A rigorous analysis of trends in rainfall season of an area over a lengthy period of time can be effectively used as a tool to guide small holder farmers in their activities. Climate change adaptation is important to ensure sustainability and survival in rainfed crop farming. In this study two districts (Chirumhanzu and Zvishavane) in the Midlands Province of Zimbabwe were selected and rainfall data for the areas was provided by Zimbabwe Meteorological Services Department. Rainfall characteristics that include onset times, cessation times, length of seasons, total amount of rainfall, number of rainy days, dry spell and risk of water logging were analysed to provide farmers with an indicative picture of possibilities in their respective areas in a bid to reduce risks of crop failure due to uncertainties brought about by climate change and variability. Time series analysis method together with risk analysis were the statistical methods employed to understand better the risk and measures that can be taken by farmers. For Chirumhanzu it was concluded there is a 41% risk of replanting if farmers plant with the first rains received. However, over the period this risk seems to be decreasing. Farmers are encouraged to stagger the planting to minimise risk. Risk analysis showed that for Zvishavane the mean number of rainy days for Zvishavane is 34 with a possibility of 45 days in good seasons and 23 days in poor seasons The tool guides meant for farmers require proper packaging and systematic channels to promote buy-in by the end users of the information.

The study was aimed at reducing internal air temperatures of a greenhouse shelter as this is one of the main problems facing greenhouse management in warm climates such as in Zimbabwe. The water vapour balance method was used to evaluate the ventilation rate and the results were employed in calibrating and validating the ventilation sub-model of the greenhouse climate model, the GDGCM model, in a naturally ventilated three span Azrom type greenhouse in Zimbabwe. Two ventilation regimes namely: configuration with roof vents only with closed side vents and configuration with both side vents and roof vents open, were investigated. Crop transpiration was estimated using the Penman-Monteith method. The model was fitted to experimental data for ventilation rates, and the parameters for the model, the discharge and wind effect coefficient were determined using statistical analysis. The results showed that there was a good fit between measured and predicted values (R 2 = 0.702 and 0.729) for the model on the two ventilation regimes. The air renewal rate was found to be influenced by the nature of ventilation regime in place. The model simulation revealed that the greenhouse has higher air renewal rates for the configuration with both roof and side vents. The greenhouse internal air temperature was reduced significantly for the latter configuration as it had lower simulated air temperatures than the former.