Southern Africa is one of the most vulnerable regions to climate change, and climate change impacts will heighten the challenge of achieving its sustainable development goals. In this context, effectively adapting to climate change is critical. Agriculture plays a critical role in the economies of most countries in Southern Africa and is among the livelihood strategies of most local people, even though agriculture in the region is currently characterised by low productivity, low levels of investment, and high levels of weather and climate-related risk. Therefore, there is a dire need to improve and intensify agricultural production to ensure food security across the region.

One proposed solution to the intertwined challenges of climate change and food insecurity is climate-smart agriculture (CSA). Smallholder farmers across the region can benefit from CSA as it can increase agricultural production while reducing or removing greenhouse-gases emissions where possible, thus securing individual livelihoods, and local food security, despite the increasing climate variability being caused by climate change. However, there is further work needed to assess the most appropriate CSA practices that can sustainably increase agricultural production (i.e. crop and water productivity) under different climatic conditions, especially for local rainfed smallholder farming systems. Since most smallholder farming systems in Southern Africa are in marginal and data-limited areas, this study, therefore, aims to integrate remote sensing with crop modelling to assess potential future climate-smart agricultural practices to improve their crop and water productivity. Hence, improve the region’s capacity to understand local farming systems and better adapt to climate change.