Crop yield risk analysis and mitigation of smallholder farmers at quaternary catchment level: Case study of B72A in Olifants river basin, South Africa

Abstract Currently, Sub-Sahara is experiencing increased frequency of disasters either as floods or droughts which depletes the scarce resources available to sustain increasing populations. Success in preventing food shortages in the African continent can only be achieved by understanding the vulnerability and risk of the majority of smallholder farmers under rainfed and supplementary irrigation coupled with appropriate interventions. Increased frequency of floods, droughts and dry spells pose an increasing threat to the smallholder farmers’ food security and water resources availability in B72A quaternary catchment of the Olifants river basin in South Africa. This paper links maize crop yield risk and smallholder farmer vulnerability arising from droughts by applying a set of interdisciplinary indicators (physical and socio-economic) encompassing gender and institutional vulnerabilities. For the study area, the return period of droughts and dry spells was 2 years. The growing season for maize crop was 121 days on average. Soil water deficit during critical growth stages may reduce potential yields by up to 62%, depending on the length and severity of the moisture deficit. To minimize grain yield loss and avoid total crop failures from intra-seasonal dry spells, farmers applied supplementary irrigation either from river water or rainwater harvested into small reservoirs. Institutional vulnerability was evidenced by disjointed water management institutions with lack of comprehension of roles of higher level institutions by lower level ones. Women are most hit by droughts as they derived more than 90% of their family income from agriculture activities. An enhanced understanding of the vulnerability and risk exposure will assist in developing technologies and policies that conform to the current livelihood strategies of smallholder, resource-constrained farmers. Development of such knowledge base for a catchment opens avenues for computational modeling of the impacts of different types of disasters under different scenarios.