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Climate Change Impacts on Rice Production

Course Name: 
Climate Change Downscaling Approaches and Applications - Course 2 (2015)
Body: 

Dr. Dillip Kumar Swain, Indian Institute of Technology Kharagpur, India
Dr. Lal Samarakoon, Geoinformatics Center, Asian Institute of Technology, Thailand
Mr. Kavinda Gunasekera, Geoinformatics Center, Asian Institute of Technology, Thailand

Objectives

This session aims to train the students on use of crop models for (1) simulation of rice yield under varying production management scenarios, (2) analysis the future climate change impacts on rice production and (3) evaluation of agro-adaptation options to mitigate the climate change impact on rice production through case study based on GIS.

Description

Farming is risky in tropical and sub-tropical regions of the developing world, because of high variability of climate. The impact of climate change on agricultural production varies from region to region, for example, this may bring benefit to crop production in higher latitudes (> 550 N), while the places particularly tropical and sub-tropical countries (developing world) will be adversely affected. If the climate change effects dominate, world crop yields are likely to be decreased significantly. Rice, the second most important food crop after wheat in world, is grown on about 145 million hectares with an annual production of 518 million tones, which is mostly concentrated in Asia.
As crop production system is more complex, because of involving environment, fertilizer, pest control, genotype, cultural practices, etc; conducting trials that take all these factors into account becomes increasingly complex and expensive too. A suitably validated crop simulation model could be used to test many such combinations in a brief time at limited expense and such simulations can adequately describe relative trends in yields caused by environmental variation. In this training programme, we will deliver the application of crop modeling and simulation in agricultural research and discuss in detail about the rice model ‘CERES-Rice’ of DSSAT (Decision Support System for Agro-Technology Transfer). We will train the students on use of the crop model in forecasting rice yield for climate change scenarios. Also agro-adaptations (change in plating time, nutrient management, varieties, etc) will be evaluated through simulation analysis for better adaptations to climate change on regional basis.
GIS is a tool that facilitates the use of various spatial data including physical, social and economical data to study a given problem in a comprehensive manner. Therefore, GIS can be considered as a tool that provide invaluable support in handling data and information in studying a very complex and interdisciplinary problem like climate change and related adaptation issues and strategies. GIS session under the Impact on Rice Production provides the basic knowledge of GIS and the necessary skill through hands-on session to address impact of climate change on rice cultivation. The case study was prepared using data over an agricultural area in Thailand to identify possible adaptation strategies to cope with economic impact on rice cultivation due to climate variations.

Outline

Lecture 1: Introduction to Crop Models

  1. Introduction on rice production system and climate change in agriculture
  2. Rationale of crop simulation models
  3. Terminologies in crop models
  4. Simulation approach
  5. Concepts in developing crop system model
  6. Crop Simulation models of DSSAT
  7. CERES-Rice of DSSAT

Lecture 2: Setting up the Crop Model (CERES-Rice of DSSAT)

  1. File system of the model
  2. Input data requirements
  3. Data management tools
  4. Data analysis tools
  5. Model calibration and validation
  6. Uncertainty and risk analysis

Exercise: Rice yield simulation (a Case Study of Thailand)

  1. Data inputs (weather, soil and crop data)
  2. Creation of experimental file
  3. Model calibration and validation
  4. Rice yield simulation for climate change scenarios and evaluation of agroadaptations

GIS Exercise: Adaptation to Climate Change (a Case Study of Thailand)

  1. Data input to GIS system (soil, land cover, rainfall)
  2. Data interpolation
  3. Work with raster and vector data
  4. Use of GIS for estimate yield for different climate scenarios
  5. Estimate possible production and cost/benefit based on the agro-adaptation techniques using GIS

Learning Outcomes

On completion of this session, the student should be able to:

  • Gain knowledge on use of crop simulation models in agriculture
  • Analyze and understand the climate change impacts on rice production using crop simulation models
  • Evaluate location specific adaptation technologies to minimize the adverse effect of climate change on rice production.
  • Use of GIS tool to identify climate related impact on rice cultivation in spatial terms

Suggested readings

Jones, J.W., and Luyten, J.C. 1998. Simulation of Biological Processes. In Robert M. Peart
and R. Bruce Curry (Eds), Agricultural Systems Modeling and Simulation. Marcel
Dekker, INC, pp:19-63.
Hunt, L.A. and Boote, K.J. 1998. Data for model operation, calibration, and evaluation. In
G. Y. Tsuji et al. (Eds.), Understanding Options for Agricultural Production. Kluwer
Academic Publishers in cooperation with International Consortium for Agricultural
Systems Applications. The Netherlands. pp. 9-40.

References

Babel M.S., Agarwal A., Swain, D.K., and Herath, S. 2011. Evaluation of climate change
impacts and adaptation measures for rice cultivation in Northeast Thailand. Climate
research, (46):137-146.
Swain D. K., and Thomas D. 2010.Climate Change Impact Assessment and Evaluation of
Agro-Adaptation Measures for Rice Production in Eastern India. Journal of
Environmental Informatics, 16(2):94-101.
Swain D. K. and Yadav A. 2009. Simulating the Impact of Climate Change on Rice Yield
Using CERES-Rice Model. Journal of Environmental Informatics, 13(2):104-110.
Krishnan P., Swain D. K., Bhaskar, B.C., Nayak S.K., and Dash R. N. 2007. Impact of
elevated CO2 and temperature on rice yield and methods of adaptation as evaluated by
crop simulation study. Agriculture, Ecosystems & Environment, 122: 233-242.
Swain D. K., Herath S., Bhaskar B.C., Krishnan P., Rao K. S., Nayak S.K., and Dash R. N.
2007. Developing ORYZA 1N for Medium- and Long-Duration Rice: Variety Selection
under Nonwaterstress Conditions. Agronomy Journal, 99: 428-440.

Dillip Swain

Associate Professor, Agricultural & Food Engineering

Dr. Dillip Kumar Swain is a actively involved in teaching and research programme of the Indian Institute of Technology Kharagpur, since his joining as Assistant Professor. Prior to joining IIT, Dr. Swain worked as Post-Doctoral Fellow at the United Nations University, Tokyo, Japan, through Japan Society for the Promotion Science Fellowship during the year 2003 to 2005. Dr. Swain teaches the subjects: Systems Approach in Agriculture, Soil-Plant-Water Relationships, and Crop Production Systems for undergraduates and postgraduate students in Agricutlural Engineering.

Lal Samarakoon

Director, Geoinformatics Center, Asian Institute of Technology (AIT), Thailand

Dr. Lal Samarakoon currently works as the Director of Geoinformatics Center of the Asian Institute of Technology, Bangkok. He has extensive working experience in Asia, Japan with AIT. His research focuses in the application of spatial analytic techniques using GIS, remote sensing, GPS in resource management for sustainable development through teaching, research, training, and real-world application.