تعیین نیاز آبی محصولات ذرت علوفه ای و چغندرقند با استفاده از سنجش از دور (مطالعه موردی دشت قزوین)
محورهای موضوعی : مدیریت آب در مزرعه با هدف بهبود شاخص های مدیریتی آبیاریحمیده نوری 1 , علی مختاری 2 , علیرضا بادیه نشین 3
1 - استاد دانشگاه/دانشگاه تهران
2 - استان البرز، کرج، چهار راه دانشکده، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، گروه مهندسی آبیاری و آبادانی
3 - گروه آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران. آدرس: استان البرز، کرج، چهار راه دانشکده، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، گروه مهندسی آبیاری و آبادانی
کلید واژه: پرستلی-تیلور, مدل SWAP, تبخیر-تعرق پتانسیل, ضریب گیاهی, شاخص گیاهی ماهواره‌ای,
چکیده مقاله :
ب در این تحقیق، منحنی‌های ضرایب گیاهی برای دو گیاه ذرت علوفه‌ای و چغندرقند با استفاده از دو روش مبتنی بر سنجش از دور شامل نسبت 〖"ET" 〗_"P" به 〖"ET" 〗_"0" (روش نسبت‌ها) و شاخص‌های گیاهی حاصل از تصاویر ماهواره‌ای سنجنده های مادیس و لندست 8 (OLI) و لندست 7 (ETM+) استخراج گردید. در روش نسبت‌ها، ضرایب گیاهی پایه ("K" _"cb" ) و تک جزئی ("K" _"c" ) به ترتیب مستقیماً از نسبت تعرق پتانسیل ("T" _"P" ) (مدل SWAP) و 〖"ET" 〗_"P" (مدل SWAP و معادله پرستلی-تیلور) به 〖"ET" 〗_"0" به دست آمد. منحنی ضرایب گیاهی حاصل از روش‌های فوق با استفاده از منحنی‌های شاخص سطح برگ که در سال زراعی 2012 با عملیات میدانی برداشت شده بود مورد ارزیابی قرار گرفتند. "K" _"cb" حاصل از روش شاخص‌های گیاهی انطباق مناسبی با روند واقعی رشد گیاه داشت ولی این روش در برآورد منحنی "K" _"c" محدود به مقادیر ارائه شده در فائو 56 بود که روش پرستلی-تیلور با محاسبه مستقیم "K" _"c" از روش نسبت‌ها و استفاده از باند حرارتی ماهواره‌های لندست روند منطبق‌تری با واقعیت برای "K" _"c" نشان داد. به طور کلی با تدقیق منحنی ضریب گیاهی، برنامه‌ریزی آبیاری در طی دوره رشد گیاه با دقت بالاتری انجام می‌گیرد.
In this study, Kc curves of early- and late-planted fodder maize and sugar beet were obtained based on two main satellite-based methods: (1) ratio approach (2) vegetation indices (VIs) approach. In the ratio approach, basal crop coefficient (Kcb) and single crop coefficient (Kc) was directly calculated from the ratio of potential transpiration (Tp) to ET0 (using SWAP) and ETp to ET0 (using SWAP and the Priestly-Taylor equation), respectively. The VI approach makes use of Landsat 7 (ETM+) and 8 (OLI) and also MODIS imagery in order to extract soil adjusted vegetation index (SAVI). The Kcb curves were evaluated against field measured leaf area index (LAI) in 2012 growing season. After each Kc curve was modeled, net irrigation requirement (NIR) was calculated on daily and season basis. Results showed that the SWAP approach was weak in estimating the Kcb and Kc curves especially at late-season stage. The VI approach could properly detect changes in vegetation cover during an entire growing season. But, when it came to Kc curve modelling, the VI approach was limited to the values given in FAO 56. However, the Priestly-Taylor approach compensated for the aforesaid limitation; therefore, yielded more sensible trends in Kc curves. Therefore satellite-based approaches derived from more realistic Kc curves during the entire growing season. Overall, making use of the satellite-based approaches could improve water management on regional scales.
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