كاربرد الگوريتم بيلان انرژي (SUTSEBAL) در تخمين ميزان آب مصرفي در دشت ورامين

APPLICATION OF THE ENERGY BALANCE ALGORITHM (SUTSEBAL) FOR ESTIMATING THE AMOUNT OF WATER USED IN THE VARAMIN PLAIN

در ايران با توجه به شرايط اقليمي خشك و نيمه‌ خشك، مديريت تامين و مصرف آب نقش اساسي در توليد بهينه به‌عهده دارد. تبخير و تعرق يكي از فرآيندهاي اساسي چرخه‌ي هيدرولوژيكي است كه معادل مجموع آب خالص مصرفي گياهان براي رشد و تبخير از سطح زمين هاي كشاورزي است. الگوريتم بيلان انرژي در سطح زمين (SEBAL)، مدلي با پايه‌ي ترموديناميك است كه با كاربرد آن در حوزه هاي بزرگ مي توان تبخير و تعرق واقعي را تخمين زد. در اين نوشتار، ضمن توسعه و به‌كارگيري يك مدل بيلان انرژي با عنوان الگوريتم SUTSEBAL، آب خالص مصرفي در بخش كشاورزي در دشت ورامين تخمين زده شده است. نتايج به‌دست‌آمده نشان مي دهد كه اين الگوريتم قادر است با دقت بسيار مناسبي ميزان آب خالص مصرفي در بخش كشاورزي را با قدرت تفكيك مكاني 1 كيلومتر و در بازه‌ي زماني دلخواه تخمين بزند. هم چنين از نتايج به‌دست‌آمده مي توان براي كاليبره‌كردن مدل هاي شبيه‌ساز هيدرولوژيكي مانند MODFLOW بهره گرفت .

Estimation of evapotranspiration (ET) is needed for many applications in diverse disciplines, such as meteorology, hydrology and agriculture. Quantifying ET from irrigated projects is important for water rights management, water resources planning, water regulation and irrigation system performance. A common way of describing irrigation system performance is by comparing water supply and demand. Estimation of water supply is a straightforward exercise in most cases. However, estimation of water demand has proved to be much more difficult. Data are required on irrigated areas, types of crop, cropping calendars and specific crop water demand. Given these data, it becomes possible to calculate the total crop water requirements for each system. However, estimation of water demand proves to be more difficult, due to the absence of data on irrigated areas and cropping patterns. Remote Sensing (RS) algorithms are currently used to spatially estimate surface energy fluxes, e.g., evapotranspiration. Many of these energy balance models use information derived from satellite imagery, such as MODIS, AVHRR, and Landsat, to estimate regional ET. The RS approach to estimate ET provides advantages over traditional methods. One of the most important advantages is that it can provide regional estimates of actual ET at low cost. Compared with traditional point measurement methods (e.g., lysimeters and weather station data), this approach captures the spatial variability between and within agricultural fields. The Surface Energy Balance Algorithm for Land (SEBAL) is an image processing model for calculating ET as a residual of the surface energy balance, which was developed in the Netherlands by Bastiaanssen. In this paper, a new algorithms was developed to use synopthic weather station data in large areas faced with lack of data, into a surface energy balance, coupled with remote sensing satellite-based mutispectral images, AVHRR, called, the Sharif University of Technology SUT-SEBAL, built on the same theoretical basis as its predecessor, SEBAL, to estimate spatial ET and actual water use in agriculture in the Varamin Plain (South of Tehran), from 2002-2005. The results show that agricultural water use in this irrigation system is around 400 MCM annually. Their results were comparable with conventional methods, including CROPWAT. The results also can be used for accurately estimating ET for large populations of field and water users, and to quantify net ground-water pumpage in this area, since water extraction from underground is not measured. ET estimates that satellite images using SUT-SEBAL may ultimately replace current procedures used by the Tehran Water Company and other management entities that rely on field visits and simple ground measurements.