施設栽培イチゴにおけるFDR-HY2Dを用いた空間的・時間的根域水分デジタル再構築と精密灌漑

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.