Crop Growth Simulation Modelling and Climate Change

Contents: 1. Crop growth simulation models in agricultural crop production/M. Mohanty, Nishant K. Sinha and Ashok K. Patra. 2. Applications of crop growth simulation models in climate change assessments/M. Mohanty, Nishant K. Sinha, Rohit Patidar and Ashok K. Patra. 3. Biophysical impacts and priorities for adaptation of agricultural crops in changing climate/R. Elanchezhian. 4. Climate change projections-India’s perspective/K.M. Hati, M. Mohanty and R.S. Chaudhary. 5. Impact of rising atmospheric CO2 concentration on plant and soil process/M.L. Dotaniya. 6. Modelling the impact of climate change on soil erosion in stabilization and destabilization of soil organic carbon/Debashis Mandal, N.K. Sharma, Rajeev Ranjan and P.K. Mishra. 7. Simulating crop yield, soil processes greenhouse gas emission and climate change impacts with infocrop model/K.K. Bandyopadhyay, B. Chakrabarti and H. Pathak. 8. Crop syst model and its application in natural resource management/Sangeeta Lenka and N.K. Lenka. 9. Climate change and crop production system: assessing the consequences for food security/Dilip Kumar Swain and Sushree Sagarika Satapathy. 10. A biophysical model to analyse climate change impacts on rainfed rice productivity in the Mid-hills of Northeast India/B.U. Choudhury, Anup Das, K.P. Mohapatra, Tazin A. Choudhury and S.V. Ngachan. 11. Auacrop modelling: a water driven simulation model/Monalisha Pramanik and Rajeev Ranjan. 12. Conservation agriculture: a strategy to cope with climate change/K.M. Hati, J. Somasundaram, R. Saha and M. Mohanty. 13. Climate change impact assessment using DSSATmodel/Nishant K. Sinha, M. Mohanty, Smita Gupta, Pankaj K. Tiwari, Bharat P. Meena and Rohit Patidar. 14. Integrating remote sensing data in crop process models/Nirmal Kumar, N.K. Sinha and M. Mohanty. 15. Decision support system for managing soil fertility and productivity in agriculture/A.K. Vishwakarma, Brajendra, K.M. Bujarbaruah, S.V. Ngachan and K.A. Pathak. 16. De-nitrification de-composition model-an introduction for SOC simulations/Pramod Jha. 17. Crop simulation modelling for climate risk assessment: adaptation and mitigation measures and rules of simulations/M. Mohanty, Nishant K. Sinha, R.S.Chaudhary andAshok K. Patra. 18. Rothamsted carbon (Roth C) model and its application in agriculture/P. Bhattacharya, J. Somasundaram, N.K. Sinha, M. Mohanty and R.S. Chaudhary. Referecnes. Subject index.

Global food security has been threatened by climate change and has become one of the most important challenges in the 21st century to supply sufficient food and nutrition for the increasing population while sustaining the already stressed environment. Studies on impacts of climate change and adaptation strategies to overcome such problems are increasingly becoming major areas of concerns for the scientists, researchers and policy makers. The climate change impacts on the production of crops like rice, wheat, maize, soybean and water resources in the river basin catchments have been studies by researchers in many parts of the world using simulation modelling. Crop productivity and soil water balance have been studied with crop growth models by using parameters from different climate models. Meanwhile, climate variability is one of the most significant factors influencing year to year crop production, even in high yield and high-technology agricultural areas.

In recent years, more and more attention has been paid to the risks associated with climate change and associated problems and hence on productivity of crops in agriculture. Water availability will be one of the limiting constrains for crop production and food security. Therefore, it is an urgent need to determine the impacts of climate change on crop production in order to employ possible adaptation strategies in farm level as well as regional level. In the last decade, crop simulation models have become essential tools to support field research and agricultural productivity in developing and developed countries. Simulation modelling result can be extrapolated to different conditions and cultivars and other cropping systems contrasting to conventional field experiments. The most potential application of crop growth simulation modelling is the prediction of crop yield under different climate change scenarios. This book provides a comprehensive work related to the assessment of climate change impacts on crop productivity and use of crop growth simulation models to assess such impacts on agriculture.