Simulating the impact of climate change and its variability on agriculture

Abstract

Indian agriculture is mostly intensive and presently showing concerns of decline in productivity primarily due to deteriorating soil health (in terms of physical, chemical and biological), surface/ground waters concerns (quality and quantity), and newly emerging insects/pests). Climate change and climatic variability are of great concerns, especially in India. Probabilities of occurrence of extreme/episodic events have increased over the last three decades. There is need to sustain agricultural productivity and safeguard the environment under these climatic/episodic events. Agricultural productivity can be affected by climate change; directly, due to changes in temperature, precipitation or CO 2 levels and indirectly, and through changes in soil health and infestation by insects/pests. Our country has numerous and complex agro-ecologies and production environments, so there is a need to evaluate the impact of climate change on regional scale, by incorporating socio-economic and bio-physical drivers along with the climatic elements. Crop models (mainly dynamic/mechanistic) can effectively integrate these aspects for assessing the impact of future climate change as well suggest suitable options for suggesting suitable mitigation and adaptation strategies. Several simulation models viz. INFOCROP, WTGROWS, ORYZA, DSSAT, APSIM have been developed and widely used for resource and inputs management, plant ideo-typic designs, climate change/its variability impact evaluation, yield forecasting and addressing extreme/episodic events. By using these models, differential response of reduced crops yields to rising temperatures was evaluated at several locations. Interaction of changes in CO2 concentration and solar radiation with temperature was noticed through modifcations in soil and crop processes and subsequent realization in grain yield. Crop models have been successfully employed for suggesting suitable mitigation and adaptation strategies (such as choice of crops/cropping systems, water/nutrients management options, adoption of suitable agronomic management) for reduction in GHGs emission and sustenance of agricultural production. Crop models have been successfully employed for assessing extreme/episodic events, viz.