Water Saving Irrigation Decision-Making Method based on Big Data Fusion

摘要

In order to realize the intelligence of irrigation management and the wisdom of irrigation decision-making, improve the efficiency of water resource utilization, and introduce information fusion technology into the field of farmland irrigation, an irrigation decision-making method based on multi-source information fusion is proposed. Firstly, according to the actual situation and specific needs of the study area, the multi-objective irrigation water quantity optimization configuration model is constructed, and the multi-objective intelligent algorithm is used to solve the model. Then, using the adaptive weighted average fusion algorithm, the weight coefficient of soil moisture of millet in different growth stages and different soil layers is constructed, and the fusion of soil moisture in the data layer is realized. Finally, in order to meet different irrigation requirements, the multi-objective particle algorithm is used to solve the multi-object canal optimal water allocation model based on the optimized configuration of irrigation water volume. The experimental results show that the fusion results obtained by the multi-source large data adaptive weighted fusion algorithm are more reasonable, the uncertainty of irrigation decision-making is greatly reduced, the reliability of irrigation decision-making is improved, and the water consumption can be saved by 25.61% by using the multi-objective optimal allocation model.