Title : Performance of aquacrop model for simulating maize growth and yield under varying sowing dates in shire area, North Ethiopia
Adjusting the proper sowing date of a crop at a particular location with a changing climate is an essential management option to maximize crop yield. Determining optimum sowing date for rainfed maize production through field experimentation may require repeated trials for many years in different weather conditions and crop managements. In such a way, crop models such as AquaCrop are useful. Therefore, the overall objective of this study was to evaluate the performance of AquaCrop model in simulating maize cultivation under varying sowing dates. Field experiments were conducted for two consecutive cropping seasons by deploying four maize seed sowing dates in a randomized complete block with three replications. Input data required to run this model are stored in climate, crop, soil, and management files of the AquaCrop database and adjusted through the user interface. Observed data of separate field experiment was used to calibrate the model. AquaCrop model was validated for its performance in simulating the green canopy and aboveground biomass of maize for the varying sowing dates based on the calibrated parameters. Results of the present study shows, a good agreement between measured and simulated values of the canopy cover and biomass yields. Considering the overall values of the statistical tests, performance of the model to predict maize growth and biomass yield was successful.
Key word: AquaCrop model, Biomass yield, Canopy Cover, Calibration, Validation, Simulation