Estimation of Actual Evapotranspiration Using Automatic Calibration in PYSEBAL and METRIC Algorithms in Qazvin Plain

Document Type : Research Paper


1 Department of Water Engineering, Faculty of Agricultural and Natural Resources, Imam Khomeini International University, Qazvin, Iran

2 Water Eng. and Science Dept., Imam Khomeini International University


Estimation of actual evapotranspiration over large areas with appropriate time intervals is important in the optimal management of water resources. The constant need for evapotranspiration data has led to the development of several methods for estimating it. In recent years, the use of remote sensing method to estimate the rate of evapotranspiration in large areas with the desired spatial and temporal resolution has been proposed. In this study, the automatic calibration efficiency of two common mono-source evapotranspiration algorithms estimated from PYSEBAL and METRIC were compared with the results of a drainage lysimeter planted with grass in the Qazvin plain. In this regard, 15 images TM, 22 images ETM+ and 24 images MODIS without cloud and snow during the years 2000 to 2003 were used, which in total 122 outputs were obtained from both algorithms. The results of this study showed that the METRIC algorithm in all three sensors with RMSE (0.42, 0.42 and 1.05 mm / day) respectively had better performance than the PYSEBAL model. Also, the studies performed from the three sensors showed that the MODIS sensor with standard error value (0.15 mm / day) and correlation coefficient (0.98) compared to the two ETM and TM sensors with correlation coefficient values (0.97 and 0.92), standard error (0.17 and 0.59 mm/day) have been able to produce better results. The executive applications of this study can be used to determine the exact amount of evapotranspiration in irrigated lands for water allocation planning, optimization of crop production, irrigation management and assessment of land use change on water effieiency.


