The invention discloses a
crop irrigation short-term prediction method and
system based on fuzzy control, and relates to the technical field of intelligent
agriculture and
irrigation control, and the method comprises the steps: collecting weather, multi-depth
soil moisture content and field
time sequence data of a
crop growth stage, and obtaining
irrigation feedback;
processing the data, and inputting a
time sequence prediction model to output
water demand prediction values of one to three days and confidence obtained by mapping historical
verification errors; fuzzifying the
water demand predicted value, the real-time root zone
moisture content and the growth stage index, performing weighted deduction and fuzzification based on a
fuzzy rule base with a rule dynamic weight, and outputting planned irrigation duration or irrigation amount; and calculating the actual
water consumption and updating the dynamic weight of the rule in the post-irrigation evaluation time window according to the
water balance and the root zone soil
moisture reserve variation. Through confidence risk suppression and post-irrigation closed-loop self-tuning, the stability of short-term prediction driving irrigation decision is improved, the over-irrigation and over-seepage risks are reduced, and the utilization efficiency of
irrigation water is improved.