Abstract: The AgMIP-Rice Pilot Study: Uncertainty, Reliability and Sensitivity of 13 Rice Models in Estimation of Rice Yield. (ASA, CSSA and SSSA Annual Meetings (Cincinnati, OH- Oct. 21

342-9The AgMIP-Rice Pilot Study: Uncertainty, Reliability and Sensitivity of 13 Rice Models in Estimation of Rice Yield.

Wednesday, October 24, 2012: 10:45 AM

Duke Energy Convention Center, Room 234, Level 2

Tao Li, Crop and Environmental Science Division, International Rice Research Institute, Los Banos, Philippines, Bas Bouman, Crop and Environment Science Division, International Rice Research Institute, Los Banos, Philippines, Toshihiro Hasegawa, National Institute for Agro-Environmental Sciences NIAES, Tsukuba Ibaraki, JAPAN, Xinyou Yin, Centre for Crop Systems Analysis (CSA), Wageningen, Netherlands, Yan Zhu, National Engineering and Technology Center for Information Agriculture, Nanjing Agriculture University, Nanjing, China, Upendra Singh, Research and Development Division, International Fertilizer Development Center (IFDC), Muscle Shoals, AL and Kenneth J. Boote, Agronomy, Univeristy of Florida, Gainesville, FL

Zvi Hochman, CSIRO Ecosystem Sciences EcoSciences, Precinct 41 Boggo Rd, Dutton Park, QLD 4102, Australia;

Françoise Ruget, Institute National de Recherce Agronomique, France;

Roberto Confalonieri, University of Milan-Italy;

Hiroe Yoshida and Hiroshi Nakagawa, National Agriculture and Food Research Organization, Tsukuba, Japan;

Tamon Fumoto, National Institute for Agro-Environmental Sciences, Tsukuba, Japan;

Philippe Oriol, CIRAD, UMR AGAP, Montpellier, F-34398, France;

Fulu Tao, Institute of Geographical Sciences and Natural Resources Research, No.11A, Chaoyang District, Beijing 100101, China;

Alex C. Ruane,NASA Goddard Institute for Space Studies, New York, USA.

Abstract: The Agricultural Model Intercomparison and Improvement Project – AgMIP (www.agmip.org) aims to build a transdisciplinary modelling framework to provide more robust estimates of climate impacts on crop yields and agricultural trade, including estimates of associated uncertainties. In the AgMIP-Rice Pilot Study, 13 rice crop simulation models were tested with quality-assessed field experimental data from four contrasting environments from China, India, Japan and Philippines. With minimal information provided on crop growth and without crop parameter calibration, the uncertainties of the rice models to estimate rice grain yield were evaluated. Next, all models were calibrated and validated against the field-experimental data. With the calibrated crop parameters, a standardized sensitivity analysis to a range of changes on temperature, atmospheric CO₂ concentration and nitrogen fertilizer application rate was carried out with each model in the selected four sentinel datasets. Results from the model intercomparison will be presented. The reliabilities for model to estimate the rice yield, the implications for model applications to climate change and global food security studies, and the options for model improvement are discussed.

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