One of the imminent threats posed by climate variability and change is food
security in Zimbabwe’s semi-arid regions like Masvingo. As an adaptive strategy
crop forecasting was employed to improve crop productivity. The objective of
the study was to investigate climatic characteristics responsible for yields in the
maize, sorghum and millet crop varieties and to calibrate Food and Agriculture
Organization (FAO)-AquaCrop model for crop forecasting purposes. AquaCrop
simulation results were used together with empirical ones to see if the model
could be relied on in crop forecasting. Seeds for the three crops were sown at
the same time and were observed for five months from 1 November 2011 to 31
March 2012. Crop management practices were employed. An automated weather
station was recording the soil moisture, air temperature and net radiation for the
five months. The climatic data recorded by the station was used as input data in
the model and it predicted yields for the crops. Comparison between simulated
and observed parameters of the water balance, biomass production and final
yield were used for the calibration of the model. The model gave a slightly higher
harvest index (HI) (ratio of yield to biomass) than what had been obtained in the
experimental treatments, with a 10% margin. The information from the station
and model provided optimum temperatures and water requirements which
essentially uphold water use efficiency especially where automated irrigation
based on air temperatures is implemented. The results from this publication are
from the first year stage only and therefore are subject to improvement.