Simulated impacts of climate change on water use and yield of irrigated sugarcane in South Africa

Abstract

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 La Mercy) for current 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. 2Future climate datasets were generated using the Delta downscaling method and three Global Circulation Models (GCMs) assuming atmospheric CO 2 concentration [CO 2 ] 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 cycles investigated.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.

Implications of climate change for the sugarcane industry

“…Through these steps, we found 27 additional studies, which were also included. Relevant insights on climate change and the sugarcane industry have also been published as book chapters, in the Proceedings of the International Society of Sugar Cane Technologists, the Australian Society of Sugar Cane Technologists, as well as the Proceedings of the South African Sugar Technologists Association . One paper was excluded from further analysis because the full text was not available .…”

“…The industry contributes significantly to gross domestic product in major sugarcane producing economies such as Brazil, India, and China. From the late 1990s onward, driven by growing concern about climate change and its potential economic consequences for the agricultural sector, researchers began to study the impacts of climate change on sugarcane production to better understand how projected changes in variables such as air temperature, rainfall, and atmospheric carbon dioxide (CO 2 ) concentration influence sugarcane production . This has created a body of knowledge of how changes in climate lead to changes in the primary production of sugarcane.…”

Understanding changes and trends in projected hydroclimatic indices in selected Norwegian and Polish catchments

“…Numerous studies have employed the MK (Chattopadhyay and Edwards 2016;Tosunoglu and Kisi 2016) and MMK (Giuntoli et al 2013;Kibria et al 2016). These are possibly the most widely used nonparametric tests for trend detection in hydrological and climatological studies (Mitof and Pravalie 2014;Jones et al 2015). This is because they are not only simple to use, but they are also resilient to skewed distribution, missing values and values that fall outside the detection limit, and to the nonstationary nature of data (Chaouche et al 2010;Jeneiova et al 2014).…”

Drying‐Off Periods for Irrigated Sugarcane to Maximize Sucrose Yields Under Brazilian Conditions

“…These differences can probably be associated with differences in weather conditions, mainly air temperature and vapour pressure, in the models´ structures (DSSAT/CANEGRO × APSIM‐Sugarcane), and the cultivars considered (calibration). Regarding the thermal pattern, Petrolina has annual average maximum and minimum air temperatures of 31.7 and 21.9°C, whereas in Pongola these values are 27.4 and 15.5°C, respectively (Jones et al ).…”