Inter-annual variability in yields of rainfed crops is often attributed to changes in the weather conditions form year to year. Therefore, research efforts in dryland agriculture were focused either to on developing cropping strategies and management practices in accordance with the variability in seasonal rainfall and other weather parameters. Of late, there is a growing awareness of changes in global climate and its impact on agriculture. Scientists from all over the world have started analyzing historical weather data for different locations to examine
• Climatic variability from year to year
• Cyclic effects on climatic variability, and
• Trends in climatic variability
There were evidence that there is an increasing trend in global temperatures during the last hundred years although the magnitude of increase is not exactly the same in all the regions. Rapid industrialization, increased use of fossil fuels, destruction of native vegetation to bring more area under cultivation to meet the growing requirement of food have all contributed to increased greenhouse gases, atmospheric pollution and consequent changes in the world climate. The major cause to climate change has been ascribed to the increased levels of greenhouse gases like carbon dioxide (CO2), methane (CH4), nitrous oxides (N2O), chlorofluorocarbons (CFCs) due to burning of fossil fuels, increased use of refrigerants, and chemical-based agricultural practices.
These activities accelerated the processes of climate change and increased the mean global temperatures by 0.6°C during the past 100 years. It has also induced increased climatic variability and occurrence of extreme weather events in many parts of the world. Studies indicate that the recent years viz., 1997, 1998 and 1999 have been among the warmest during the past century and the process continued into the 21st century and the year 2010 was declared as the third warmest year since 1860, the period for which instrumental records are available.
According to IPCC (2007), the 21st century is projected to experience 1.8 to 4.0 C rise in surface air temperature together with very likely occurrence of frequent warm spells, heat waves and heavy rainfall and a likely increase in the frequency of droughts. Climate change scenarios for the Indian subcontinent as inferred by Lal (2001) from simulation experiments using atmosphere-ocean GCMs under the fourth Special Report on Emission Scenarios (SRES) marker scenarios suggest an annual mean area-averaged surface warming over the Indian subcontinent to range between 3.5 and 5.5°C over the region by 2080s. These projections showed more warming in winter season over summer monsoon. The spatial distribution of surface warming suggests a mean annual rise in surface temperatures in north India by 3°C or more by 2050.
The study also suggests that during winter, the surface mean air temperature could rise by 3°C in northern and central parts while it would rise by 2°C in southern parts by 2050. In case of annual rainfall, a marginal increase of 7 to 10 per cent is projected over the sub-continent by the year 2080. The study further suggests a decline in rainfall by 5 to 25 per cent in winter while it would be 10 to 15 per cent increase in summer monsoon rainfall over the country.
Crop growth models vis-a-vis Climate change
Crop growth models are widely used to simulate the impact of climate change on various crops such as rice (Tao et al., 2008), wheat (Hundal and Prabhajyot-Kaur, 2007, Chapman, 2008), groundnut (Challinor et al., 2007; Challinor and Wheeler, 2008) sorghum (Zeng and Heilman, 1997, Tingem and Rivington, 2009; Srivatsava et al., 2010) and maize (Xiong et al., 2007; Almaraz et al., 2008). In most of these studies, models are used to assess the crop response to changes in atmospheric CO2 and rise/fall in temperature.
For example, groundnut yields were simulated by INFOCROP model (Anonymous, 2010) under elevated temperatures (up to +3.5 C) and elevated CO2. The model projected that groundnut shows greater thermal sensitivity during the reproductive growth phase followed by a vegetative growth phase. The crop subjected to elevated temperature for the entire growth period showed the additive detrimental effect of high temperature during vegetative and reproductive growth phases. Reduction in groundnut yields was attributed to a drastic reduction in nuts per sqm, 1000 seed weight and biomass. Groundnut responded positively to elevated CO2 (560 ppm) which was again attributed to a marked increase in biomass and nuts per sqm. These models have inherent empiricism and assumptions that they often fail to take into account the interactive effects of more than one variable that occur in nature.
Climates all over the world are classified based on the thermal regime and moisture regime as both these factors have a profound influence on the native vegetation, agricultural production systems and their productivity. Thus, the crop response to variable and changing climate has to be examined considering the variability in thermal and moisture regimes together using real-time crop data. Such an approach may be helpful in assessing the factors that govern the changes in crop productivity from year to year and to identify research priorities to sustain and stabilize agricultural productivity in drylands
In order to assess the impact of changing thermal and moisture regimes on crop productivity under rainfed conditions, an analytical approach can be attempted using real-time data. To illustrate this approach, the variation in productivity of groundnut grown under rainfed conditions in Anantapur region of Andhra Pradesh was used an as example. The site was chosen because of its high inter-annual variation in rainfall (a 40-year mean of 572 mm with a standard deviation of 200 mm) to ensure crop seasons of contrasting water regimes.
Source-
- Centrial institue of dryland agriculture
