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تخمین تبخیرتعرق واقعی با استفاده از تصاویر سنجندههای MODIS و ETM+ در اراک | ||
| تحقیقات آب و خاک ایران | ||
| مقاله 13، دوره 51، شماره 3، خرداد 1399، صفحه 697-712 اصل مقاله (1.32 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2019.289239.668317 | ||
| نویسندگان | ||
| بهاره بهمن آبادی1؛ عباس کاویانی* 2 | ||
| 1دانشجوی دوره دکتری آبیاری و زهکشی، گروه علوم و مهندسی آب، دانشکده کشاورزی و منابع طبیعی، دانشگاه بین المللی امام خمینی(ره)، قزوین، ایران | ||
| 2استادیار، گروه علوم و مهندسی آب، دانشکده کشاورزی و منابع طبیعی، دانشگاه بین المللی امام خمینی(ره)، قزوین، ایران | ||
| چکیده | ||
| در این تحقیق به بررسی توزیع مکانی تبخیرتعرق و رابطه آن با سنجش از دور در مقابل دادههای لایسیمتری به عنوان شاهد در شهرستان اراک واقع در استان مرکزی در ایران پرداخته شده است. در برآورد مقدار تبخیرتعرق واقعی براساس مدلهای SEBAL، SSEB و TSEB در منطقه از 28 تصویر از سنجندههای MODISو سنجنده + ETM در طی سالهای1380 تا 1383 استفاده شد. تعدد تصاویر MODIS وقدرت تفکیک زمانی مناسب آن، دلیلی بر میزان خطای کمتر در برآورد تبخیرتعرق مرجع است. طبق نتایج آماری از میان سه مدل مورد بررسی، مدل SEBALبا کمترین میزان RMSE در هر دو سنجنده MODIS وETM+ (97/0و 38/1میلیمتر بر روز) بهعنوان مدل برتر در منطقه معرفی شد و مدل TSEBضعیفترین عملکرد را در هر دو سنجنده MODISوETM+ داشته است (mm/day 57/3 و 53/2RMSE=). در مقایسه عملکرد دو سنجنده، سنجنده ETM+ماهواره لندست7 به دلیل قدرت تفکیک مکانی بالاتر، برای برآورد تبخیرتعرق توصیه میشود. علاوه بر این در بررسی پوشش گیاهی، بر اساس شاخص گیاهی NDVI، در ابتدای دوره کشت به دلیل جوانهزنی و تنک بودن پوشش گیاهی، این شاخص در پایینترین حد خود قرار دارد و بهترتیب با افزایش دمای هوا و پوشش گیاهی، شاخص NDVI رو به افزایش است. فاکتور L اهمیت بهسزایی در برآورد SAVI و در نهایت، برآورد تبخیرتعرق برای منطقه مورد مطالعه دارد که به پوشش منطقه وابسته است. در این تحقیق برای منطقه مورد مطالعه در دوره رشد حداکثری گیاه، مقدار6/0 L= تخمین زده شد که در برابر دیگر مقادیر مورد بررسی، دارای کمترین مقدار خطا بود. | ||
| کلیدواژه‌ها | ||
| SEBAL؛ ETM+؛ MODIS؛ SAVI؛ NDVI | ||
| عنوان مقاله [English] | ||
| Actual Evapotranspiration Estimation Using MODIS and ETM+ Imageries (Case Study: Arak) | ||
| نویسندگان [English] | ||
| Bahareh Bahman Abadi1؛ Abbas Kaviani2 | ||
| 1Ph.D student candidate in irrigation and drainage, Dept. of Water Sciences and Engineering, Faculty of Agricultural and Natural Resources, Imam Khomeini International University, Qazvin, Iran | ||
| 2Assistant Professor, Department of Water Engineering, Faculty of Agricultural and Natural Resources, Imam Khomeini International University, Qazvin, Iran | ||
| چکیده [English] | ||
| In this research, the spatial distribution of evapotranspiration and its relationship with remote sensing in contrast with lysimetric data as control was investigated in Arak, Markazi province in Iran. For estimation of actual evapotranspiration amount in the region based on SEBAL, SSEB and TSEB algorithms, 28 imageries of MODIS and Landsat7 (ETM+) were used for the years of 2000-2004. The multiplicity of MODIS images and its high temporal resolution is the reason of least error for ET estimation. According to the statistical results, the SEBAL model with the lowest RMSE in both TERRA and ETM + sensors (0.97 and 1.38 mm/day) was presented as the superior model in the region. Also, TSEB model showed the weakest results among the proposed models, in both MODIS and ETM + sensors (3.57 And 2.53 mm per day). Comparing the performance of two sensors, the ETM+ satellite images are recommended for ET estimation due to increased spatial resolution and improved resolution of images in the Landsat satellite. In addition, the NDVI vegetation index was at its lowest level at the beginning of the growing period due to germination and vegetation thinness, and it is increased by increasing air temperature and vegetation cover. L factor has a significant effect on SAVI and ET estimation and it is depended on the region vegetation. In this study, the L factor for the studied area was estimated to be 0.6 during the maximum growth period, which had the least amount of error in comparison with other values. | ||
| کلیدواژه‌ها [English] | ||
| SEBAL, ETM+, MODIS, SAVI, NDVI | ||
| مراجع | ||
