ABSTRACT
Agricultural production will face uncertainty as there is regional variation of rainfall, temperature, soils, crop yields, cropping systems and management practices (Palanisami et al. 2011). The crop losses may increase further if the predicated climate change (CC) increases climate variability. Crop growth simulation models also indicated that yield of some crops in tropical regions would decrease generally even with a minimal increase in temperature under dryland agriculture (Rao et al. 2008). In order to strengthen climate forecasts, researchers are also developing ex-ante type CC forecasts by innovative approaches to assess the uncertainty of the climate impacts (Mendelsohn et al. 2000; Immerzeel 2008). Scientists have also estimated that under moderate CC scenarios, there could be about 9 per cent decline in farm-level net revenues in India (Kumar and Parikh 2001; Sanghi and Mendelsohn 2008). A one degree increase in temperature may reduce yields of wheat, soybean, mustard, groundnut, and potato by 3-7 per cent (Kumar et al. 2010). The yield losses are likely to be substantially higher with the long-term CC scenarios (Nagothu et al. 2012). Such climate forecasts, tools and scenarios can help evaluate sector-specific incremental changes in risk over the next few decades (Wilby et al. 2009). The studies in this book clearly outline the effects of CC on crop production and income; therefore, appropriate adaptation measures at farm level are absolutely necessary.
