge, particularly in irrigation. Modern irrigation systems have improved water efficiency, but also increased energy consumption, a concern with rising energy prices impacting farmers. Although considerable research has focused on optimising energy use in on-demand irrigation systems, rotational management systems remain under-researched. These systems, essential in regions with limited water resources or infrastructure constraints, have received insufficient attention, particularly regarding the optimisation of the irrigation schedule to enhance cost efficiency. This study addresses this gap by proposing a methodology for optimising weekly irrigation schedules in rotational management, taking into account branch capacity and critical pump nodes while aligning pumping schedules with lower electricity costs. Implemented in an irrigation network in South Tyrol, Italy, the methodology uses Particle Swarm Optimisation and network sectoring to optimise irrigation sequences and achieve more cost-effective operations. The results demonstrate that the implementation of an optimised irrigation schedule in scenarios characterised by higher electricity prices leads to significant savings. The analysis revealed a cost reduction in all scenarios, ranging from 19.8% to 36.8%. This finding suggests that farmers and network managers should prioritise energy-efficient irrigation scheduling during periods of elevated energy costs. In addition, the results emphasise the importance of integrating considerations of the energy market into irrigation strategies and highlight the need for tools that assist operators in making informed decisions. • Optimisation of pumping costs using particle swarm optimisation and network sectoring. • Identifying the optimal cost-effective irrigation schedule within network constraints. • Achieved savings of 19.8% to 36.8% with optimised schedules in high-price scenarios. • Integration of the energy market considerations into irrigation management strategies.