مدلسازی رابطه تبخیر و تعرق پتانسیل سالانه و فصلی گیاه مرجع با عوامل اقلیمی در حوضه آبریز فلات مرکزی ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه جغرافیا، دانشکده علوم انسانی، دانشگاه یزد، یزد، ایران

2 دانشیار آب و هواشناسی، دانشگاه یزد، یزد، ایران

چکیده

تخمین دقیق تبخیر و تعرق نقش مهمی در مدیریت منابع آب، برنامه‌ریزی آبیاری و تأمین نیاز آبی گیاهان به‌ویژه در مناطق نیمه‌خشک و خشک دارد. هدف از این تحقیق ارائه‌ی یک مدل رگرسیونی است که با مبنا قرار دادن روش فائو-پنمن-مانتیث بتوان مقدارتبخیر و تعرق گیاه مرجع را با عوامل اقلیمی برآورد کرد. در این پژوهش ابتدا با استفاده از داده‌های ماهانه‌ی حداکثر و حداقل دما، متوسط رطوبت نسبی، ساعات آفتابی و متوسط سرعت باد ایستگاه‌های سینوپتیک واقع در حوضه‌ی آبریز فلات مرکزی ایران در یک دوره‌ی آماری 18 ساله (2012-1995)، مقادیر تبخیر و تعرق سالانه و فصلی به روش FAO-56-PMمحاسبه شد. سپس با استفاده از نرم‌افزار SPSSرابطه‌ی بین عوامل اقلیمی فوق با مقدار تبخیر و تعرق از طریق رگرسیون خطی چندمتغیره مدلسازی گردید. صحت دقت مدل‌ها نیز با آزمودن چهار فرضیه‌ی خطی بودن رابطه، نرمال بودن باقیمانده‌ها، ثابت بودن واریانس باقیمانده‌ها و ناهمبسته بودن خطای مدل سنجیده شد. نتایج حاصل از اجرای مدل مبیّن آن است که رابطه‌ی قوی بین EToحاصل از رگرسیون چندمتغیره با عوامل اقلیمی وجود دارد؛ بطوریکه در مقطع زمانی سالانه و فصول بهار و تابستان حدود 98درصد تغییرات ETo توسط این پنج متغیر تبیین می‌شود و در فصول پاییز و زمستان به ترتیب حدود 97 و 96 درصد از پراش تبخیر و تعرق با پراش پنج عامل اقلیمی مشترک است. معادلات رگرسیون استاندارد حاکی از آن است که سهم متغیرهای سرعت باد و حداکثر دما در میزان تبخیر و تعرق سالانه و فصلی بیش از سایر عوامل اقلیمی است.مقایسه‌ی نقشه‌های هم تبخیر سالانه و فصلی حوضه‌ی آبریز فلات مرکزی نشان داد که ازلحاظ مکانی نیز ارتباط نزدیک و قابل قبولی بین روش فائو-پنمن-مانتیث و مدل رگرسیون وجود دارد و شمال غرب حوضه از کمترین و مناطق جنوبی از بیشترین میزان تبخیر و تعرق سالانه و فصلی برخوردار می‌باشند.

کلیدواژه‌ها


عنوان مقاله [English]

Modeling the relationship between reference evapotranspiration annual and seasonal with climatic factors in catchment central plateau Iran

نویسندگان [English]

  • hossein behzadi karimi 1
  • Ahmad Mazidi 2
1 Department of Geography,yazd University, yazd, iran
2 Associate Professor of Climatology, Yazd University, Yazd, Iran
چکیده [English]

Introduction
The precise estimation of evapotranspiration plays an important role in managing water resources, planning irrigation and providing water needed for plants, especially in semi-arid and dry areas. The FAO-Penman-Monteith method is proposed as the only standard method for calculating reference evapotranspiration from climate data and for evaluating other methods (Allen et al., 1998). In the last few decades, multivariate regression has been used a one of the important methods for recognizing the interrelationship among variables and determining the correlation between evapotranspiration and a set of climatic factors. In this method, evapotranspiration was the dependent variable and various climatic elements were included as independent variables to the model. The best model is a model that can provide a better estimate of two or more other dependent variables. Arab Solghar et al. (2010) predicted annual evapotranspiration using multivariate regression in a number of subtropical stations in Iran. The results showed association between estimated evapotranspiration using Penman-Monteith equation and the method had a relatively small error level. Therefore, the aim of this study was to calculate evapotranspiration in different months of the year and subsequently in annual and seasonal periods for stations located in the central watershed of Iran during 1995-2012 using the FAO-Penman-Monteith method and modeling and estimating ETo values based on five climatic factors (maximum and minimum temperature, relative humidity, suny hours, and average wind speed at 2 meters above ground level) and the FAO-56-PM equation.
 
