مقایسه تبخیر-تعرق مرجع پنمن-مانتیث ASCE و پنمن-مانتیث فائو-56 در مقیاس های زمانی زیرروزانه مختلف: یک مطالعه عددی

نوع مقاله : مقالات پژوهشی

نویسندگان

1 دانشگاه تربیت مدرس

2 دانشگاه شهرکرد

3 دانشگاه هرمزگان

چکیده

در پژوهش حاضر، برآوردهای تبخیر-تعرق مرجع (ETo) حاصل از مدل های پنمن-مانتیث ASCE و فائو-56 (به‌ترتیب، ASCE-PM و FAO56-PM) در مقیاس های زمانی زیرروزانه مختلف از طریق اجرای یک آزمایش محاسباتی مورد مقایسه قرار گرفت. داده های هواشناسی در مقیاس های زمانی روزانه و زیرروزانه مختلف (یک تا 360 دقیقه) با استفاده از داده های روزانه بلندمدت ایستگاه سینوپتیک آبادان (59 ساله) و یک چارچوب ریزمقیاس سازی اطلاعات هواشناسی تولید گردید. نتایج نشان داد در فصول گرم سال، مقادیر مجموع 24 ساعته مولفه های تشعشع و آیرودینامیک و ETo اشتقاق یافته از هر دو مدل ASCE-PM و FAO56-PM از انطباق بهتری با مقادیر نظیر روزانه برخوردار بودند. عملکرد هر دو مدل در بازسازی مقادیر روزانه مولفه آیرودینامیک بهتر از عملکرد آنها در بازسازی مقادیر روزانه مولفه تشعشع بود. در مقایسه با مدل FAO56-PM، عملکرد مدل ASCE-PM در بازسازی مقادیر روزانه ETo نسبت به نحوه محاسبه تشعشع خالص طول موج بلند (Rnl) از حساسیت بیشتری برخوردار بود. نتایج نشان داد اتخاذ یک گام زمانی کوچکتر، لزوما به بهبود انطباق مقادیر مجموع 24 ساعته و مقادیر روزانه ETo نمی انجامد. به-منظور برآورد تبخیر-تعرق مرجع زیرروزانه در شرایط اقلیمی منطقه مطالعاتی، استفاده از مدل ASCE-PM بر اساس انتگرال مقادیر Rnl اشتقاقی از برآوردهای تشعشع خورشیدی در شرایط آسمان صاف (Rso) حاصل از یک مدل فیزیکی-بنیان برآورد تشعشع خورشیدی در بازه‌های زمانی یک ثانیه ای با میانگین ضریب کارآیی مدل برابر با 9970/0 نسبت به سایر گزینه های مورد بررسی ارجح می باشد.

کلیدواژه‌ها


عنوان مقاله [English]

A Comparison of ASCE and FAO56 Reference Evapotranspiration at Different Subdaily Timescales: a Numerical Study

نویسندگان [English]

  • Farzin Parchami-Araghi 1
  • Seyed Majid Mirlatifi 1
  • Shoja Ghorbani Dashtaki 2
  • Adnan Sadeghi-Lari 3
1 Tarbiat Modares University
2 Shahrekord University
3 Hormozgan University
چکیده [English]