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Abdoli, H. Eslamian,S.S, and Abedi Koohpaei, J. (2011) The use of Landsat7 satellite images and MODIS for estimating evapotranspiration through remote sensing in irrigation management. In Proceedings of 3rd Irrigation and Drainage Network Management National Conference (IDNC201). Faculty of Irrigation Engineering, Shahid Chamran University.(In Persian) Alavi Panah, K. (2005). Remote sensing application in earth science. Tehran University press. (In Farsi) Alavi Panah, K. (2011). Principles of modern remote sensing and interpretation of stellite imageries and aerial photoes. (2nd ed) Tehran University press. (In Farsi) Allen, R. Pereira, L. Raes, D. Smith, M. (1998). Crop evapotranspiration (Guidelines for computing crop water requirements). FAO-56, Pp:300. Rome. Allen, R. Tasumi, M. and Trezza R. (2002). SEBAL (Surface Energy Balance Algorithms for Land) Advanced Training and User’s Manual—Idaho Implementation,Version 1.0. Allen, R.G. Tasumi, M. Trezza, R. (2007). Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—model. Journal of Irrigation and Drainage Engineering 133, 380–394 Bagheri M.H. Arshad, S. Majnooni, A. Morid, S. "Compression Remote Sensing Single Source and two Sources Models Energy Flux in the Real Evapotranspiration Estimate", J. Rem.Sen. GIS, 2012, Yr. 4, No. 1, Pp. 81-96, [ Persian] Bastiaanssen, W. Noordman, E. Pelgrum, H. Davids, G. Thoreson, B. Allen, R. (2005). SEBAL model with remotely sensed data to improve water-resources management under actual field conditions. Journal of Irrig. Drain. 131, 85–93 Bastiaanssen, W.G.M. (2002). SEBAL-Based Sensible and Latent Heat Fluxes in the Irrigated Gediz Basin, Turkey. Journal of Hydrology, 229, 87-100 Bastiaanssen, W.G.M. Menenti, M. Feddes, R.A. Holtslag. A.A.M. (1998). A Remote Sensing Surface Energy Balance Algorithm for Land (SEBAL), Journal of Hydrology 212-213, 198-212 Bastiaanssen, W.G.M. (1995). Regionalization of surface flux densities and moisture indicators in composite terrain. Ph.D. Wageningem Agricultural University, Wageningen, Netherlands, 273f... Bezerra, B.G. Silva, B. Santos, C. Bezerra, J. (2015). Actual Evapotranspiration Estimation Using Remote Sensing: Comparison of SEBAL and SSEB Approaches. Journal of Advances in Remote Sensing, Vol.4 (3),234-247 Binh, T.N.K.D. Vromant, N. Hung, N.T.Hens, L. Boon, E.K. (2005). "Land cover changes between 1968 and 2003 in Cai Nuoc, Ca Mau Peninsula, Vietnam" environmental change. Journal of Trends in ecology and evolution. 9(20).115-124 Delgarm. S., Rahimpoor. M, Bakhtiari. B, Sayari. N, 2015. Comparison of Transpiration Evapotranspiration by Lysimus Data and SEBAL Algorithm in Kerman Plain Using MODIS Sensor Imaging.J Soil and water research. Vol.46. p373-383 Farid Hoseini, A. Astarae, A. Sanaee Nejad, s.A. Mirhoseini Mosavi, P. (2012). Estimation of Leaf Area Index usingIRS satellite data in Neyshabur, Journal of the Agriculture of Iran. Ferdowsi University. Volume 10, Issue 3. Pages 577–582. (In Persian) French, A. Jacob, F. Anderson, M. Kustas, W. Timmermans, W. Gieske, A. Su, Z. Su, H. Mccabe, M. and Li, F. (2005). Surface energy fluxes with the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) at the Iowa 2002 SMACEX site (USA).Journal of Remote Sensing of Environment, 99: 55-65 Huete, A. R., Post, D. F. and Jackson, R. D., 1984. Soil spectral effects and 4-space vegetation discrimination. Journal of remote sensing of Environment, 15:155-165. Iqbal, M. (1983) an Introduction to Solar Radiation. Academic Press, Toronto Kustas, W.P. Anderson, M.C, Cammalleri, C. Alfieri, J.G. (2013). Utility of a Termal-base Two- source Energy Balance Model for Estimating Surface flux over Complex Landscapes. Journal of Procedia Enviromental science, 19. 224-230 Kustas, W.P. & Norman J.M. (1977). A two-source approach for estimating turbulent fluxes using multiple angle thermal infrared observations. Journal of Water Resources Research, 33: 1495-1508 Landres, G. Barredo, A.O. and Lopez, J.J. (2008). Comparison of artificial neural network models and empirical and semi_empirical equations for daily refrence evapotranspiration estimation in the Basque Country (Northern Spain). Journal of Agricaulture Management. 95:553_565 Mardikis, M.G. and Kalvivas, D.P. and Kollias, V, J. (2005). Comparison of Intepolation Methods for the prediction of reference Evapotranspiration-An Application in Greece, Journal of Water Resource Manage. 