Materials and methods
In this study, first, annual and seasonal evapotranspiration were measured by the FAO-56-PM method using Cropwat software based on monthly data of maximum and minimum temperature, average relative humidity, sunny hours and average wind speed of synoptic stations located in the central watershed of Iran during a statistical period of 18 years (1995-2012). Then, SPSS software was used to model the relationship between the above climatic factors and evapotranspiration through multivariate linear regression. The accuracy of the models was evaluated by testing the four hypotheses of the linearity of the relationship, normality of the residuals distribution, constant variance of the residuals, and statistical independence of the errors. In the end, the GIS software capability was used for zoning the annual and seasonal evapotranspiration of the central plateau watershed, and preparing plans related to ETo values ​​derived from the FAO-Penman-Monteith equation and multivariate regression equation. The two methods were also spatially compared and analyzed.
 
Results and discussion
The results of the model show a strong correlation between ETo obtained from multivariate regression and the five climatic factors, so that about 98% of changes in ETo at annual scale and in the spring and summer were explained by these five variables, and approximately 97 and 96 percent of evapotranspiration changes were associated with changes in climatic factors in the autumn and winter seasons. Standard regression equations showed that the contribution of wind speed and maximum temperature variables in annual and seasonal evapotranspiration was more than other climatic factors. In summer, sunny hours and in other seasons, as well as at annual time scale, relative humidity had the least effect on the amount of evapotranspiration. Also, the highest effect of wind speed area and maximum temperature calculated in the study was 0.81 in the summer season and 0.41 in the spring. Comparison of the annual and seasonal evaporation maps of the central plateau watershed showed an acceptable correlation between the FAO-Penman-Monteith method and the regression model. In spring and summer, the highest ETo observed in both FAO-Penman-Monteith and regression methods occurred in the southern and middle regions of the central plateau watershed and the lowest ETo was in the northwest of the watershed area. In winter, ETo was increasing from the center of the watershed towards lower latitudes due to the relative increase in temperature and wind speed. The annual ETo value was lower in the northern regions but higher in the southern regions. Wind speed, average maximum temperature and minimum temperature had the greatest effect on increasing ETo respectively. The results of this study are consistent with studies by Azizi et al. (2009) on estimating ETo through multivariable regression in Isfahan province; Arab Solghar et al. (2011), in predicting annual ETo using meteorological data in a number of stations in semi-arid areas of Iran; Sheikholeslami et al. (2014) on modeling ETo using daily data in Khorasan Razavi; and Bakhtiari et al. (2015) on the estimation of daily ETo in selected semi-arid climates of Iran.
 
 Conclusion
The purpose of this study was to provide a regression model based on the FAO-Penman-Monteith method that can estimate ETo using climatic factors. In this study, the maximum and minimum temperature, average relative humidity, sunny hours and average wind speed were measured monthly at 2 meter height from the ground surface of the synoptic stations via Cropwat software.
ETo values in the watershed of the central plateau of Iran ​​were calculated in annual and seasonal time scales using the FAO-56-PM method during the statistical period of 18 years (1995-2012). Using SPSS 20, the relationship between the above climatic factors and ETo was modeled through multivariable regression. The results of the model showed a significant relationship between ETo obtained from multivariable regression and the climatic factors, in which the contribution of wind speed and maximum temperature variables in annual and seasonal ETo were more than other climatic factors. Comparison of annual and seasonal ETo maps of the central plateau watershed showed a close and acceptable association between the FAO-Penman-Monteith method and the regression model at spatial level, so that the northwest of the watershed had the lowest and the southern regions had the highest annual and seasonal ETo. Therefore, due to the acceptable results of this study in Iran’s central plateau watershed, it is recommended that regression equations be used in other watersheds of the country with insufficient or lack of lysimeter data to predict ETo with acceptable accuracy, which plays a very important role in determining the water requirement of plants.

کلیدواژه‌ها [English]

  • plants
  1.  

