This study addresses the problems of severe deep percolation, low water use efficiency, and the difficulty of reconstructing the spatiotemporal soil moisture distribution in the 0–60 cm root zone under traditional empirical drip irrigation for greenhouse strawberries. An intelligent irrigation method is proposed by integrating real-time soil moisture data obtained from frequency domain reflectometry (FDR) sensors with the HYDRUS-2D mechanistic model. High spatiotemporal resolution FDR data are assimilated into the HYDRUS-2D framework to dynamically calibrate key soil–root parameters, enabling two-dimensional simulation and water balance analysis of drip irrigation infiltration, root water uptake, soil evaporation, and deep percolation processes. Compared with SIMDualKc and AquaCrop models, the proposed FDR-HY2D approach achieves higher accuracy in simulating soil moisture dynamics across different irrigation treatments and soil layers, with increased R2 and reduced RMSE and MAE. The model effectively reproduces daily moisture variations and vertical gradients in the root zone. Moreover, intelligent irrigation based on FDR-HY2D shifts water allocation from deep percolation to crop transpiration, significantly improving effective water use and water use efficiency. This study provides a digital decision-support tool for precision irrigation and water–fertilizer management in greenhouse strawberry production.
Tang et al. (Thu,) studied this question.
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