Introduction: Subdaily estimates of reference evapotranspiration (ETo) are needed in many applications such as dynamic agro-hydrological modeling. The ASCE and FAO56 Penman–Monteith models (ASCE-PM and FAO56-PM, respectively) has received favorable acceptance and application over much of the world, including the United States, for establishing a reference evapotranspiration (ETo) index as a function of weather parameters. In the past several years various studies have evaluated ASCE-PM and FAO56-PM models for calculating the commonest hourly or 15-min ETo either by comparing them with lysimetric measurements or by comparison with one another (2, 3, 5, 9, 10, 11, 16, 17, 19). In this study, sub-daily ET o estimates made by the ASCE-PM and FAO56-PM models at different timescales (1-360 min) were compared through conduction of a computational experiment, using a daily to sub-daily disaggregation framework developed by Parchami-Araghi et al. (14).
Materials and Methods: Daily and sub-daily weather data at different timescales (1-360 min) were generated via a daily-to-sub-daily weather data disaggregation framework developed by Parchami-Araghi et al. (14), using long-term (59 years) daily weather data obtained from Abadan synoptic weather station. Daily/sub-daily net long wave radiation (Rnl) was estimated through 6 different approaches, including using two different criteria for identifying the daytime/nighttime periods : 1) the standard criteria implemented in both ASCE-PM and FAO56-PM models and 2) criterion of actual time of sunset and sunrise in combination with 1) estimation of clear-sky radiation (Rso) based on the standard approach implemented in both ASCE-PM and FAO56-PM models (1st and 2nd Rnl estimation approaches, respectively), 2) integral of the Rso estimates derived via a physically based solar radiation model developed by Yang et al. (25), YNG model, for one-second time-steps (3rd and 4th Rnl estimation approaches, respectively), and 3) integral of the calculated Rnl based on Rso estimates derived via YNG model for one-second time-steps (5th and 6th Rnl estimation approaches, respectively). The capability of the two models for retrieving the daily ETo was evaluated, using root mean square error RMSE (mm), the mean error ME (mm), the mean absolute error ME (mm), Pearson correlation coefficient r (-), and Nash–Sutcliffe model efficiency coefficient EF (-). Different contributions to the overall error were decomposed using a regression-based method (7).
Results and Discussion: Results showed that during the summer days, 24h sum of sub-daily radiation and aerodynamic components of ETo and the estimated ETo derived from both models were in a better agreement with the respective daily values. The reason for this result can be attributed to the nighttime value of cloudiness function (f) and the longer nighttime during the cold seasons. Because the nighttime values for f are equal the f value at the end of the previous daylight period until the next daylight period. The difference between sub-daily ETo derived from the ASCE-PM and FAO56-PM models during the day and night was highly dependent on the wind speed. In case of both models, daily aerodynamic component of ETo (ETod,aero) were reproduced more efficiently, compared to radiation component (ETod,rad). Except in the case of 6th Rnl estimation approach, FAO56-PM model (with a mean model efficiency (MEF) of 0.9934 to 0.9972) had better performance in reproducing the daily values of ETo (ETod), compared to ASCE-PM model (with a MEF of 0.9910 to 0.9970). The agreement between 24h sum and daily values of aerodynamic component had a lower sensitivity to the adopted time-scale, compared to the radiation component. Compared to the FAO56-PM model the performance of the ASCE-PM model in reproducing the ETod,rad, ETod,aero and ETod had higher sensitivity to the approach utilized for calculation of Rnl and hence, to the uncertainty of net radiation. Results showed that a smaller time step does not necessarily leads to an improvement in agreement between 24h sum of subdaily and daily values of ETo. Deficiency of the standard daytime/nighttime identification criteria resulted in a higher daily averaged daytime (1.3831 to 1.6753 h) used in cloudiness function calculations, compared to the respective value used in calculations of the radiation and aerodynamic components. In order to estimate the sub-daily ETo under climatic condition of the studied region, the use of ASCE-PM model based on the 6th Rnl estimation approach, (ASCE-PM)6, with a MEF of 0.9970 is preferred, compared to other studied alternatives. Another advantage of the (ASCE-PM)6 and (FAO56-PM)6 models is their computational efficiency in case of their implementation in hydrological models.

کلیدواژه‌ها [English]

