Sensitivity and uncertainty propagation in coupled models for assessing smallholder farmer food security in the Olifants River Basins, South Africa
MetadataShow full item record
Magombeyi, M.S. and Taigbenu, A.E. 2014. 'Sensitivity and uncertainty propagation in coupled models for assessing smallholder farmer food security in the Olifants River Basins, South Africa.' Environmental Modelling & Software 60: 228-240.
Permanent link to cite or share this item: https://hdl.handle.net/10568/41710
External link to download this item: http://www.sciencedirect.com/science/article/pii/S1364815214001601
Using family balance (i.e., combined net farm and non-farm incomes less family expenses), an output from an integrated model, which couples water resource, agronomic and socio-economic models, its sensitivity and uncertainty are evaluated for five smallholder farming groups (AeE) in the Olifants Basin. The crop management practiced included conventional rainfed, untied ridges, planting basins and supplemental irrigation. Scatter plots inferred the most sensitive variables affecting family balance, while the Monte Carlo method, using random sampling, was used to propagate the uncertainty in the model inputs to produce family balance probability distributions. A non-linear correlation between in-season rainfall and family balance arises from several factors that affect crop yield, indicating the complexity of farm family finance resource-base in relation to climate, crop management practices and environ- mental resources of soil and water. Stronger relationships between family balance and evapotranspira- tion than with in-season rainfall were obtained. Sensitivity analysis results suggest more targeted investment effort in data monitoring of yield, in-season rainfall, supplemental irrigation and maize price to reduce family balance uncertainty that varied from 42% to 54% at 90% confidence level. While sup- plemental irrigation offers the most marginal increase in yields, its wide adoption is limited by avail- ability of water and infrastructure cost.