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ارزیابی دقت برآورد مکانی تبخیر-تعرق با الگوریتم SEBS در منطقه‌ی کوهستانی خشک، جنوب ایران | ||
| پژوهش های آبخیزداری | ||
| مقاله 8، دوره 31، شماره 3 - شماره پیاپی 120، مهر 1397، صفحه 91-107 اصل مقاله (1.1 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/wmej.2018.122097.1122 | ||
| نویسندگان | ||
| مریم زارع1؛ ام البنین بذرافشان* 2؛ مجتبی پاک پرور3؛ غلامرضا قهاری3 | ||
| 1دانشجوی دکتری تخصصی علوم و مهندسی آبخیزداری، دانشگاه هرمزگان، دانشکده کشاورزی، بندرعباس، ایران | ||
| 2استادیار دانشگاه هرمزگان، دانشکده‌ی کشاورزی و منابع‌طبیعی، بندرعباس، ایران | ||
| 3استادیار بخش تحقیقات حفاظت خاک و آبخیزداری، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی سازمان تحقیقات آموزش و ترویج کشاورزی، شیراز، ایران | ||
| چکیده | ||
| مقدار واقعی ﺗﺒﺨﻴﺮ-ﺗﻌﺮق از سطح حوضه‌ی آبخیز، یکی از عوامل اصلی در دوره‌ی آب‌شناسی و از اجزای مهم معادله‌ی تراز آب است که بخش عمده‌ای از جریان‌های خروجی حوضه یا هر مقیاس دیگری است. اندازه‌گیری مقدار واقعی ﺗﺒﺨﻴﺮ-ﺗﻌﺮق از دشواری‌های بررسی‌های تراز آب است، چراکه ﺑﻪﻋﻠﺖ نقطه‌ای ﺑﻮدن اﻃﻼﻋﺎت ﻫﻮاﺷﻨﺎﺳﻲ و دشواری تعیین ضریب گیاهی، دﻗﺖ اﺳﺘﻔﺎده از شبیه‌های ﻣﺮﺳﻮم در ﺑـﺮآورد پهنه‌ای ﺗﺒﺨﻴـﺮ-ﺗﻌﺮق واﻗﻌﻲ کم است. در این پژوهش با استفاده از نُه تصویر ماهواره‌ی لندست 8، داده‌های هواشناسی ایستگاه کِلِستان و شبیه SEBS تبخیر-تعرق دوره‌ی زمانی 1393 تا 1396 در منطقه‌ی کلستان در شمال‌غربی شیراز محاسبه، و نتایج آن با معادله‌ی ﻓﺎﺋﻮ ﭘﻨﻤﻦ-ﻣﺎﻧﺘﯿس مقایسه شد تا درستی این شبیه در این منطقه بررسی شود. پرونده‌های تشعشع مورد نیاز SEBS با استفاده از شناسه‌ی دستوری R.sun در نرم‌افزار گراس-جی‌آی‌اس تولید، و دیگر داده‌های سنجش‌ازدور در محیط الویس محاسبه شدند. نتایج تبخیر-تعرق به‌دست‌آمده از شبیه SEBS در مقایسه با معادله‌ی یادشده ازلحاظ آماری ضریب همبستگی ۹۹۳/۰ را نشان داد. تغییرات مقادیر تبخیر-تعرق واقعی در کاربری‌های مختلف در محدوده‌ا‌ی پذیرفتنی بود. تولید اطلاعات پهنه‌ای مطمئن از تبخیر-تعرق از مزیت‌های برجسته‌ی کاربرد این شبیه در بررسی‌های آب‌شناسی حوضه است. | ||
| کلیدواژه‌ها | ||
| الگوریتم SEBS؛ تبخیر-تعرق واقعی؛ تصاویر لندست 8؛ روندیابی مکانی | ||
| عنوان مقاله [English] | ||
| Evaluation of Spatial Evapotranspiration Estimation by the SEBS Model in a Dry Mountainous Region, Southern Iran | ||
| نویسندگان [English] | ||
| Maryam Zare1؛ Ommolbanin Bazrafshan2؛ Mojtaba Pakparvar3؛ Gholamreza Ghahari3 | ||
| 1Ph.D. Student of Watershed Management, University of Hormozgan | ||
| 2Assistant Professor Agriculture engineering and natural resource, University of Hormozgan | ||
| 3Assistant Professor of Soil Conservation and Watershed Management Research Department, Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Shiraz, Iran | ||
| چکیده [English] | ||
| The conventional methods for actual evapotranspiration (ETa) estimating is not sufficiently accurate due to the point based nature of meteorological data and the difficulties related to the plant coefficient (Kc) estimation. The true rate of ET from a basin is an important factor of hydrological cycle and in the water balance equation and accounts for a huge part of out-flow of a basin or any other scale. In this study, the ET values were calculated in the region of Kelestan located in the northwest of Shiraz. The SEBS evapotranspiration model was applied and evaluated by using the Landsat 8 satellite images (nine images) and the meteorological data collected at the Kelestan Station for the period 