  • Disaggregation
  • Evapotranspiration
  • ASCE Penman-Monteith
  • FAO-56 Penman-Monteith
1- Allen R.G., Pereira L.S., Raes D., and Smith M. 1998. Crop evapotranspiration: Guidelines for computing crop water requirements. FAO irrigation and drainage paper 56, FAO, Rome, Italy, 301 pp.
2- Allen R.G., Pruitt W.O., Businger J.A., Fritschen L.J., Jensen M.E., and Quinn F.H. 1996. Evaporation and transpiration. In: Heggen R.J. (Ed.), ASCE Handbook of Hydrology. American Society of Civil Engineers, New York.
3- Allen R.G., Pruitt W.O., Wright J.L., Howell T.A., Ventura F., Snyder R., Itenfisu D., Steduto P., Berengena J., Yrisarry J.B., Smith M., Pereira L.S., Raes D., Perrier A., Alves I., Walter I., and Elliott R.L. 2006. A recommendation on standardized surface resistance for hourly calculation of reference ETo by the FAO 56 Penman-Monteith method. Agricultural Water Management, 81(1): 1-22.
4- Allen R.G., Walter I.A., Elliott R.L., Howell T.A., Itenfisu D., Jensen M.E., and Snyder R.L. 2005. The ASCE standardized reference evapotranspiration equation. American Society of Civil Engineers, Reston, Virginia, 192 pp.
5- Bakhtiari B., Khalili A., Liaghat A.M., and Khanjani M.J. 2009. Comparison of Daily with Sum-of-Hourly Reference Evapotranspiration in Kerman Reference Weather Station. Journal of Water and Soil, 23(1): 45-56. (in Persian with English abstract).
6- Cesaraccio C., Spano D., Duce P., and Snyder R.L. 2001. An improved model for determining degree-day values from daily temperature data. International Journal of Biometeorology, 45(4): 161-169.
7- Gauch H.G., Hwang J.T., and Fick G.W. 2003. Model evaluation by comparison of model-based predictions and measured values. Agronomy Journal, 95(6): 1442-1446.
8- Green H.M., and Kozek A.S. 2003. Modelling weather data by approximate regression quantiles. Australian and New Zealand Industrial and Applied Mathematics Journal, 44: C229-C248.
9- Irmak S., Howell T.A., Allen R.G., Payero J.O., and Martin D.L. 2005. Standardized ASCE Penman-Monteith: Impact of Sum-of-Hourly Vs. 24- Hour Time step Computations at Reference Weather Station Sites. Transactions of the ASAE, 48(3): 1063-1077.
10- Itenfisu D., Elliott R.L., Allen R.G., and Walter I.A. 2003. Comparison of reference evapotranspiration calculations as part of the ASCE standardization effort. Journal of irrigation and drainage engineering, 129(6): 440-448.
11- Lopez-Urrea R., Olalla F., Fabeiro C., and Moratalla A. 2006. An evaluation of two hourly reference evapotranspiration equations for semiarid conditions. Agricultural water management, 86(3): 277-282.
12- Ortega-Farias S.O., Cuenca R.H., and English M. 1995. Hourly grass evapotranspiration in modified maritime environment. Journal of Irrigation and Drainage Engineering, 121(6): 369-373.
13- Parchami-Araghi F., Mirlatifi S.M., Ghorbani Dashtaki S., and Mahdian M.H. 2013. Point estimation of soil water infiltration process using Artificial Neural Networks for some calcareous soils. Journal of Hydrology, 481: 35-47.
14- Parchami-Araghi F., Mirlatifi S.M., Ghorbani Dashtaki S., Vazifehdoust M., and Sadeghi-Lari A. 2015. Development of a Disaggregation Framework toward the Estimation of Subdaily Reference Evapotranspiration: 1- Performance Comparison of Some Daily-to-subdaily Weather Data Disaggregation Models Journal of Water and Soil, Accepted (in Persian with English abstract).
15- Parchami-Araghi F., Mirlatifi S.M., Ghorbani Dashtaki S., Vazifehdoust M., and Sadeghi-Lari A. 2015. Development of a Disaggregation Framework toward the Estimation of Subdaily Reference Evapotranspiration: 2- Estimation of Sub-daily Reference Evapotranspiration Using Disaggregated Weather Data Journal of Water and Soil, Accepted with minor revisions (in Persian with English abstract).
16- Pruitt W.O., and Lourence F.J. 1966. Tests of energy balance and other evaporation equations over a grass surface. Chapter IV, Final Report, USAEPG Grant No. DA-AMC-28-043-65-G12, AD-635-588. University of California, Davis, California, pp. 37-63.
17- Shirmohammadi Z., Ansari H., and Alizadeh A. 2011. A Comparison of ASCE and FAO-56 Reference Evapotranspiration for a Hourly Time Step in Fariman Weather Station. Journal of Water and Soil, 25(3): 472-484. (in Persian with English abstract).
18- Steduto P., Todorovic M., Caliandro A., and Rubino P. 2003. Daily ETo estimates by the Penman-Monteith equation in southern Italy: Constant vs. variable canopy resistance. Theoretical and Applied Climatology, 74(3): 217-225.
19- Suleiman A.A., and Hoogenboom G. 2009. A comparison of ASCE and FAO-56 reference evapotranspiration for a 15-min time step in humid climate conditions. Journal of hydrology, 375(3): 326-333.
20- Tanner C.B., and Pelton W.L. 1960. Potential evapotranspiration estimates by the approximate energy balance method of Penman. Journal of Geophysical Research, 65(10): 3391-3413.
21- Todorovic M. 1999. Single-layer evapotranspiration model with variable canopy resistance. Journal of Irrigation and Drainage Engineering, 125(5): 235-245.
22- United Nations Educational, Scientific and Cultural Organization (UNESCO). 1979. Map of the world distribution of arid regions: Map at scale 1:25,000,000 with explanatory note. MAB Technical Notes 7, UNESCO, Paris.
23- Van Bavel C.H.M. 1966. Potential evaporation: The combination concept and its experimental verification. Water Resources Research, 2(3): 455-467.
24- Ventura F., Spano D., Duce P., and Snyder R.L. 1999. An evaluation of common evapotranspiration equations. Irrigation Science, 18(4): 163-170.
25- Yang K., Koike T., and Ye B. 2006. Improving estimation of hourly, daily, and monthly solar radiation by importing global data sets. Agricultural and Forest Meteorology, 137(1): 43-55.