Comparison of Empirical Methods to Estimated Reference Evapotranspiration
Authors
Vivi Fitriani , Cahyoadi Bowo , Marga Mandala , La GandriDOI:
10.29303/jrpb.v12i2.629Published:
2024-09-29Issue:
Vol. 12 No. 2 (2024): Jurnal Ilmiah Rekayasa Pertanian dan BiosistemKeywords:
empirical methods, FAO penman monteith, reference evapotranspirationArticles
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Abstract
Evapotranspiration plays an important role in agricultural water management and crop modelling. Estimating reference Evapotranspiration (ETo) using meteorological variables, both theoretical and empirical methods, is highly recommended considering the availability of weather data in several locations. The estimation method recommended as the standard method is FAO Penman Monteith (FAOPM), but due to the limited meteorological data in a region and the difficulty and complexity of FAOPM, it is recommended to use the empirical method which is easier and only requires a few simple meteorological variables. The aim of this research is to compare and evaluated empirical methods for estimating ETo against the FAOPM. The statistical analysis using in this research are RSME, MAE, coefficient Correlation, NSE, Average bias, index of agreement, and confidence index (c). Evaluation for the best models based on statistic analyzed shows that several empirical methods show terrible performance in estimating the monthly average ETo (mm/day), which are Thornthwaite-Mather, Hargraves-Samani, Makkink, Hamon, Romaneko, and Kharauffa. Modified Blaney-Criddle method showed a good performance method, while PMAWS showed very good performance The Turc and Hansen method showed excellent performance with RMSE, MAE, NSE, and C values for the Turc method, are 0.12, 0.11, 0.78, 0.92 respectively, and for the Hansen method are 0.12, 0.1, 0.8, and 0.89 respectively.
References
Adlan, Setiawan, B. I., Arif, C., & Saptomo, S. K. (2021). Evaluation of the Standard Evapotranspiration Rate Estimation Method (ETo) Using the Microsoft Excel Visual Basic Programming Language in Nagan Raya District, Aceh. Jurnal Teknik Sipil Dan Lingkungan, 6(1), 35–48. https://doi.org/10.29244/jsil.6.1.35-48 DOI: https://doi.org/10.29244/jsil.6.1.35-48
Ahmad Fausan, Setiawan, B. I., Arif, C., & Saptomo, S. K. (2021). Evaporation and Evapotranspiration Model Analysis Using Mathematical Modeling in Visual Basic in Maros Regency. Jurnal Teknik Sipil Dan Lingkungan, 5(3), 179–196. https://doi.org/10.29244/jsil.5.3.179-196 DOI: https://doi.org/10.29244/jsil.5.3.179-196
Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56 (Vol. 17). FAO - Food and Agriculture Organization of the United Nations. https://www.researchgate.net/publication/235704197
Althoff, D., Santos, R. A. dos, Bazame, H. C., Cunha, F. F. da, & Filgueiras, R. (2019). Improvement of Hargreaves–Samani Reference Evapotranspiration Estimates with Local Calibration. Water, 11(11), 2272. https://doi.org/10.3390/w11112272 DOI: https://doi.org/10.3390/w11112272
Araújo Lima, J. G., Carneiro Viana, P., Sobrinho, J. E., & Chaves Couto, J. P. (2019). COMPARAÇÃO DE MÉTODOS DE ESTIMATIVA DE ETO E ANÁLISE DE SENSIBILIDADE PARA DIFERENTES CLIMAS BRASILEIROS. IRRIGA, 24(3), 538–551. https://doi.org/10.15809/irriga.2019v24n3p538-551 DOI: https://doi.org/10.15809/irriga.2019v24n3p538-551
Aydın, Y. (2021). Assessing of evapotranspiration models using limited climatic data in Southeast Anatolian Project Region of Turkey. PeerJ, 9, e11571. https://doi.org/10.7717/peerj.11571 DOI: https://doi.org/10.7717/peerj.11571
Ayeni, A. (2014). Empirics of Standard Deviation. https://doi.org/10.13140/2.1.1444.6729
