Reliable predictions of climate change impacts on water use, irrigation requirements and yields of irrigated
sugarcane in South Africa (a water-scarce country) are necessary to plan adaptation strategies. Although previous
work has been done in this regard, methodologies and results vary considerably. The objectives were (1) to
estimate likely impacts of climate change on sugarcane yields, water use and irrigation demand at three irrigated
sugarcane production sites in South Africa (Malelane, Pongola and LaMercy) for current (1980–2010) and future
(2070–2100) climate scenarios, using an approach based on the Agricultural Model Intercomparison and
Improvement Project (AgMIP) protocols; and (2) to assess the suitability of this methodology for investigating
climate change impacts on sugarcane production.
Future climate datasets were generated using the Delta downscaling method and three Global Circulation Models
(GCMs) assuming atmospheric CO2 concentration [CO2] of 734 ppm (A2 emissions scenario). Yield and water use
were simulated using the DSSAT-Canegro v4.5 model.
Irrigated cane yields are expected to increase at all three sites (between 11 and 14%), primarily due to increased
interception of radiation as a result of accelerated canopy development. Evapotranspiration and irrigation
requirements increased by 11% due to increased canopy cover and evaporative demand. Sucrose yields are expected
to decline because of increased consumption of photo-assimilate for structural growth and maintenance
respiration. Crop responses in canopy development and yield formation differed markedly between the crop
Possible agronomic implications of these results include reduced weed control costs due to shortened periods of
partial canopy, a need for improved efficiency of irrigation to counter increased demands, and adjustments to
ripening and harvest practices to counter decreased cane quality and optimise productivity.
Although the Delta climate data downscaling method is considered robust, accurate and easily-understood,
it does not change the future number of rain-days per month. The impacts of this and other climate data simplifications
ought to be explored in future work. Shortcomings of the DSSAT-Canegro model include the simulated
responses of phenological development, photosynthesis and respiration processes to high temperatures, and
the disconnect between simulated biomass accumulation and expansive growth. Proposed methodology
refinements should improve the reliability of predicted climate change impacts on sugarcane yield.