ABSTRACT
Soil–Vegetation–Atmosphere Transfer (SVAT) models are commonly used to describe crop‐seasonal dynamics including the prediction of crop yield and water balance. In the case of absent detailed information, a straightforward application of the model using given parameter sets may take place against rather different soil and/or climate conditions. The objective of this study was (i) to calibrate and validate a SVAT model utilizing data of two sites and two crops, (ii) to evaluate the model's ability to employ plant parameters determined on the basis of field data against greenhouse data, and (iii) to estimate optimal irrigation schedules for maximizing water productivity. Irrigation experiments were conducted on a field rain‐out shelter (wheat and barley) and in a container greenhouse experiment (barley). In the case of barley which was only grown in 2009, inverse calibration of plant data was carried out using field data, whereas the DAISY model was validated against independent greenhouse data. For validation, the specific condition in a container greenhouse experiment was taken into account. The study shows that DAISY performed well with simulating lightly drought‐stressed crop growth and water balance. For both crops and sits, optimal irrigation schedules were determined in a simulation‐optimization study which led to considerable irrigation water savings. Copyright © 2011 John Wiley & Sons, Ltd.