Thesis (MSc. (Agricultural Economics)) -- University of Limpopo, 2011 / In-field rainwater harvesting technology is the technique that combines the advantages of water harvesting, no till, basin tillage and mulching on high drought risk clay soils. It reduces total runoff to zero, and also considerably reduce surface evaporation. The scarcity of agricultural water is increasing at a faster rate than for other sectors in Limpopo Province. Sufficient, clean drinking water is essential to life, but millions of people throughout the world including South Africa continue to have no access to this basic necessity. This study aimed at investigating the extent and nature of adoption of in-field rainwater harvesting technology by households in Lambani village of Limpopo Province. The main objectives of this study were to identify factors determining the in-field rainwater adoption technology for cropland productivity in Lambani village and to determine the extent to which in-field rainwater harvesting adoption influences cropland productivity in Lambani village. Simple random sampling technique was used to select 70 farmers in Lambani village of Limpopo Province. Data was collected using a structured questionnaire. Descriptive statistics, logistic regression model and linear regression model were used to analyse the data. Descriptive statistics was used to describe the characteristics of households and the nature of Lambani village, and logistic regression model was used to investigate factors that determine the adoption of infield rainwater harvesting technology, while linear regression model was used to determine the extent to which in-field rainwater harvesting influence the cropland productivity in Lambani village. The results from the logistic regression model indicate that 5 variables out of 10 variables are significant in explaining farmers’ adoption decision. Land size, access to financial service, access to information and contact with extension officer are some of the variables that have significantly positive effects on the adoption of infield rainwater harvesting technology, while hired labour has significantly negative correlation with adoption. Variables such as household size, level of education, age of the household, level of income and the main water source do not significantly influence adoption of in-field rainwater harvesting. This information will help prioritize