مقایسه برخی روابط تجربی برآورد تبخیر- تعرق مرجع برای دشت تبریز با استفاده از لایسیمتر و ارائه مدلی برای تعیین آن از روی داده‌های هواشناسی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 استادیار، بخش تحقیقات خاک و آب، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی آذربایجان شرقی، سازمان تحقیقات، آموزش و ترویج کشاورزی، تبریز، ایران

2 استاد، گروه علوم خاک، دانشگاه تبریز

چکیده

تبخیر- تعرق گیاهان درکل به دو روش اندازه­گیری مستقیم و یا برآورد غیرمستقیم از روی داده­های هواشناسی تعیین می­شود. تعیین مستقیم تبخیر-تعرق گیاهان پرهزینه و وقت‌گیر است، لذا روش‌هائی تعیین شده‌اند که بتوان با استفاده از آنها نیاز آبی محصولات را با دقت قابل قبولی تعیین نمود. در این مطالعه تبخیر- تعرق مرجع توسط فرمول بیلان آبی خاک با استفاده از لایسیمتر برای دوره‌های 10 روزه و ماهانه در دشت تبریز تعیین گردیده و با نتایج به­دست آمده از برخی روابط تجربی مقایسه شد. نتایج نشان داد که مقدار تبخیر- تعرق مرجع (ETo) سالانه در طول 9 ماه به­طور متوسط برابر 9/1226 میلی‌متر می‌باشد. در این مدت متوسط تبخیر از تشت کلاس A (Ep)، برابر 3/1947 میلی‌متر بود. مقایسه تبخیر- تعرق اندازه‌گیری شده توسط لایسیمتر با آنچه توسط روابط مختلف تجربی بدست آمده نشان داد که روش تشت تبخیر کلاس A (99/0=R2 ) و روش هارگریوز به­ترتیب بیش‌ترین و کمترین همبستگی را با مقادیر اندازه­گیری شده توسط لایسیمتر دارند. با این وجود نزدیکترین روش به لایسیمتر از نظر شاخص‌های مورد بررسی، روش پنمن- مانتیث بود. در کل بهترین روش برای برآورد تبخیر- تعرق مرجع در دشت تبریز روش پنمن- مانتیث شناخته شد. همچنین بهترین رابطه رگرسیونی برای تعیین تبخیر- تعرق مرجع از روی داده­های هواشناسی ارائه گردید.

کلیدواژه‌ها


عنوان مقاله [English]

Comparison of Some Empirical Estimating Methods of Reference Evapotranspiration in Tabriz Plain Using Lysimeter and Proposing a Model for its Determination from Climatic Data

نویسندگان [English]

  • A Onnabi Milani 1
  • MR Neyshabouri 2
1 Assistant Prof., Soil and Water Research Department, East Azarbaijan Agricultural and Natural Resources Research and Education Center, AREEO, Tabriz, Iran
2 Prof., Soil Science Dep., Faculty of Agriculture, Univ. of Tabriz, Iran
چکیده [English]

Determining the evapotranspiration of plants is possible mainly by two methods, namely direct measuring and indirect estimation using climatic parameters. Evapotranspiration determination using direct method is difficult, costly and time consuming. For this reason, some indirect methods have been proposed for determination of crop water requirement with acceptable accuracy. A lysimetric study was conducted to determine the reference evapotranspiration (ETo) in Tabriz plain in a loamy soil. Evapotranspiration was measured in ten days and monthly intervals by water balance equation method and then compared with ETo obtained using some empirical methods. Results indicated that the average seasonal ETo and pan evaporation (Ep) for 9 months were 1226.9 and 1947.3 mm respectively. Comparison between the measured and estimated ETo by various methods showed that the pan evaporation (class A) and Hargreaves methods had the highest and lowest correlation with lysimeteric data, respectively. Based on the statistical analysis, Penman-Monteith method had the closest estimates to lysimeteric measurement. In general, Penman-Monteith was introduced as a suitable method for estimating reference evapotranspiration in Tabriz plain. Also, the best regression equation for estimating ETo using meteorological parameter was introduced.

کلیدواژه‌ها [English]

  • Climatic data
  • Empirical model
  • Lysimeter
  • Penman-Monteith
  • Reference evapotranspiration
 
