Field Evaluation of Irrigation Scheduling Strategies using a Mechanistic Crop Growth Model

Abstract

AbstractIn a field experiment with white cabbage (Brassica oleracea L. var. capitata (L.) alef.) in Germany, three irrigation scheduling approaches were tested: (i) three sprinkler irrigation schedules based on soil water balance calculations using different development‐dependent crop coefficients; (ii) automatic drip irrigation based on soil water tension thresholds; (iii) irrigation scheduling by real‐time application of a partially calibrated mechanistic crop growth model. Multi‐objective calibration was applied to derive a fully calibrated model as a diagnostic tool to identify the water loss terms of the individual irrigation strategies.The results of the experiment showed that: (i) high yields can be achieved with relatively low amounts of irrigation water (~100 mm), provided the optimal irrigation strategy and technique are applied; (ii) automated tension threshold‐based drip irrigation outperformed soil water balance or crop growth model‐based strategies; (iii) the soil water balance calculation approach relying on recommended Kc factors led to an enormous overirrigation; (iv) the application of a partially calibrated crop growth model led to an underestimation of the crop water requirements in conjunction with an incorrect timing of irrigation events and therefore resulted in the lowest yields. The diagnostic model identified percolation, for the wet sprinkler irrigation treatments, and canopy evaporation, for the dry and model‐based treatments, as major water loss sources; only minimal additional water was lost in the tension‐controlled treatment. Copyright © 2016 John Wiley & Sons, Ltd.