Bartolomeu, F. T., & Catine, A. C. (2019). Efficiency of empirical methods for reference evapotranspiration estimation in the district of Vilankulo, Mozambique. International Journal of Water Resources and Environmental Engineering, 11(4), 76–82. https://doi.org/10.5897/IJWREE2018.0780 DOI: https://doi.org/10.5897/IJWREE2018.0780
Bin Poyen, Er. F., Kumar Ghosh, A., & Khundu, P. (2016). Review on Different Evapotranspiration Empirical Equations. International Journal of Advanced Engineering, Management and Science (IJAEMS), 2(3). www.ijaems.com
Bourletsikas, A., Argyrokastritis, I., & Proutsos, N. (2018). Comparative evaluation of 24 reference evapotranspiration equations applied on an evergreen-broadleaved forest. Hydrology Research, 49(4), 1028–1041. https://doi.org/10.2166/nh.2017.232 DOI: https://doi.org/10.2166/nh.2017.232
Brouwer, C., & Heibloem, M. (1986). Irrigation Water Management Training Manual No. 3: Irrigation Water Needs (Vol. 3). FAO. https://www.fao.org/3/S2022E/s2022e00.htm#Contents
De Melo, G. L., & Fernandes, A. L. T. (2012). EVALUATION OF EMPIRICAL METHODS TO ESTIMATE REFERENCE EVAPOTRANSPIRATION IN UBERABA, STATE OF MINAS GERAIS, BRAZIL. Engenharia Agricola, Jaboticabal, 32(5), 875–888. https://doi.org/DOI: 10.1590/S0100-69162012000500007 DOI: https://doi.org/10.1590/S0100-69162012000500007
Djaman, K., Koudahe, K., Akinbile, C. O., & Irmak, S. (2017). Evaluation of Eleven Reference Evapotranspiration Models in Semiarid Conditions. Journal of Water Resource and Protection, 09(12), 1469–1490. https://doi.org/10.4236/jwarp.2017.912094 DOI: https://doi.org/10.4236/jwarp.2017.912094
Dlouhá, D., Dubovský, V., & Pospíšil, L. (2021). Optimal Calibration of Evaporation Models against Penman–Monteith Equation. Water, 13(11), 1484. https://doi.org/10.3390/w13111484 DOI: https://doi.org/10.3390/w13111484
Doorenbos, J., & Pruitt, W. O. (1977). Guidelines for predicting crop water requirements. Food and Agriculture Organization of the United Nations.
Ghamarnia, H., Mousabeygi, F., Amiri, S., & Amirkhani, D. (2015). Evaluation of a Few Evapotranspiration Models Using Lysimeteric Measurements in a Semi Arid Climate Region. International Journal of Plant & Soil Science, 5(2), 100–109. https://doi.org/10.9734/IJPSS/2015/14320 DOI: https://doi.org/10.9734/IJPSS/2015/14320
Gong, X., Qiu, R., Ge, J., Bo, G., Ping, Y., Xin, Q., & Wang, S. (2021). Evapotranspiration partitioning of greenhouse grown tomato using a modified Priestley–Taylor model. Agricultural Water Management, 247, 106709. https://doi.org/10.1016/j.agwat.2020.106709 DOI: https://doi.org/10.1016/j.agwat.2020.106709
Gonzalez del Cerro, R. T., Subathra, M. S. P., Manoj Kumar, N., Verrastro, S., & Thomas George, S. (2021). Modelling the daily reference evapotranspiration in semi-arid region of South India: A case study comparing ANFIS and empirical models. Information Processing in Agriculture, 8(1), 173–184. https://doi.org/10.1016/j.inpa.2020.02.003 DOI: https://doi.org/10.1016/j.inpa.2020.02.003
Hansen, S. (1984). Estimation of Potential and Actual Evapotranspiration. Hydrology Research, 15(4–5), 205–212. https://doi.org/10.2166/nh.1984.0017 DOI: https://doi.org/10.2166/nh.1984.0017
Harwell, M. (2019). A Strategy for Using Bias and RMSE as Outcomes in Monte Carlo Studies in Statistics. Journal of Modern Applied Statistical Methods, 17(2). https://doi.org/10.22237/jmasm/1551907966 DOI: https://doi.org/10.22237/jmasm/1551907966
