A Numerical Procedure to Improve Drip Irrigation Management of Field Grown Strawberry.

Irrigation management based on soil water potential (SWP) has proven effective in improving yield and water use efficiency with many different crops, including strawberries. However, problems related to inadequate water application methods were reported when applying SWP-based irrigation to strawberries in coarse soils. The objectives of this study were 1) to calibrate and validate a numerical model predicting the SWP in the root zone with data from a field strawberry irrigation experiment; 2) to use model predictions to evaluate the impacts of various irrigation management parameters on root water uptake, leaching beneath the root zone and WUE; 3) to establish optimal irrigation strategies for the studied field. Three SWP datasets, climatic data and water balance data were collected from a field experiment in which a pulsed irrigation management strategy was compared to a conventional strategy. The HYDRUS 2D numerical code in conjunction with the PEST optimization algorithm was used to optimize the soil hydraulic function parameters required by the model with one SWP dataset. Two additional SWP datasets were used to compare model predictions to field observations. HYDRUS 2D was then used in conjunction with SENSAN to evaluate the effects of all possible permutations of five levels of four irrigation management parameters (ETo, irrigation initiation threshold, irrigation duration, emitter discharge rate) and two drip lateral configurations. Results showed a good agreement between model predictions and field observations. Irrigation duration and emitter discharge rate were shown to be the most influential input parameters on most model outputs. Analysis of model predictions revealed that root uptake is greatly affected by anoxic conditions and that SWP-based irrigation initiation thresholds should be adjusted during the day for an optimal irrigation management at the experimental site.