Aboukhaled A, Alfaro A and Smith M, 1982. Lysimeters. FAO Irrigation and Drainage Paper. 39. FAO, Rome.
Alexandris S, Stricevic R and Petkovic S, 2008. Comparative analysis of reference evapotranspiration from the surface of rainfed grass in central Serbia, calculated with six empirical methods against the Penman–Monteith formula. European Water 21/22: 17–28.
Allen RG, Pereira LS, Raes D and Smith M, 1998. Crop Evapotranspiration – Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper. 56. FAO, Rome.
Bakhtiari B, Ghahreman N, Liaghat AM and Hoogenboom G, 2011. Evaluation of reference evapotranspiration models for a semiarid environment using lysimeter measurements. Journal of Agricultural Science and Technology 13: 223–237.
Banihabib, ME, Valipour M and Behbahani, SMR, 2012. Comparison of autoregressive static and artificial dynamic neural network for the forecasting of monthly inflow of Dez reservoir. Journal of Environmental Science and Technology 13(4): 1–14.
De Sousa Lima JR, Dantas Antonio AC, De Souza ES, Hammecker C, Lima Montenegro SMG and de Oliveira Lira CAB, 2013.    Calibration of Hargreaves-Samani equation for estimating reference evapotranspiration in Sub-humid region of Brazil. Journal of Water Resource and Protection 5: 1–5.
Djaman K, Balde AB, Sow A, Muller B, Irmak S, N’Diaye MK, Manneh B, Moukoumbi YD, Futakuchi K and Saito K, 2015. Evaluation of sixteen reference evapotranspiration methods under sahelian conditions in the Senegal River Valley. Journal of Hydrology: Regional Studies 3: 139–159.
Doorenbos H, and Pruitt WO, 1977. Guidelines for Predicting Crop Water Requirement. FAO Irrigation and Drainage Paper. 24. FAO, Rome.
Droogers P and Allen RG, 2002. Estimating reference evapotranspiration under inaccurate data conditions. Irrigation and Drainage Systems 16 (1): 33–45.
Ehteshami M, Najafi P and Sattar M, 1999. Estimating reference evapotranspiration in Isfahan region using minimum weather data set. Iranian Journal of Soil and Water Sciences 13(2): 140–147. (In Farsi)
Emdad MR, and Sabbagh Farshi AA, 2000. Selection of suitable empirical model for estimating reference evapotranspiration in Golestan (Gorgan). Iranian Journal of Soil and Water Sciences 12(10): 90–95. (In Farsi)
Igbadun HE, Mahoo HF, Tarimo AKPR and Salim BA, 2006. Performance of Two Temperature-Based Reference Evapotranspiration Models in the Mkoji Sub-Catchment in Tanzania. Agricultural Engineering International: the CIGR Ejournal. Manuscript LW 05 008. Vol. VIII.
Maeda EE, Wiberg DA and Pellikka PKE, 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.
Maulé C, Helgalson W, McGinn S and Cutforth H, 2006. Estimation of standardized reference evapotranspiration on the Canadian Prairies using simple models with limited weather data. Canadian Biosystems Engineering 48:1.1–1.11.
Onnabi Milani A. 1997. Evaluating the effect of different irrigation scheduling method for forage corn in Azarshahr. MSc Thesis, Agricultural Faculty, Tarbiat Modarres University. (In Farsi)
Saremi M, 1994. Determination of reference (grass) evapotranspiration. Agricultural Research Center of Khuzestan Province Annual Report: 26–28. (In Farsi)
Schrader F, Durnera W, Fank Johann, Gebler S, Pütz T, Hannes M and Wollschläger U, 2013. Estimating precipitation and actual evapotranspiration from precision lysimeter measurements. Procedia Environmental Sciences 19: 543–552.
Shariati M, 1993. Determining water requirement of the region (Lysimetric study of grass evapotranspiration). Soil and Water Research Institute Annual report: 154–157. (In Farsi)
Shoja Razavi M, 1983. Gardening Principles in Homes. Tizhoush and Golara. Tehran, Iran. PP. 55. (In Farsi)
Subburayan S, Murugappan A and Mohan S, 2011. Modified Hargreaves equation for estimation of ET0 in a hot and humid location in Tamilnadu State, India. International Journal of Engineering Science and Technology (IJEST) 3(1): 592–600.
Sentelhas PC and Folegatti MV, 2003. Class A pan coefficients (Kp) to estimate daily reference evapotranspiration (ETo). Revista Brasileria de Engenharia Agricola e Ambiental 7 (1): 111–115. Available at: http://www.scielo.br/pdf/rbeaa/v7n1/v7n1a18.pdf
Tabari H, 2009. Evaluation of reference crop evapotranspiration equations in various climates. Water Resources Management. 24(10): 2311–2337.
Trajković S and Gocić M, 2010. Comparison of some empirical equations for estimating daily reference evapotranspiration. Facta Universitatis series: Architecture and Civil Engineering 8(2): 163-168.
Valipour M, 2014. Comparative evaluation of radiation-based methods for estimation of reference evapotranspiration. Journal of Hydrological Engineering 20(5): 1–14, doi: 10.1061/(ASCE)HE.1943-5584.0001066
Xu, CY and Chen D, 2005. Comparison of seven models for estimation of evapotranspiration and groundwater recharge using lysimeter measurement data in Germany. Hydrological Processes 19(18): 3717–3734.
Xu CY and Singh VP, 2002. Cross comparison of empirical equations for calculating potential evapotranspiration with data from Switzerland. Water Resources Management 16: 197–219.