Hernández-Bedolla, J., Solera, A., Sánchez-Quispe, S. T., & Domínguez-Sánchez, C. (2023). Comparative analysis of 12 reference evapotranspiration methods for semi-arid regions (Spain). Journal of Water and Climate Change, 14(9), 2954–2969. https://doi.org/10.2166/wcc.2023.448 DOI: https://doi.org/10.2166/wcc.2023.448
Heydari, M. M., Beygipoor, G., Mehdi Heydari, M., Aghamajidi, R., & Heydari, M. (2014). Comparison and evaluation of 38 equations for estimating reference evapotranspiration in an arid region. Fresenius Environmental Bulletin, 3(8a). https://www.researchgate.net/publication/287850018
Hu, X., Chen, M., Liu, D., Li, D., Jin, L., Liu, S., Cui, Y., Dong, B., Khan, S., & Luo, Y. (2021). Reference evapotranspiration change in Heilongjiang Province, China from 1951 to 2018: The role of climate change and rice area expansion. Agricultural Water Management, 253, 106912. https://doi.org/10.1016/j.agwat.2021.106912 DOI: https://doi.org/10.1016/j.agwat.2021.106912
Huntley, B. J. (2023). Soil, Water and Nutrients. In Ecology of Angola (pp. 127–147). Springer International Publishing. https://doi.org/10.1007/978-3-031-18923-4_6 DOI: https://doi.org/10.1007/978-3-031-18923-4_6
Itolima, O., & Ify, L. N. (2017). Evaluation of empirical models for estimating reference-evapotranspiration (RET-ET) in humid semi-hot equatorial coastal climate. International Journal of Water Resources and Environmental Engineering, 9(8), 162–177. https://doi.org/10.5897/IJWREE2017.0731 DOI: https://doi.org/10.5897/IJWREE2017.0731
Jensen, M. E., & Haise, H. R. (1963). Estimating Evapotranspiration from Solar Radiation. Journal of the Irrigation and Drainage Division, 89(4), 15–41. https://doi.org/10.1061/JRCEA4.0000287 DOI: https://doi.org/10.1061/JRCEA4.0000287
Karunasingha, D. S. K. (2022). Root mean square error or mean absolute error? Use their ratio as well. Information Sciences, 585, 609–629. https://doi.org/10.1016/j.ins.2021.11.036 DOI: https://doi.org/10.1016/j.ins.2021.11.036
Lee, D. K., In, J., & Lee, S. (2015). Standard deviation and standard error of the mean. Korean Journal of Anesthesiology, 68(3), 220. https://doi.org/10.4097/kjae.2015.68.3.220 DOI: https://doi.org/10.4097/kjae.2015.68.3.220
Li, X., & Kang, Y. (2020). Agricultural utilization and vegetation establishment on saline-sodic soils using a water–salt regulation method for scheduled drip irrigation. Agricultural Water Management, 231, 105995. https://doi.org/https://doi.org/10.1016/j.agwat.2019.105995 DOI: https://doi.org/10.1016/j.agwat.2019.105995
Manik, T. K., Sanjaya, P., & Rosadi, R. A. B. (2017). Comparison of Different Models in Estimating Standard Evapotranspiration in Lampung Province, Indonesia. International Journal of Environment, Agriculture and Biotechnology, 2(5), 2309–2318. https://doi.org/10.22161/ijeab/2.5.5 DOI: https://doi.org/10.22161/ijeab/2.5.5
Manuela Portela, M., Santos, J., & Marinho de Carvalho Studart, T. (2020). Effect of the Evapotranspiration of Thornthwaite and of Penman-Monteith in the Estimation of Monthly Streamflows Based on a Monthly Water Balance Model. In Current Practice in Fluvial Geomorphology - Dynamics and Diversity. IntechOpen. https://doi.org/10.5772/intechopen.88441 DOI: https://doi.org/10.5772/intechopen.88441
Ndulue, E., & Ranjan, R. S. (2021). Performance of the FAO Penman-Monteith equation under limiting conditions and fourteen reference evapotranspiration models in southern Manitoba. Theoretical and Applied Climatology, 143(3–4), 1285–1298. https://doi.org/10.1007/s00704-020-03505-9 DOI: https://doi.org/10.1007/s00704-020-03505-9
