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Estimating seasonal fragrant rice production in Thailand using a spatial crop modelling and weather forecasting approach

Published online by Cambridge University Press:  09 January 2020

Thewin Kaeomuangmoon ,
Attachai Jintrawet Open the ORCID record for Attachai Jintrawet [Opens in a new window] ,
Chakrit Chotamonsak ,
Upendra Singh ,
Chitnucha Buddhaboon ,
Panu Naoujanon ,
Sahaschai Kongton ,
Yasuyuki Kono  and
Gerrit Hoogenboom
Thewin Kaeomuangmoon
Affiliation:
Agricultural Systems Management Program, Center for Agricultural Resource System Research, Faculty of Agriculture, Chiang Mai University, Chiang Mai50200, Thailand
Attachai Jintrawet*
Affiliation:
Plant and Soil Sciences Department and Center for Agricultural Resource System Research, Faculty of Agriculture, Chiang Mai University, Chiang Mai50200, Thailand
Chakrit Chotamonsak
Affiliation:
Department of Geography, Faculty of Social Sciences, Chiang Mai University, Chiang Mai50200, Thailand
Upendra Singh
Affiliation:
International Fertilizer Development Center, Muscle Shoals, Alabama35662, USA
Chitnucha Buddhaboon
Affiliation:
Rice Department, Ubon Ratchathani Rice Research Center, Bureau of Rice Research and Development, Muang, Ubon Ratchathani34000, Thailand
Panu Naoujanon
Affiliation:
Geo-Informatics & Space Technology Development Agency (Public Organization), Chaeng Wattana Road, Lak SiBangkok10210, Thailand
Sahaschai Kongton
Affiliation:
Land Development Department, Ministry of Agriculture and Cooperatives, Bangkean, Bangkok, Thailand
Yasuyuki Kono
Affiliation:
Center for Southeast Asian Studies, Kyoto University, 46 Shimoadachi-cho, Yoshida, Sakyo-ku, Kyoto606-8501, Japan
Gerrit Hoogenboom
Affiliation:
Institute for Sustainable Food Systems, University of Florida, 185 Rogers Hall, PO Box 110570, Gainesville, FL32611 Gainsville, Florida, USA
*
Author for correspondence: Attachai Jintrawet, E-mail: [email protected]
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Abstract

Fragrant rice is an important export commodity of Thailand and obtaining seasonal production estimates well in advance is important for marketing and stock management. Rice4cast is a software platform that has been developed to forecast rice yield several months prior to harvesting; it links a rice model with a Minimum Data Set (MDS) and Weather Research Forecast (WRF) data. The current study aimed to parameterize and evaluate the model and to demonstrate the use of the Rice4cast platform in forecasting seasonal KDML 105 rice yield and production with local data set. The study area encompassed 77 districts in Thailand, covering 0.94 of the total area of KDML 105 in the country. Minimum Data Sets for the 2013–2015 growing seasons were used for model parameterization and evaluation. The annual statistics from the Office of Agricultural Economics (OAE) were used as a reference basis and planted areas from the Geo-Informatics and Space Technology Development Agency (GISTDA) was used for production estimation. Model evaluation showed good to fairly good agreement between the predicted and reported OAE yield. Production forecasts, however, over-estimated the OAE values considerably, primarily because of the use of GISTDA planted areas that were larger than the harvested areas in the production estimates. Adjustment of the planted areas to account for damaged areas need to be explored further. Nevertheless, the results demonstrated the capability of yield predictions with the Rice4cast, making it a valuable tool for in-season estimates for fragrant rice yield and production.

Keywords

CSM-CERES-RiceDSSATRice4castWeather Research and Forecasting modelweather variability
Type
Crops and Soils Research Paper
Information
The Journal of Agricultural Science , Volume 157 , Issue 7-8 , October 2019 , pp. 566 - 577
Copyright
Copyright © Cambridge University Press 2020

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