نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجوی دکتری اکولوژی گیاهان زراعی، گروه زراعت و اصلاح نباتات، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج
2 استاد، گروه زراعت و اصلاح نباتات، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج
3 استاد، گروه مهندسی علوم خاک، دانشکدۀ مهندسی و فناوری کشاورزی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج
4 دانشیار، گروه اقتصاد کشاورزی، دانشکدۀ اقتصاد و توسعۀ کشاورزی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
The AquaCrop model has been used for optimum sowing date determination for maximum yield production based on historical climate data in Moghan plain, Ardabil province, Iran. Based on phonological data for the eight main cultivated crop gathering from Moghan plain and thirty years climate data, the optimum sowing dates were determined after model calibration. The model used cumulative growing degree days, effective and active base temperature and calculated harvest index to perform each crop yield. Determination coefficient, normalized root mean squared and index of agreement were 0.99, 29.16 and 0.97 respectively. The statistics showed that the model could accurately perform the crop yield estimation in this region. Based on the results the simulated sowing window for winter wheat was a little bit shorter. The winter barley also performed as winter wheat. The spring maize simulated sowing window was longer than usual period. But the simulated sowing window for winter canola, cotton, soybean and maize was the same as actual sowing window. The net Irrigation requirement in the determined planting dates have been calculated by the AquaCrop and compared with the NETWAT software outputs. In this Comparison, determination coefficient, normalized root mean squared and index of agreement were 0.92, 14.07 and 0.99 respectively. The results showed the importance of using winter precipitation in crop production in the region and lower water irrigating input using winter cultivation should be noted.
کلیدواژهها [English]