Oliveira, G. M. de, Leitão, M. de M. V. B. R., Bispo, R. de C., Santos, I. M. S., & Almeida, A. C. de. (2010). Comparação entre métodos de estimativa da evapotranspiração de Referência na região norte da bahia. Revista Brasileira de Agricultura Irrigada, 4(2), 104–109. https://doi.org/10.7127/rbai.v4n206100 DOI: https://doi.org/10.7127/rbai.v4n206100
P. B. JADHAV, S. A. KADAM, & S. D. GORANTIWAR. (2015). Comparison of methods for estimating reference evapotranspiration (ETo) for Rahuri region. Journal of Agrometeorology, 17(2), 204–207. https://doi.org/10.54386/jam.v17i2.1007 DOI: https://doi.org/10.54386/jam.v17i2.1007
Paredes, P., Trigo, I., de Bruin, H., Simões, N., & Pereira, L. S. (2021). Daily grass reference evapotranspiration with Meteosat Second Generation shortwave radiation and reference ET products. Agricultural Water Management, 248, 106543. https://doi.org/10.1016/j.agwat.2020.106543 DOI: https://doi.org/10.1016/j.agwat.2020.106543
Pereira, H. R., Meschiatti, M. C., Pires, R. C. de M., & Blain, G. C. (2018). On the performance of three indices of agreement: an easy-to-use r-code for calculating the Willmott indices. Bragantia, 77(2), 394–403. https://doi.org/10.1590/1678-4499.2017054 DOI: https://doi.org/10.1590/1678-4499.2017054
Pereira, L. S., Paredes, P., Hunsaker, D. J., López-Urrea, R., & Jovanovic, N. (2021). Updates and advances to the FAO56 crop water requirements method. Agricultural Water Management, 248, 106697. https://doi.org/10.1016/j.agwat.2020.106697 DOI: https://doi.org/10.1016/j.agwat.2020.106697
Qiu, R., Liu, C., Cui, N., Wu, Y., Wang, Z., & Li, G. (2019). Evapotranspiration estimation using a modified Priestley-Taylor model in a rice-wheat rotation system. Agricultural Water Management, 224, 105755. https://doi.org/10.1016/j.agwat.2019.105755 DOI: https://doi.org/10.1016/j.agwat.2019.105755
Rahimikhoob, A., & Hosseinzadeh, M. (2014). Assessment of Blaney-Criddle Equation for Calculating Reference Evapotranspiration with NOAA/AVHRR Data. Water Resources Management, 28(10), 3365–3375. https://doi.org/10.1007/s11269-014-0670-7 DOI: https://doi.org/10.1007/s11269-014-0670-7
Renner, M., Brenner, C., Mallick, K., Wizemann, H. D., Conte, L., Trebs, I., Wei, J., Wulfmeyer, V., Schulz, K., & Kleidon, A. (2019). Using phase lags to evaluate model biases in simulating the diurnal cycle of evapotranspiration: A case study in Luxembourg. Hydrology and Earth System Sciences, 23(1), 515–535. https://doi.org/10.5194/hess-23-515-2019 DOI: https://doi.org/10.5194/hess-23-515-2019
Santos, L. da C., Cruz, G. H. T., Capuchinho, F. F., José, J. V., & Reis, E. F. dos. (2019). Assessment of empirical methods for estimation of reference evapotranspiration in the Brazilian Savannah. Australian Journal of Crop Science, 1094–1104. https://doi.org/10.21475/ajcs.19.13.07.p1569 DOI: https://doi.org/10.21475/ajcs.19.13.07.p1569
Sasireka, K., Jagan Mohan Reddy, C., Charan Reddy, C., & Ramakrishnan, K. (2017). Evaluation and Recalibration of Empirical Constant for Estimation of Reference Crop Evapotranspiration against the Modified Penman Method. IOP Conference Series: Earth and Environmental Science, 80, 012062. https://doi.org/10.1088/1755-1315/80/1/012062 DOI: https://doi.org/10.1088/1755-1315/80/1/012062
Shaw, P. A., Johnson, L. L., & Proschan, M. A. (2018). Intermediate Topics in Biostatistics. In Principles and Practice of Clinical Research (pp. 383–409). Elsevier. https://doi.org/10.1016/B978-0-12-849905-4.00027-7 DOI: https://doi.org/10.1016/B978-0-12-849905-4.00027-7
Shirmohammadi-Aliakbarkhani, Z., & Saberali, S. F. (2020). Evaluating of eight evapotranspiration estimation methods in arid regions of Iran. Agricultural Water Management, 239, 106243. https://doi.org/10.1016/j.agwat.2020.106243 DOI: https://doi.org/10.1016/j.agwat.2020.106243
