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Evaluation of the CERES-Rice version 3.0 model for the climate conditions of the state of Kerala, India

Published online by Cambridge University Press:  04 April 2001

S.A. Saseendran ,
K.K. Singh ,
L.S. Rathore ,
G.S.L.H.V.P. Rao ,
Nisha Mendiratta ,
K. Lakshmi Narayan  and
S.V. Singh
S.A. Saseendran
Affiliation:
National Centre for Medium Range Weather Forecasting, Department of Science and Technology, Mausam Bhawan, New Delhi-110003, India
K.K. Singh
Affiliation:
National Centre for Medium Range Weather Forecasting, Department of Science and Technology, Mausam Bhawan, New Delhi-110003, India
L.S. Rathore
Affiliation:
National Centre for Medium Range Weather Forecasting, Department of Science and Technology, Mausam Bhawan, New Delhi-110003, India
G.S.L.H.V.P. Rao
Affiliation:
Regional Research Station, Pilicode, Kerala Agricultural University, India
Nisha Mendiratta
Affiliation:
National Centre for Medium Range Weather Forecasting, Department of Science and Technology, Mausam Bhawan, New Delhi-110003, India
K. Lakshmi Narayan
Affiliation:
National Centre for Medium Range Weather Forecasting, Department of Science and Technology, Mausam Bhawan, New Delhi-110003, India
S.V. Singh
Affiliation:
National Centre for Medium Range Weather Forecasting, Department of Science and Technology, Mausam Bhawan, New Delhi-110003, India
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Abstract

The CERES-Rice version 3.0 crop growth simulation model was calibrated and evaluated for the agroclimatic conditions of the state of Kerala in India. Genetic coefficients were developed for the rice crop variety Jaya and used for the model evaluation studies. In four experiments using different transplanting dates during the virippu season (June to September) under rainfed conditions (i.e. no irrigation), the flowering date was predicted within an error of four days and date of crop maturity within an error of two days. The model was found to predict the phenological events of the crop fairly well. The grain yield predicted by the model was within an error of 3% for all the transplanting dates, but the straw yield prediction was within an error of 27%. The high accuracy of the grain yield prediction showed the ability of the model to simulate the growth of the crop in the agroclimatic conditions of Kerala. It can be concluded from this study that the model can be used for making various strategic and tactical decisions related to agricultural planning in the state.

Type
Research Article
Information
Meteorological Applications , Volume 5 , Issue 4 , December 1998 , pp. 385 - 392
Copyright
© 1998 Meteorological Society

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