Agriculture consumes the largest share of freshwater globally, therefore, distinguishing between rainfed and irrigated croplands is essential for agricultural water management and food security. Yet in Africa, disaggregating croplands is challenging due to the continent's vast size, diverse climates, and varied agricultural practices. In this study, a framework using the Budyko model was applied to differentiate between rainfed and irrigated cropland areas in Africa for eight remote sensing landcover products and a high confidence cropland map (HCCM). The approach outlined in this research expands on the suite of remote sensing landcover products that can be used for agricultural water studies in Africa by enabling the extraction of irrigated and rainfed cropland data from landcover products that do not have disaggregated cropland classes.