برآورد عملکرد برنج و تعیین بهره‌وری آب اراضی شالیزاری با استفاده از سنجش از دور و داده‌های لایسیمتر (مورد مطالعه: شمال شهرستان ساری)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی آب- دانشکده مهندسی زراعی- دانشگاه علوم کشاورزی و منابع طبیعی ساری- استان مازندران- ایران

2 گروه مهندسی آب، دانشکده مهندسی زارعی، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری، ایران.

3 عضو هیات علمی گروه زراعت دانشگاه علوم کشاورزی و منابع طبیعی ساری

چکیده

با توجه به نقش کلیدی محصول برنج در تأمین امینت غذایی و اشتغال‌زایی در کشور، دست­یابی به اطلاعات به‌هنگام عملکرد و بهره‌وری زمین‌های شالیزاری می‌تواند راهبردهای مهمی را به‌منظور برنامه‌ریزی فعالیت‌هایی مانند برداشت، ذخیره­سازی، بازاریابی و مدیریت منابع و نهاده‌ها فراهم نماید. هدف پژوهش حاضر، برآورد عملکرد و تعیین بهره‌وری آب شالیزارهای شمال شهرستان ساری با استفاده از داده‌های ماهواره لندست 8 و لایسمتر نوع N است. به­این منظور، پس از انجام تصحیح‌های اتمسفریک و رادیومتریک تصاویر ماهواره‌ای در دوره رشد برنج، شاخص‌های گیاهی NDVI، SAVI و RGVI به دست آمد. با استفاده از این شاخص‌ها رابطه رگرسیونی مناسب با عملکرد برنج ایجاد شد. همچنین، با پایش مداوم شالیزارها و نصب لایسیمتر نوع N داده های مربوط به آب مصرفی و تبخیر- تعرق برنج اندازه‌گیری شد. در نهایت، نقشه بهره‌وری آب برنج در منطقه مورد مطالعه با تلفیق داده‌های سنجش از دور (عملکرد) و مزرعه‌ای (آب مصرفی و تبخیر-تعرق) به­دست آمد. نتایج نشان داد، شاخص‌های گیاهی در مرحله پنجه‌زنی بیشترین همبستگی را با میزان عملکرد گیاهی برنج دارند و در صورتی‌که، برآورد عملکرد با استفاده از داده‌های سنجش از دور مدنظر باشد، شاخص‌های گیاهی در مرحله پنجه‌زنی باید مورد استفاده قرار گیرد. در میان شاخص‌های گیاهی، شاخص SAVI بهترین همبستگی (94/0=r) را با عملکرد داشته و نقشه عملکرد حاصل از این شاخص گیاهی برای تهیه نقشه بهره‌وری آب بر مبنای آب مصرفی شالیزار و تبخیر- تعرق گیاه برنج مورد استفاده قرار گرفت. میانگین بهره‌وری با استفاده از شاخص SAVI، 63/0 کیلوگرم بر مترمکعب و میانگین بهره‌وری اندازه‌گیری‌شده 68/0 کیلوگرم بر مترمکعب بود. یافته‌ها نشان می‌دهد سنجش از دور حاوی اطلاعات مفیدی برای تهیه نقشه عملکرد گیاهی و بهره‌وری آب در اراضی شالیزاری بوده و از پتانسیل خوبی برای استفاده درکشاورزی دقیق و هوشمند برخوردار است.

کلیدواژه‌ها

عنوان مقاله [English]

Estimating the Rice Yield and Determining Water Productivity of Paddy Fields with Remote Sensing and Lysimeter Data (The Studied Case: North of Sari)

نویسندگان [English]

  • Fatemeh Jafari Sayadi 1
  • Mohammad Ali Gholami Sefidkouhi 2
  • Hemmatollah Pirdashti 3
  • Mojtaba Khoshravesh 2
1 Department of irrigation. Faculty of Agricultural Engineering, Sari Agricultural Sciences and Natural Resources University (SANRU), Mazandaran. Iran
2 Department of Water Engineering, Faculty of Agricultural Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
3 Scientific staff, sari agricultural sciences and natural resources University
چکیده [English]

Due to the key role of rice crops in food security and employment in Iran, access to on-time information of productivity and water productivity in paddy fields can provide important strategies for planning activities such as harvesting, storage, marketing, and management of resources and inputs. This study aimed to estimate the yield and determine water productivity of paddy fields in the north of Sari city using Landsat 8 satellite data and N type lysimeter. For this purpose, NDVI, SAVI, and RGVI indices were extracted from the images. Using these indices, a suitable regression relationship was created with rice yield. With continuous monitoring of paddy fields and installation of type N lysimeter, water consumption and evapotranspiration of rice data were measured. Finally, the study area's rice water productivity map was obtained by incorporating remote sensing data (yield) and field data (water consumption and evapotranspiration). The results showed that plant indices in the tillering stage have the highest correlation with rice crop yield, and if yield estimation using remote sensing data is considered, plant indices in tillering stage should be used. Among the plant indices, the SAVI index had the best correlation (r=0.94) with yield, and the yield map obtained from this plant index was used to prepare a water productivity map based on water consumption and rice evapotranspiration. Evapotranspiration-based water productivity map provided more realistic data than water consumption-based productivity map, so the SAVI index average productivity was 0.63 kg/m3, and the average measured productivity was 0.68 kg/m3. Findings showed that remote sensing provides useful information for mapping crop yield and water productivity in paddy fields and has good potential for precision and smart agriculture.

کلیدواژه‌ها [English]

  • Rice water consumption
  • Landsat 8
  • Vegetation indices

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