Sobrinho, O. P. L., Júnior, W. L. C., Santos, L. N. S. dos, Silva, G. S. da, Pereira, Á. I. S., & Tavares, G. G. (2020). Empirical methods for reference evapotranspiration estimation. Scientia Agraria Paranaensis, 19(3), 203–210. https://doi.org/10.18188/sap.v19i3.21487 DOI: https://doi.org/10.18188/sap.v19i3.21487
Steidle Neto, A. J., Borges Júnior, J. C. F., Andrade, C. L. T., Lopes, D. C., & Nascimento, P. T. (2015). Reference evapotranspiration estimates based on minimum meteorological variable requirements of historical weather data. Chilean Journal of Agricultural Research, 75(3), 366–374. https://doi.org/10.4067/S0718-58392015000400014 DOI: https://doi.org/10.4067/S0718-58392015000400014
Suwarman, R., Junnaedhi, I. D. G. A., & Novitasari, N. (2021). A Study on Characteristics and Comparison of Evaporation Estimation Methods in Bandung. Journal of Mathematical and Fundamental Sciences, 53(2), 182–199. https://doi.org/10.5614/j.fund.math.sci.2021.53.2.2 DOI: https://doi.org/10.5614/j.fund.math.sci.2021.53.2.2
Talebmorad, H., Ahmadnejad, A., Eslamian, S., Askari, K. O. A., & Singh, V. P. (2020). Evaluation of uncertainty in evapotranspiration values by FAO56-Penman-Monteith and Hargreaves-Samani methods. International Journal of Hydrology Science and Technology, 10(2), 135. https://doi.org/10.1504/IJHST.2020.106481 DOI: https://doi.org/10.1504/IJHST.2020.106481
Thongkao, S., Ditthakit, P., Pinthong, S., Salaeh, N., Elkhrachy, I., Linh, N. T. T., & Pham, Q. B. (2022). Estimating FAO Blaney-Criddle b-Factor Using Soft Computing Models. Atmosphere, 13(10), 1536. https://doi.org/10.3390/atmos13101536 DOI: https://doi.org/10.3390/atmos13101536
TURC, L. (1961). Evaluation des besoins en eau d’irrigation, evapotranspiration potentielle. Ann. Agron., 12, 13–49. https://cir.nii.ac.jp/crid/1574231876103538304.bib?lang=en
Valipour, M., & Guzmán, S. M. (2022). Identification of the Meteorological Variables Influencing Evapotranspiration Variability Over Florida. Environmental Modeling & Assessment, 27(4), 645–663. https://doi.org/10.1007/s10666-022-09828-3 DOI: https://doi.org/10.1007/s10666-022-09828-3
Wang, W., & Lu, Y. (2018). Analysis of the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE) in Assessing Rounding Model. IOP Conference Series: Materials Science and Engineering, 324(1). https://doi.org/10.1088/1757-899X/324/1/012049 DOI: https://doi.org/10.1088/1757-899X/324/1/012049
Weiss, O., Minixhofer, P., Scharf, B., & Pitha, U. (2021). Equation for Calculating Evapotranspiration of Technical Soils for Urban Planting. Land, 10(6), 622. https://doi.org/10.3390/land10060622 DOI: https://doi.org/10.3390/land10060622
Willmott, C. J., Robeson, S. M., & Matsuura, K. (2012). A refined index of model performance. International Journal of Climatology, 32(13), 2088–2094. https://doi.org/10.1002/joc.2419 DOI: https://doi.org/10.1002/joc.2419
Xystrakis, F., & Matzarakis, A. (2011). Evaluation of 13 Empirical Reference Potential Evapotranspiration Equations on the Island of Crete in Southern Greece. Journal of Irrigation and Drainage Engineering, 137(4), 211–222. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000283 DOI: https://doi.org/10.1061/(ASCE)IR.1943-4774.0000283
Zhang, Q., Cui, N., Feng, Y., Gong, D., & Hu, X. (2018). Improvement of Makkink model for reference evapotranspiration estimation using temperature data in Northwest China. Journal of Hydrology, 566, 264–273. https://doi.org/10.1016/j.jhydrol.2018.09.021 DOI: https://doi.org/10.1016/j.jhydrol.2018.09.021
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