نوع مقاله : مقاله پژوهشی

نویسندگان

• امیر نورجو ¹
• فرید فیض‌اله‌پور ²

¹ استادیار بخش تحقیقات فنی و مهندسی کشاورزی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان آذربایجان غربی، سازمان تحقیقات، آموزش

² گروه مهندسی آب، دانشکده کشاورزی، دانشگاه ارومیه، ارومیه، ایران

چکیده

با توجه به محدودیت کمی و کیفی آب، مدیریت و تحویل حجمی آب در شبکه‌های آبیاری و زهکشی امری مهم محسوب می‌شود. برای دستیابی به این هدف، الگوی کشت شبکه آبیاری و زهکشی مهاباد با استفاده از تصاویر ماهواره‌ای سنتینل 2 و روش طبقه‌بندی ماشین بردار پشتیبان برای سال زراعی 98-97 استخراج گردید. همچنین، با استفاده از داده‌های هواشناسی ایستگاه مهاباد و معادله پنمن‌مانتیث، حجم خالص آب مورد نیاز گیاهان غالب در محل نقاط تحویل حجمی محاسبه گردید. برای تعیین میزان تبخیر-تعرق واقعی، از تصاویر ماهواره‌ای لندست 8 و الگوریتم سبال استفاده شد و در نهایت نقشه‌های مکانی تبخیر-تعرق واقعی و نیاز خالص آبیاری برای شبکه استخراج گردید. بر اساس نتایج حاصل، 64 درصد از اراضی کشت شده (6786 هکتار) شبکه مهاباد به‌صورت باغی و 36 درصد از اراضی (3808 هکتار) به‌صورت زراعی به دست آمد. بدین ترتیب، نیاز خالص آبیاری (تبخیر و تعرق محاسباتی با کسر بارش موثر)برابر با 71 میلیون مترمکعب و نیاز ناخالص آبیاری با لحاظ راندمان آبیاری 44 درصد، برابر با 36/161 میلیون مترمکعب محاسبه گردید. همچنین، کل میزان تبخیر-تعرق حاصل از الگوریتم سبال برابر با 78/79 میلیون متر محاسبه گردید. بر اساس نقشه‌های کاربری اراضی، نیاز خالص آبیاری و تبخیر-تعرق واقعی، نحوه برداشت آب در شبکه مورد بررسی قرار گرفته و مشاهده شد که در اراضی بالادست شبکه و مجاور رودخانه مهاباد، نیاز آبی گیاهان برطرف شده ولی مناطق پایین‌دست شبکه، به علت عدم دسترسی به آب کافی، دچار تنش آبیاری شده‌اند.

کلیدواژه‌ها

• الگوی کشت
• چرخه فنولوژی گیاهی
• سبال
• کم آبیاری
• ماشین بردار پشتیبان

موضوعات

• منابع و مصارف آب

عنوان مقاله [English]

Estimation of crop water requirement and actual evapotranspiration using satellite images to improve volumetric water delivery in irrigation and drainage networks (case study: Mahabad irrigation and drainage network, West Azerbaijan province

نویسندگان [English]

• amir nourjou ¹
• Farid Feizolahpour ²

¹ Agricultural Engineering Research Department, West Azarbaijan Agricultural and Natural Resources Research and Education Center, AREEO, Urmia, Iran

² Department of Water Engineering, Faculty of Agriculture, Urmia University, Urmia, Iran Email: farid.feizolahpour@gmail.com

چکیده [English]

Due to the location of Iran in arid and semi-arid regions and according to the quantitative and qualitative limitations of water resources, optimal management and volumetric delivery of water is important in irrigation and drainage networks. In this regard, it is necessary to estimate the water requirement of crops accurately and provide adequate water to farmers. Remote sensing technology provides facilities that can be used to obtain different layers of information at the lowest cost in the fastest time. Accordingly, many researchers have used remote sensing data to monitor vegetation cover, provide land use maps, estimate crop evapotranspiration and have declared this technology as appropriate tool for such studies. Based on the previous studies, it is observed that low researches has been conducted to investigate the crop evapotranspiration considering the crop water requirement. Therefore, the most important objectives of this study are: provide the cropping pattern and land use maps using Sentinel 2 satellite images, determination of the water requirement for the delivery points of irrigation network, determination of the actual evapotranspiration of the crop cover using SEBAL algorithm and Landsat 8’s images and finally evaluation of the water supply and management in the Mahabad irrigation and drainage network.

In order to determine the cropping pattern of the Mahabad irrigation and drainage network, Sentinel 2 images have been used related to the 2018-2019 crop year. The images were examined in terms of the region of syudy and the percentage of cloudiness and after selecting the appropriate images, pre-processing operations including radiometric and atmospheric corrections were applied on them. Then, the NDVI index was calculated based on selected images. On the other hand, after determination of the classification classes, the phenological cycle of crops were examined for each class and spectral pattern of crops was determined during the growing season. Training samples were selected for supervised classification using the existing maps, Google Earth images, creating images with false color composites and considering the growth pattern and some of them were also considered for validation of the classified map. Then, the cropping pattern map was obtained by using the SVM classification algorithm. After generating the crop classification map, the water requirement of the different classes was determined based on the Penman-Montith evapotranspiration method, applying plant coefficients and irrigation application efficiency at the volumetric water delivery points. Finally, the actual evapotranspiration rate of the study area calculated based on the SEBAL algorithm and compared with the net water requirement map.

Based on the results, kappa coefficient and overall accuracy of the classified map were determined to be 0.953 and 91%, respectively. The area of the planted agricultural farms was equal to 10594 hectares and 1576 hectares of farms were without planting. The area of orchard farms was equal to 6786 hectares and the area of sugar beet, wheat, alfalfa and corn lands were obtained to 998, 1839, 693 and 278 hectares, respectively. Thus, the net irrigation water requirement was equal to 71 million cubic meters and the gross irrigation water requirement was calculated equal to 161.36 million cubic meters, considering the irrigation efficiency of 44%. On the other hand, the evaluation of the SEBAL evapotranspiration maps during the growing season indicated that the total amount of evapotranspiration was equal to 79.78 million cubic meters, and this amount was 14% higher than the net irrigation water requirement. Finally, according to the crop classification map and based on the comparison of the net irrigation water requirement and evapotranspiration maps, the water consumption in the Mahabad irrigation and drainage network was evaluated. It turned out that in the upstream farms of the network or close to the Mahabad River, the Water consumption was more than net water requirement and downstream areas were faced to deficit irrigation due to lack of sufficient water.

Finally, based on the results of this study, it was observed that by using the capabilities of satellite images and remote sensing, it is possible to monitor and evaluate the condition of agricultural farms on a large scale with acceptable accuracy. Also it is possible to improve the management of water supply and water use efficiency in irrigation and drainage networks by creating up-to-date land use maps, determining net and gross irrigation water requirment and comparing with actual evapotranspiration maps.

کلیدواژه‌ها [English]

• Crop Pattern
• Plant Phenology Cycle
• SEBAL
• Deficit Irrigation
• Support Vector Machine