2015–2017. Results were compared to the FAO Penman-Monteith equation to verify the accuracy of this model in the region of Kelestan. The radiation sources required for the SEBS model were produced by the R.sun module in Grass-GIS. Other remote sensing data were calculated in the Ilwis software environment. The results of evapotranspiration obtained from the SEBS model in comparison with the mentioned equation showed a correlation coefficient of 0.999, which is statistically significant. Variations of the ETa for different landuses were within a reasonable range. The production of reliable data from evapotranspiration is one of the prominent advantages of using this model for application in hydrologic research of the basin. | ||
| کلیدواژه‌ها [English] | ||
| Eta, Landsat 8, SEBS model, spatial evapotranspiration | ||
| مراجع | ||
|
Aghdasi F. 2010. Crop water requirement assessment and annual planning of water allocation. University of Twente Faculty of Geo-Information and Earth Observation (ITC). Allen RG, Tasumi M, Trezza R. 2007. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)-model. ASCE Journal of Irrigation and Drainage Engineering,133(1): 380–394. Allen RG, Pruitt W, Businger J, Fritschen L, Jensen M. 1998. Chapter 4 “Evaporation and Transpiration” in ASCE Handbook of Hydrology. New York, NY, 125–252 . Allen RG, Morse A, Tasumi M. 2003. Application of SEBAL for western US water rights regulation and planning. Paper presented at the Proc. ICID Int. Workshop on Remote Sensing. Bansouleh VF, Valizadeh KH, Pirnazar M. 2015. Land surface temperature retrieval from Landsat 8 TIRS: comparison between split window algorithm and SEBAL method. Third International Conference on Remote Sensing and Geoinformation of the Environment: 953503–953503–953512. Bastiaanssen W. 1998. A remote sensing surface energy balance algorithm for land (SEBAL).: Part 2: Validation. Journal of Hydrology. 212(1): 213–229. Bastiaanssen W. 2000. SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. Journal of Hydrology. 229(1): 87–100. Bastiaanssen W, Menenti M, Feddes RA, Holtslag AAM. 1998. A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation. Journal of Hydrology, 212–213(2): 198–212. doi:http://dx.doi.org/10.1016/s0022–1694(98)00253–4. Chehbouni A, Nouvellon Y, Lhomme P, Watts C. 2001. Estimation of surface sensible heat flux using dual angle observations of radiative surface temperature. Agricultural and Forest Meteorology, 108(1): 55–65. Chen X, Su Z, Ma Y, Yang K, Wen J, Zhang Y. 2013. An improvement of roughness height parameterization of the Surface Energy Balance System (SEBS) over the Tibetan Plateau. Journal of Applied Meteorology and Climatology, 52(3): 607–622. El Tahir M, Wenzhong W, Xu C, Youjing Z, Singh V. 2012. Comparison of methods for estimation of regional actual evapotranspiration in data scarce regions: Blue Nile Region, Eastern Sudan. Journal of Hydrologic Engineering, 17(4): 578–589. doi:http://dx.doi.org/10.1061/(ASCE)HE.1943–5584.0000429. Enko T. 2009. Estimation of evapotranspiration from satellite remote sensing and meteorological data over the Fogera flood plain-Ethiopia, M.Sc. Thesis, ITC, Enschede, The Netherlands. Estévez J, Gavilán P. 2009. Sensitivity analysis of a Penman–Monteith type equation to estimate reference evapotranspiration in southern Spain. Hydrological Processes. Evapotranspiration Equation. American Society of Civil Engineers, Virginia, USA. 23(1): 3342–3353. Gong, L, Xu C, Chen D, Halldin S, Chen Y. 2006. Sensitivity of the Penman–Monteith reference evapotranspiration to key climatic variables in the Changjiang (Yangtze River) basin. Journal of Hydrology. 