پیش‌بینی فصلی به روش تلفیقی بازنمونه‌گیری k-نزدیک‌ترین همسایه و مدل CERES-Wheat در کشت گندم دیم

نوع مقاله: مقاله پژوهشی

نویسندگان

1 عضو هیئت علمی، سازمان تحقیقات ل، آموزش و ترویج کشاورزی، مزکز تحقیقات و آموزش کشاورزی خوزستان

2 مرکز ملی اقلیم شناسی مشهد

3 دانشجوی کارشناسی ارشد امنیت سایبری، دانشگاه اصفهان

چکیده

اطلاع از شرایط آب و هوایی فصل پیش رو امکان اتخاذ راهبردهای مدیریتی متناسب در مزرعه را فراهم ساخته و در کاهش هزینه‌ها و ریسک تولید نقش مهمی ایفا نماید. در این مطالعه، به منظور پیش‌بینی فصلی عوامل جوی و انتخاب دو گزینه مدیریت زراعی (تاریخ کاشت و مصرف نیتروژن) برای فصل آتی در شهرستان ایذه در استان خوزستان، از روش  kنزدیک‌ترین همسایه (k-NN) اصلاح شده و مدل شبیه‌ساز رشد و نمو گندم CERES-Wheat استفاده شد. نتایج نشان داد که روش k-NN برای پیش‌بینی شرایط آب و هوایی و مدل CERES-Wheat جهت شبیه‌سازی عملکرد گندم از دقت مناسبی برخوردارند. از تلفیق روش پیش‌بینی فصلی k-NN با مدل CERES-Wheat تاریخ کاشت مناسب گندم دیم در منطقه مطالعاتی، بین 5 آبان تا اوایل آذر تعیین شد. مقدار نیتروژن مصرفی در سال‌های کم‌باران و سال‌های نرمال به ترتیب 50 و 150 کیلوگرم در هکتار پیشنهاد می‌گردد. این رهیافت می‌تواند به عنوان یک ابزار پشتیبان تصمیم در مدیریت زراعت دیم پیش از آغاز سال فصل زراعی در سایر مناطق اقلیمی مورد استفاده قرار گیرد.

کلیدواژه‌ها


عنوان مقاله [English]

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

نویسندگان [English]

  • S. B. Andarzian 1
  • I. Babaeian 2
  • S. B. Andarzian 3
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
چکیده [English]

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.

کلیدواژه‌ها [English]

  • Crop models
  • Dry-land Farming
  • Global warming
  • seasonal forecasting
  • Wheat

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