Evaluating the use of extended range forecasts in DSSAT for predicting rice yield: A case study of Madhya Pradesh, India

Authors

  • MEHNAJ THARRANUM Agromet Advisory Service Division, India Meteorological Department, New Delhi
  • D. R. PATTANAIK Numerical Weather Prediction Division, India Meteorological Department, New Delhi
  • K. K. SINGH Agromet Advisory Service Division, India Meteorological Department, New Delhi
  • SHESHAKUMAR GOROSHI Agromet Advisory Service Division, India Meteorological Department, New Delhi
  • S. K. MANIK Hydrometeorology Division, India Meteorological Department, New Delhi.

DOI:

https://doi.org/10.54386/jam.v27i3.2952

Keywords:

DSSAT, Rice, Extended range forecast (ERF), Vegetative phase, Reproductive phase, Ripening phase

Abstract

This study evaluates the potential of Extended Range Forecasts (ERFs) in improving rainfed rice yield simulations during three kharif seasons (2019–2021) using the DSSAT v4.8 model for Madhya Pradesh. Three weather datasets were evaluated: (1) observed weather, (2) observed + ERF + climatological normal and (3) observed + climatological normal. The ERF generated as weekly interval during the crop season with a total of 19 initial conditions (IC) were used for ERF dataset. The yields simulated using hybrid datasets (2 & 3) were related with those obtained with the observed weather data (1). Results indicated that integrating ERFs during the reproductive and ripening phases improves yield simulations, with the most notable improvements observed in 2021. However, benefits varied across seasons and growth phases. The findings highlight the potential of ERFs to enhance seasonal yield forecasts when applied strategically, particularly by bridging observed data and climatological normal during key crop phases.

References

Chattopadhyay, N. (2023). Advances in application of sub-seasonal weather forecast in Indian agriculture. J. Agrometeorol., 25(1): 34–41. https://doi.org/10.54386/jam.v25i1.2047

GoI. (2024). “Agricultural Statistics at a Glance 2023”. Ministry of Agriculture & Farmers Welfare Department of Agriculture, Cooperation & Farmers Welfare. Directorate of Economics and Statistics. pp.29.

Harinarayanan M.N., Manivannan. V., Dheebakaran, Ga. and Guna. M. (2022). Usability of monthly ERFS (Extended Range Forecast System) to predict maize yield using DSSAT model over Erode District of Tamil Nadu. J. Appl. Natural Sci., 14(SI): 244-250.

IMD. (2014). “A manual for crop yield forecasting by statistical model”. Agricultural Meteorology Division, India Meteorological Department, Shivajinagar, Pune. Ministry of Earth Sciences. pp.1.

Pattanaik, D.R., Alone, A., Kumar, P. Phani, M, K., Mandal, Raju and Dey, Avijit. (2022). Extended-range forecast of monsoon at smaller spatial domains over India for application in agriculture. Theor. Appl. Climatol. 147: 451–472.

Sahai, A. K., Chattopadhyay, R., Joseph, S., Mandal, R., Dey, A., Abhilash, S., Krishna, R. P. M., & Borah, N. (2015). Real-time performance of a multi-model ensemble-based extended range forecast system in predicting the 2014 monsoon season based on NCEP-CFSv2. Current Sci., 109(10): 1802–1813.

Sahai, A.K., Sharmila, S., Abhilash, S., Chattopadhyay, R., Borah, N., Krishna, R.P.M., Joseph, S., Roxy, M., De, S., Pattnaik, S., Pillai, P.A. (2013). Simulation and extended range prediction of monsoon intraseasonal oscillations in NCEP CFS/GFS version 2 framework. Current Sci., 104(10):1394–1408.

Sahu, V.N., Sahu, R.K. and Shrivastava, M.N. (1985). IR 36 for rainfed conditions in Madhya Pradesh, India. Intern. Rice Res. Newsletter (Philippines). 10(5):6

Singh, K.K., Baxla, A.K., Chaudhary, J.L., Kaushik, S and Gupta, A. (2005). Exploring the possibility of second crop in Bastar Plateau region of Chhattisgarh using DSSAT crop simulation model. J. Agrometeorol., 7(2):149-160. https://doi.org/10.54386/jam.v7i2.834

Singh, P. (2023). Crop models for assessing impact and adaptation options under climate change. J. Agrometeorol., 25(1): 18–33. https://doi.org/10.54386/jam.v25i1.1969

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Published

01-09-2025

How to Cite

THARRANUM , M., PATTANAIK, D. R., SINGH, K. K., GOROSHI, S., & S. K. MANIK. (2025). Evaluating the use of extended range forecasts in DSSAT for predicting rice yield: A case study of Madhya Pradesh, India. Journal of Agrometeorology, 27(3), 286–291. https://doi.org/10.54386/jam.v27i3.2952

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