329(1): 620–629. Gibson L, Jarmain C, Su Z, Eckardt F. 2013. Estimating evapotranspiration using remote sensing and the surface energy balance system–A South African perspective. Water Sa, 39(4): 477–484. Han H, Yang L. 2004. Evaluation of regional scale evapotranspiration using SEBS model in western Chinese Loess Plateau. Geoscience and Remote Sensing Symposium. 2004. IGARSS'04. Proceedings. 2004. IEEE International, IEEE. Jia L, Su Z, van den Hurk B, Menenti M, Moene A, De Bruin H. 2003. Estimation of sensible heat flux using the Surface Energy Balance System (SEBS) and ATSR measurements. Physics and Chemistry of the Earth, Parts A/B/C, 28(1), 75–88. Kisi O. 2007. Eapotranspiration modelling from climatic data using a neural computing technique. Hydrological Processes, 21(14): 1925–1934. Landeras G, Ortiz-Barredo A, López J. 2008. Comparison of artificial neural network models and empirical and semi-empirical equations for daily reference evapotranspiration estimation in the Basque Country (Northern Spain). Agricultural Water Management, 95(5): 553–565. doi:http://dx.doi.org/10.1016/j.agwat. 2007.12.011. Liaqat U, Choi M. 2015. Surface energy fluxes in the Northeast Asia ecosystem: SEBS and METRIC models using Landsat satellite images. Agricultural and Forest Meteorology, 214(1): 60–79. Lu J, Li Z, Tang R, Tang B H, Wu H, Yang F, Labed J, Zhou G. 2013. Evaluating the SEBS-estimated evaporative fraction from references – 215. MODIS data for a complex underlying surface. Hydrological Processes, 27(1): 3139–3149. McCabe M, Wood E F. 2006. Scale influences on the remote estimation of evapotranspiration using multiple satellite sensors. Remote Sensing of Environment, 105(2): 271–285. Maeda E, Wiberg D, Pellikka P. 2011. Estimating reference evapotranspiration using remote sensing and empirical models in a region with limited ground data availability in Kenya. Applied Geography, 31(1): 251–258. Mahour M, Stein A, Sharifi A, Tolpekin V. 2015. Integrating super resolution mapping and SEBS modeling for evapotranspiration mapping at the field scale. Precision Agriculture, 16(5): 571–586. Menenti M, Choudhury B. 1993. Parameterization of land surface evapotranspiration using a location dependent potential evapotranspiration and surface temperature range. Proceedings of Exchange Processes at the Land Surface for a Range of Space and Time Scales, IAHS Publ, 212(1): 561–568. Mesbah H. 2014. Assessment of watershed management projects on flood mitigation in catchments, final report of research project, PROJECT NO: 01–22–22–8804–88001. (In Persian). Nandagiri L, Kovoor G. 2006. Performance evaluation of reference evapotranspiration equations across a range of Indian climates. Journal of Irrigation and Drainage Engineering, 132(3): 238–249. Norman JM, Kustas W, Humes K. 1995. Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature. Agricultural and Forest Meteorology, 77(3): 263–293. Norman J M, Kustas WP, Anderson MC. 2006. Are single-source, remotesensing surface-flux models too simple. Earth Observation for Vegetation Monitoring and Water Management, AIP Conference. Pakparvar M. 2015. Evaluation of floodwater spreading for groundwater recharge in Gareh Bygone Plain, southern Iran. Soil Management Dept., Faculty of Bioscience Engineering. Ghent, Belgium, Ghent University. PhD: 252p. Pakparvar M, Cornelis W, Pereira LS, Gabriels D, Hosseinimarandi H, Edraki M, Kowsar SA. 2014. Remote sensing estimation of actual evapotranspiration and crop coefficients for a multiple land use arid landscape of southern Iran with limited available data. J. of Hydroinformatics 16(6): 1441–1460. doi:http://dx.doi.org/10.2166/hydro.2014.140. Parlange M. 1995. Regional scale evaporation and the atmospheric boundary layer. Reviews of Geophysics, 33(1): 99–124. Pereira LS, Allen R, Smiith M, Raes D. 2015. Crop evapotranspiration estimation with FAO56: Past and future. Agricultural Water Management Proceedings, 147(1): 4–20. Raziei T, Pereira L S. 2013. Estimation of ETo with Hargreaves–Samani and FAO-PM temperature methods for a wide range of climates in Iran. Agricultural Water Management, 121(1): 1–18. doi:http://dx.doi.org/10.1016/j.agwat.2012.12.019. Roerink GJ, Su Z, Menenti M. 2000. S-Sebi: A simple remote sensing algorithm to estimate the surface energy balance. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 25(2): 147–157. Singh R, Senay G. 2015. Comparison of four different energy balance models for estimating evapotranspiration in the Midwestern United States. Water, 8(1): 9. Su z. 2002. The surface energy balance system (SEBS) for estimation of turbulent heat fluxes. Hydrology and Earth System Sciences, 6(1): 85–99. Su Z, Wang Q, Matsushita B, Fukushima T, Ouyang Z, Watanabe M. 2009. Assessing relative soil moisture with remote sensing data: theory, experimental validation, and application to drought monitoring over the North China Plain. Physics and Chemistry of the Earth, Parts A/B/C, 28(1): 89–101. Su Z, Yacob A, Wen J, Roerink G, He Y, Gao . 2003. Assessing relative soil moisture with remote sensing data: theory, experimental validation, and application to drought monitoring over the North China Plain. Physics and Chemistry of the Earth, Parts A/B/C, 28(1), 89–101. Tang R, Li Z. 2017. An improved constant evaporative fraction method for estimating daily evapotranspiration from remotely sensed instantaneous observations. Geophysical Research Letters 44(5): 2319–2326. Tabari H, Grismer M, Trajkovic S. 2013. Comparative analysis of 31 reference evapotranspiration methods under humid conditions. Irrigation Science, 31(2): 107–117. Vander Kwast J, Timmermans W, Gieske A, Su Z, Olioso A, Jia L, Elbers J, Karssenberg D, de Jong S. 2009. Evaluation of the surface energy balance system (SEBS) applied to ASTER imagery with flux-measurements at the SPARC 2004 site (Barrax, Spain). Hydrol. Earth Syst. Sci, 13(7): 1337–1347. Wagle P, Bhattarai N, Gowda P, Kakani V .2017. Performance of five surface energy balance models for estimating daily evapotranspiration in high biomass sorghum. ISPRS Journal of Photogrammetry and Remote Sensing, 128(1): 192–20. Ye J, Guo A, Sun G. 2009. Statistical analysis of reference evapotranspiration on the Tibetan Plateau. Journal of Irrigation and Drainage Engineering, 135(1): 134–140. | ||
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