Integrating seasonal forecasting using K- nearest neighbor (k-NN) method and CERES-wheat model for management of rainfed wheat cultivation

Document Type : Original Article

Authors

1 Research and Education Center of Agricultural and Natural Resources of Khuzestan, Agriculture Research, Education and Extension Organization (AREEO), Ahvaz, Iran

2 Meteorology Organization, Climate Institute

3 M. Sc. Student of Cyber Security, Isfahan University, Isfahan, Iran

Abstract

Seasonal weather forecast for the upcoming season may serve as a usefool tool for making management decisions which may decrease the production costs and associated risks. In this study attemps haven been made to combine a seasonal weather forecast approach based on k-NN nearest neighbor and dynamic simulation model CERES-Wheat model as a decision support system of farm management practices (planting date and nitrogen applicatin level) for rainfed wheat (variety Dehdasht) using the data of a field experiment at Izeh research station, Khuzastan province, Iran during 2015-2016 growing season. The results showed that the k-NN approach and CERES-Wheat model have an acceptable performance in seasonal weather forecast and crop growth simulation, respectively. By combining  k-NN and CERES-Wheat models, the appropriate sowing time of the selected variety in Izeh region was determined to be between November 5 and early December. The recommended amount of applied nitrogen fertilizer in dry and rainy seasons are 50 and 150 kg ha-1, respectively. The proposed combined approach can be used as a suitable decision support system of rainfed crops in other climatic regions.

Keywords

References

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Journal of Agricultural Meteorology
Volume 6, Issue 2 - Serial Number 12
Vol. 6, No. 2, Autumn & Winter 2019
March 2019
Pages 30-43

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