19:251-278 Mobasheri, M.R. Khavarian, H. and Moussaoui H.( 2006). Error estimates of ET from Sensible Heat in the SEBAL.National In proceedings 3rd Conference on Irrigation and Drainage network management, Shahid Chamran University, Department of Water Engineering. (In Farsi) Mosaedi, A. & Ghabaei Sough, M.( 2013). Evaluation of different empirical equations of the estimation of reference crop evapotranspiration in different conditions lacking measured meteorological parameters in some climatic regions of Iran Journal of Water and Soil Conservation. 20(3) Nishida, K. Nemani, R.R. Running, S.W. and Glassy, J.M. (2003). An operational remote sensing algorithm of land surface evaporation. Journal of geophysical research, 108: 4270 Norman, J.M, Kustas, W.P, Humes, K.S. (1995) Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature. Journal of Agricultural and Forest Meteorology 77, 263-293. Omidvar, J.( 2011). Estimation of actual evapotranspiration using ASTER imagery and metric models. Ph.D. Department of Water Engineering, Mashhad Ferdowsi University. (In Farsi) Qi, J. Chehbouni, A. Huete, A.R. Kerr,Y.H., (1994). Modified Soil Adjusted Vegetation Index (MSAVI). Journal of Remote Sens Environ 48:119-126 Rafiee,y. Alavi Panah, K. Malek Mohammadi, B. and Ramezani Mehraban, M. (2012). Producing land cover maps using remote sensing and decision tree algorithm (Case study: Bakhtegan national park and wildlife refuge).Journal of Geography and Environmental Planning .47(3).93-110 (In Farsi) Rahimian, M.H. & Poormohammadi, S.( 2012). Estimation of winter wheat actual evapotranspiration under stress condition by remote sensing data and energy balance algorithm (Case study: Azadegan plain, Khuzestan). Journal of Water Resource Agricaulture. 4: 12-28. (In Farsi) Rahmani, N. Shahedi, K, Miryaghobzadeh, M. (2011). Evaluation of vegetation indices in Remote Sensing, In proceedings of Geomatic Conference. (In Farsi) Roerink, G.J. Su, Z. and Menenti, M. (2000) S-SEBI: A Simple Remote Sensing Algorithm to Estimate the Surface Energy Balance. Physics and Chemistry of the Earth—Part B. Journal of Hydrology, Oceans and Atmosphere, 25, 147-157. Sanaei Nejad, S.H. Noori, S. and Hasheminia, S.M. (2011) .Estimation of Evapotranspiration Using Satellite Image Data in Mashhad area. Journal of Water and Soil. 25(3), 540-547. (In Farsi) Senay, G.B., Budde, M. Verdin, J.P. and Melesse, A. (2007). A Coupled Remote Sensing and Simplified Surface Energy Balance Approach to Estimate Actual Evapotranspiration from Irrigated Fields. Journal of Sensors. 7(6). 979-1000. Senay, M. Budde and J. Verdin, (2011). Enhancing the SimplifiedSurface Energy Balance (SSEB) approach for estimating landscape ET: Validation with the METRIC model," Journal of Agricultural Water Management. 98. 606–618. Stull, R.B. (1988). An Introduction to Boundary Layer Meteorology. Kluwer Academic Publishers, Boston. Tang, R. Li, Z.L, Sun, X. (2013). Temporal upscaling of instantaneous evapotranspiration: An intercomparison of four methods using eddy covariance measurements and MODIS data. Journal of Remote Sensing of Environment. 138. 102–118. Tasumi, M. Trezza, R. Allen, R.G. and Wright, J.L. (2005). Operational aspects of satellite-based energy balance models for irrigated crops in the semi-arid U.S. Journal of irrigation and drainage system. 19. 355-376. Timmermans, W.J. Kustas, W.P. Anderson, M.C. and French, A.N. (2007). An inter-comparison of the surface energy balance algorithm for land (SEBAL) and the two-source energy balance (TSEB) modeling schemes. Journal of Remote Sensing of Environment, 108: 369-384 Wenjing, L. (2006). Sattelite based Regional-Scale Evapotranspiration in the Hebi Plain, Northeastern China. MSc, Geo-Information science and Earth Observation, international institute for Geo-Information science and Earth Observation Enschede, the Netherland. Zhou, Y. Ma, Z. Wang, L. (2002). Chaotic dynamics of the flood series in the Huaihe River Basin for the last 500 years. Journal of Hydrology 258.100–110. Su, Z. (2002). The surface energy balance system (SEBS) for estimation of turbulent heat fluxes Hydrology and Earth System Sciences, 6 (1) (2002), pp. 85-89 | ||
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