    1. Abedi Kupai, J., Islamiyan,  S.S. & Amiri, M.J. (2008). Comparison of four methods for estimating the reference level of evapotranspiration and transpiration with microsilica data in Isfahan region. Second National Conference on Irrigation and Drainage Networks, Ahvaz Shahid Chamran University, Ahvaz.
    2. Alizadeh, A. (2010). Principles of Applied Hydrology. Mashhad, Imam Reza University.
    3.  Alizadeh, A., Kamali., G., Khanjani, M.J., & Rahnamood, M.R. (2004). Estimation of evapotranspiration estimation methods in arid regions of Iran. Quarterly journal of geographic research, No. 73, pp. 105-97.
    4. Allen, R.G., Pereira, L.S., Reas, D. & Smith, M. (1998). Crop Evapotranspiration-Guidelines for Computing Crop Water Requirement, FAO Irrigation and Drainage Paper No.56, Rome, Italy.
    5. Arabsolaghar, A.A., Dehghan, H., Sedghi, H., & Naderifar, M. (2011). Projection of annual evapotranspiration with application of meteorological data in a number of semi arid regions of Iran. Journal of Water Resources Engineering, pp. 30-21.
    6. Asakereh, H. (2011). Basics of Statistical Climatology. Zanjan University of Zanjan.
    7. Azizi, G., Hanafi, A., & Soltani, M. (2009). Estimation of Potential Evapotranspiration through Multivariate Regression in Isfahan Province. Quarterly Geography, No. 11, pp. 92-77.
    8. Bakhtiari, B., Mohebbi Dehaghani, A.R., & Qaderi, K. (2015). Estimation of daily reference evapotranspiration with limited meteorological data in selected Iran’s semi-arid climates. Iranian Water Resources Research, No. 3, pp. 144-131.
    9. Burn D.H. & N.M., Hesch. (2007). Trends in Evaporation for Canadaian Prairies. J. of Hydrology, 336, PP. 61-73.
    10. Djaman, K.B., Balde, A., Sow, A., Muller, B., Irmak, S.K., N’Diaye, M., Manneh, B.D., Moukoumbi, Y., Futakuchi, K., & Saito, K. (2015). Evaluation of sixteen reference
      Evapotranspiration methods under sahelian conditions in the Senegal River Valley.J. Hydrol. Region. Stud. 3: 139-159.
    11. Ghahraman, B. (2006). Time Trend in the Mean Annual Temperature of Iran, Turk. J. Agric forest. 30, PP. 439-448.
    12. Hargreaves, G.H. (1994). Defining and Hsing Reference Evapotranspiration, Journal of Irrigation and Drainage Engineering Vol. 120, No. 6, PP. 1132-1139.
    13. Jamei, M., & Mousavi Payegi, M. (2013). Spot Estimation and Zoning of Reference Evapotranspiration in Khuzestan Province. Magazine Geography and Development Zone, No. 21, pp. 42-23.
    14. Javari, Majid. (2008). Application of statistics in climatology. Tehran, Payame Noor Publications.
    15. Khoshhal, J., Zarea Abyaneh, H., & Jooshni, A.R. (2015). Evaluation of different methods for estimating reference evapotranspiration using the FAO evaporation pan method in the eastern and southeastern watershed of the country. Journal of Natural Geography, Vol. 8, No. 28, pp. 16-1.
    16. Laaboudi A. Mouhouche, B. & Draoui B. (2012). Neural network approach to reference evapotranspiration modeling from limited climatic data in arid regions. Int. J. Biometeorol. 56: 831–841.
    17. Ladlani I. Houichi L. Djemili L. Heddam S. & Belouz K. (2012). Modeling daily reference evapotranspiration (ET0) in the north of Algeria using generalized regression neural networks (GRNN) and radial basis function neural networks(RBFNN): a comparative study. Meteorol. Atmos. Phys. 118:163–178.
    18. Lashkari, H., Keykhosrowi, Q., & Rezaei, A. (2009). Analysis of the CROPWAT Model Efficiency in Estimating the Need for Wheat Crop in West Kermanshah: West Islamabad, Saripul Zahab and Ravansar. Quarterly Journal of Humanities, Volume 13, Issue 1, pp. 270-247.
    19. Liu, X., Xu, C., Zhong, X., Li, Y., Yuan, X., & Cao, J. (2017). Comparison of 16 models for reference crop Evapotranspiration against weighing Lysimeter measurement. J. Agric. Water
      Manage. 184: 145-155.