Allen, Richard G, Burnett, B., Kramber, W., Huntington, J., Kjaersgaard, J., Kilic, A., Kelly, C., & Trezza, R. (2013). Automated calibration of the metric‐landsat evapotranspiration process. JAWRA Journal of the American Water Resources Association, 49(3), 563–576.
Allen, Richard 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(4), 380–394.
 Ayenew, T. (2003). Evapotranspiration estimation using thematic mapper spectral     satellite data in the Ethiopian rift and adjacent highlands. Journal of Hydrology, 279(1–4), 83–93.
Bala, A., Rawat, K. S., Misra, A. K., & Srivastava, A. (2016). Assessment and validation of evapotranspiration using SEBAL algorithm and Lysimeter data of IARI agricultural farm, India. Geocarto International, 31(7), 739–764.
Bastiaanssen, W. G. M. (1995). Regionalization of surface flux densities and moisture indicators in composite terrain: A remote sensing approach under clear skies in Mediterranean climates. Wageningen University and Research.
Bhattarai, N., Quackenbush, L. J., Im, J., & Shaw, S. B. (2017). A new optimized algorithm for automating endmember pixel selection in the SEBAL and METRIC models. Remote Sensing of Environment, 196, 178–192.
Caiserman, A., & Faour, G. (2021). Spatial variability of evapotranspiration and pressure on groundwater resources: remote sensing monitoring by crop type in the Bekaa plain, Lebanon. Journal of Applied Remote Sensing, 15(1), 14517.
dos Santos, C. A. C., Mariano, D. A., Francisco das Chagas, A., Dantas, F. R. da C., de Oliveira, G., Silva, M. T., da Silva, L. L., da Silva, B. B., Bezerra, B. G., & Safa, B. (2020). Spatio-temporal patterns of energy exchange and evapotranspiration during an intense drought for drylands in Brazil. International Journal of Applied Earth Observation and Geoinformation, 85, 101982.
Ebrahimi pak N.A. (2000). Determination of evapotranspiration potential of reference plant (grass) by lysymeter method and comparison with experimental methods in Qazvin. Ministry of Agricultural Jihad, Agricultural Research, Education and Promotion Organization, Qazvin Agricultural and Natural Resources Research Center. (In Persian).
Firouzi Nezamabadi, F. and Kaviani, A. (2015). Introduction of energy balance algorithms to calculate the actual evapotranspiration using remote sensing techniques. The 1st Int. Conference on Earth Space and Clean Energy, Ardebil, Iran (In Persian).
Gowda, P. H., Chavez, J. L., Colaizzi, P. D., Evett, S. R., Howell, T. A., & Tolk, J. A. (2008). ET mapping for agricultural water management: present status and challenges. Irrigation Science, 26(3), 223–237.
Hessels, T., van Opstal, J., Trambauer, P., Bastiaanssen, W., Faouzi, M., Mohamed, Y., & ErRaji, A. (2017). pySEBAL Version 3.3. 7.
 Hedayati, A., & Kakavand, R. (2012). Climatic zoning of Qazvin Province. Nivar,  36(77–76), 59–66.(In Persian).
Jaafar, H. H., & Ahmad, F. A. (2020). Time series trends of Landsat-based ET using automated calibration in METRIC and SEBAL: The Bekaa Valley, Lebanon. Remote Sensing of Environment, 238, 111034.
Kazamias, A. P., & Sapountzis, M. (2017). Spatial and temporal assessment of potential soil erosion over Greece. Water, 59, 315–321.
Khoshkhoo, Y., Babaei, K., & AsadiOskouei, E. (2018). Estimating Rice Actual Evapotranspiration Using METRIC Algorithm in a part of the North of Iran. Journal of Water and Soil Conservation, 24(6), 105–122.
Khoshkhoo, Y., & Nikmehr, S. (2021). Application of Land Surface Temperature Extracted from Satellite Images for Zoning Reference Evapotranspiration. Environment and Water Engineering, 7(4), 708–722 (In Persian).
Kustas, W. P., & Norman, J. M. (1996). Use of remote sensing for evapotranspiration monitoring over land surfaces. Hydrological Sciences Journal, 41(4), 495–516.
Lee, T. S., Najim, M. M. M., & Aminul, M. H. (2004). Estimating evapotranspiration of irrigated rice at the West Coast of the Peninsular of Malaysia.
Li, Z.-L., Tang, R., Wan, Z., Bi, Y., Zhou, C., Tang, B., Yan, G., & Zhang, X. (2009). A review of current methodologies for regional evapotranspiration estimation from remotely sensed data. Sensors, 9(5), 3801–3853.
Lian, J., & Huang, M. (2016). Comparison of three remote sensing based models to estimate evapotranspiration in an oasis-desert region. Agricultural Water Management, 165, 153–162.
Liaqat, U. W., & Choi, M. (2015). Surface energy fluxes in the Northeast Asia ecosystem: SEBS and METRIC models using Landsat satellite images. Agricultural and Forest Meteorology, 214, 60–79.
Nyolei, D., Nsaali, M., Minaya, V., van Griensven, A., Mbilinyi, B., Diels, J., Hessels, T., & Kahimba, F. (2019). High resolution mapping of agricultural water productivity using SEBAL in a cultivated African catchment, Tanzania. Physics and Chemistry of the Earth, Parts A/B/C, 112, 36–49.
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, 1–18.
Sawadogo, A., Gundogdu, K. S., Traoré, F., Kouadio, L., & Hessels, T. (2020) Estimate in season actual evapotranspiration over a large-scale irrigation scheme in resource-limited conditions.Comptes Rendus de l’Académie Bulgare Des Sciences, 73(10).
Sawadogo, A., Hessels, T. İ. M., Gündoğdu, K. S., Demir, A. O., Mustafa, Ü., & Zwart, S. J. (2020). Comparative analysis of the pysebal model and lysimeter for estimating actual evapotration of soybean crop in adana, turkey. International Journal of Engineering and Geosciences, 5(2), 60–65.
Senay, G. B., Friedrichs, M., Singh, R. K., & Velpuri, N. M. (2016). Evaluating Landsat 8 evapotranspiration for water use mapping in the Colorado River Basin. Remote Sensing of Environment, 185, 171–185.
Tasumi, M. (2003). Progress in operational estimation of regional evapotranspiration using satellite imagery. University of Idaho.
Tasumi, M. (2019). Estimating evapotranspiration using METRIC model and Landsat data for better understandings of regional hydrology in the western Urmia Lake Basin. Agricultural Water Management, 226, 105805.
Tasumi, M., Allen, R. G., Trezza, R., & Wright, J. L. (2005). Satellite-based energy balance to assess within-population variance of crop coefficient curves. Journal of Irrigation and Drainage Engineering, 131(1), 94–109.
Yilmaz, M. T., Anderson, M. C., Zaitchik, B., Hain, C. R., Crow, W. T., Ozdogan, M., Chun, J. A., & Evans, J. (2014). Comparison of prognostic and diagnostic surface flux modeling approaches over the Nile River basin. Water Resources Research, 50(1), 386–408.
Zhang, K., Kimball, J. S., & Running, S. W. (2016). A review of remote sensing based actual evapotranspiration estimation. Wiley Interdisciplinary Reviews: Water, 3(6), 834–853.