Impact of Climate Change On Productivity in Rice-Wheat Cropping System of Indo-Gangetic Plains.

Rice and wheat, the major cereal crops of  the Indo-Gangetic plain (IGP) of South Asia, grown in rotation in almost 13.5 million hectares are the principal source of food, nutrition and livelihood security for several hundred millions of people in the region. The yield of Rice & Wheat crops is either on the decrease or has stabilized (Ladha et al., 2003) in the region. The total factor productivity is declining because of extreme events, climate change and its variability, nutrient mining and water depletion and soil degradation. Inter-and intra-seasonal climatic variability and occurrences of extreme climatic events, such as rise in temperature in specific growth period (more recently in 2006 - in month of January & February in northern part of India and Pakistan), drought, floods, have increased in last couple of decades. The annual mean warming by 2020 is projected to be between 1.0 and 1.4°C and between 2.23 and 2.87°C by 2050, and may rise to 3-4°C towards the end of 21st century (DEFRA, 2005; IPCC, 2007). Temperature in the IGP is touching the critical limits observed for major food grain crops (rice & wheat) and further increase in temperature will affect the yields of rice and wheat.

Monitoring the long term effect of climate change can be accessed by identifying the associated factors and their change over the period. Long term experiments (LTE) provide unique opportunity to study the changes in the grain yield in conjunction with changes in soil (OC, P, K and micro nutrient) and climatic parameters. We are analyzing 28 rice-wheat LTE (varying from 20 to 27 years) data collected from Indo-Gangetic plains of India, Bangladesh and Nepal to assess effect of climatic variability on historical yield trends of rice and wheat. Long term (35-50 years) district average yield of rice & wheat is collected from IGP of India, Nepal, Bangladesh and Pakistan for measuring the yield trends and its relation to downscale climatic scenarios generated using PRECIS model.  Multi-spectral and hypersepctral remote sensing data will be used to estimate crucial climatic parameters e.g concentration of troposphere gases (eg.CO₂ / NO₂) and Land use/Land cover etc. The study is utilizing the remote sensing & GIS techniques and simulation models to integrate bio-physical and socio-economic parameters and thereby providing the site specific solutions to vulnerable regions in terms of climate change.