    20. Lo ́pez-Urrea, R., Martın de Santa Olalla, F., Fabeiro, C. & Moratalla, A. (2006). Testing evapotranspiration equations using lysimeter observations in a semiarid climate.Agricaltural Water Management, 85: 15-26.
    21. Maasoompour, J., Rajai, S., & Yeganeh, M. (2014). Time and spatial variability of the evapotranspiration trend of reference plant in Iran. Journal of Applied Geosciences Research, No. 34, pp. 25-7.
    22. Mahdavi, M., & TaherKhani., M. (2012). Application of statistics in geography. Tehran, Gomes publishing house.
    23. Martinez-cob A. (1996). Multivariate Geo statistical Analysis of Evapotranspiration and Precipitation in Mountainous Terrain. Journal of Hydrology. 174: 19-35.
    24. Merimosavi, H., Panahi, H., Akbari, H., & Akbarzadeh, Y. (2012) . Calibration methods of reference crop potential evapotranspiration and calculate crop water requirement olives in Kermanshah. Journal of Geography and Environmental Sustainability, No. 3, pp. 64-45.
    25. Mohammadi, H., Azizi, G., Khosh Akhlagh, F., & Khazei., M. (2016). Estimate of summer evapotranspiration of sugarcane plant in Khuzestan province using climatic data. Journal of Geographical Information (Sepehr), Volume 25, Issue 99, pp. 153-141.
    26. Molnar, P. & Ramirez, J. A. (2001). Recent Trends in Precipitation and Stream Flow in the Rio Puerco Basin,  Journal of Climate, 14, PP. 2317-2328.
    27. Nazeer, M. (2009). Simulation of maize crop under irrigated and rained conditions with CROPWAT model. ARPN J. Agric. Biol. Sci, 4(2), pp 68-73.
    28. Norrant, C. & A., Douguedroit. (2005). Monthly And Daily Precipitation  Trends in the Mediterranean(1950-2000), Theoretical and Applied Climatology, 83, PP. 89-106.
    29. Rao. Y., Sun, G.,  Ford, C.R., &  Vose, J.M. (2011). Modeling Potention Evapotranspiration of Two Forested Watersheds in the Southern APPALACHIANS, American Society of Agricultural Biological Engineers, Vol. 54, No. 6, PP. 2067-2078.
    30. Raouf, M., & Azizi Mobser, J. (2017) . Evaluation of Eight Reference Evapotranspiration Models in Ardabil Plain. Journal of Soil and Water Research, Vol. 24, No. 6, pp. 227-241.
    31. Sharghi, T., Barry Abarghouie , H., Asadi, M.A., & Kousari, M.R. (2010) . Estimation of evapotranspiration of reference plant using Penman-Monteith method and its zoning in Yazd province. Dry Boom Journal, No. 1, pp. 33-25.
    32. Sheikholeslami, N., Ghahraman, Bijan., Azhadi, A., Davari, K., & Mohajerpour; M. (2014). Propagation of evapotranspiration of reference plant using main component analysis method and development of multiple linear regression model (case study: Mashhad station). Water and Soil Journal, No. 2, pp. 429-420.
    33. Singh, K. R., Pawer, P.S. (2011). Comparative Study of  Reference Crop Evapotranspiration (ETo) By Different Energy Based Method With FAO56 Penman-Monteith Method at New Delhi, India, International Journal of Engineering Science and Technology,Vol.3,No.10,7861-7868.
    34. Su, H.; Wood, E. F.; Wojcik, R.; McCabe, M. (2006). Sensitivity Analysis of Regional Scale. Evapotranspiration Predictions to the Forcing Data, American Geophysical Union,
      Fall Meeting 2007, abstract #H31A-02.
    35. Talebi, A., Pourmohammad, S., & Rahimian, M.H. (2010). Investigation of the Factors Affecting Reference Evapotranspiration by Using the Sensitivity Analysis of the FAO-Penman-Monteith Equation. Natural Geography Research, No. 73, pp. 110-97.
    36. Vaziri, J., Salamat, A., Ansari, M. R., Maschi, M., Heidari, N., Dehghani Sanić, H. (2008). Evapotranspiration of plants (instructions for calculation of required water requirements of plants). Publication of Iran National Irrigation and Drainage Commission, First Edition, p. 9.
    37. Zhang X., K,D., Harvey, W.D., Hogg. & T.R., Yuzyk. (2001).  Trends in Canadian Stream Flow, Water Resources Research, 37(4), PP.  987-998.