Management of surface flow allocation in rice cultivation by maximization of water use and economic efficiency

Abstract

The multi-objective genetic algorithm was used as a decision variable to estimate the water required for irrigation in each of the growth stages. Agricultural costs and product sales prices in the agricultural year 2017–2023 in Luoyang Plain and its surrounding areas were collected for this purpose. Optimal irrigation strategies according to different water price scenarios were considered to calculate water use efficiency and net profit. In the conditions of optimal distribution, the amount of allocated water was 7,809, 2,928, 3,904, and 1,789 m3/ha for the stages of vegetative growth, flowering, crop formation, and ripening by the proposed model. On the other hand, it is necessary to reduce water stress in the periods of clustering and seed filling to increase crop yield and net income, as well as to achieve the desired irrigation schedule. Effective rainfall, especially in the ripening stage of the crop, can be considered to determine the optimal volume of water harvesting from the river. In addition, the results showed that by reducing the amount of available water, the water model allocated to leaf greening and tillering stages decreases. HIGHLIGHTS A simulation model is calibrated using field data for rice cultivation.; The economic value of water adjustments has been measured in different stages of planning.;

Keywords

• deficit irrigation
• genetic algorithm
• net profit
• surface water