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Developing Equations for Estimating Reference Evapotranspiration in Australia

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Abstract

Quantifying reference evapotranspiration (ET0) is essential in water resources management. Although, many methods have been developed with different level of accuracy, in this study, two new equations were developed and optimized for estimating ET0 using Honey-Bee Mating Optimization (HBMO) algorithm. The first eq. estimates ET0 from extraterrestrial radiation (Ra), relative humidity (RH) and mean daily temperature (Tmean), while the second uses the same parameters except that mean daily temperatures is replaced with maximum daily air temperature (Tmax). Both equations were developed using climatic data from eight weather stations in Western Australia and subsequently verified using data from ten sites across Australia. The estimated ET0 values from both equations versus the FAO56-Penman-Monteith have a coefficient of determination, R2, of larger than 0.96. Moreover, the performance of six commonly used methods of estimating ET0 including Hargreaves-Samani, Thornthwaith, Hamon, Mc Guinness-Bordne, Irmak and Jensen-Haise were assessed and the Hargreaves-Samani method performed better than others. An attempt was made to calibrate the Hargreaves-Samani equation; however, its overall performance did not improved and the two newly proposed equations are suggested to be used in Australia.

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References

  • Abtew W (1996) Evapotranspiration measurements and modelling for three wetland systems in South Florida. J Am Water Resour Assoc 32:465–473

    Article  Google Scholar 

  • Ahooghalandari M, Khiadani M, Jahromi ME (2016) Calibration of Valiantzas’ reference evapotranspiration equations for the Pilbara region, Western Australia. Theor Appl Climatol 1–12. doi:10.1007/s00704-016-1744-7

  • Alavi SA, Rahimikhoob A (2016) A simple model for determining reference evapotranspiration using NOAA satellite data: a case study. Environ Process 1:1–15

    Google Scholar 

  • Alexandris S, Kerkides P, Liakatas A (2006) Daily reference evapotranspiration estimates by the “Copais” approach. Agric Water Manag 82:371–386

    Article  Google Scholar 

  • Allen RG, Smith M, Perrier A, Pereira LS (1994a) An update for the definition of reference evapotranspiration. ICID Bull 43:1–34

    Google Scholar 

  • Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration-guidelines for computing crop water requirements-FAO irrigation and drainage paper 56. FAO, Rome

    Google Scholar 

  • Azhar AH, Perera B (2010) Evaluation of reference evapotranspiration estimation methods under southeast Australian conditions. J Irrig Drain Eng 137:268–279

    Article  Google Scholar 

  • Chauhan S, Shrivastava RK (2009) Performance evaluation of reference evapotranspiration estimation using climate based methods and artificial neural networks. Water Resour Manag 23:825–837

    Article  Google Scholar 

  • Eberhard S, Halse S, Humphreys W (2005) Stygofauna in the Pilbara region, north-West Western Australia: a review. J R Soc West Aust 88:167–176

    Google Scholar 

  • Efthimiou N, Alexandris S, Karavitis C, Mamassis N (2013) Comparative analysis of reference evapotranspiration estimation between various methods and the FAO56 penman-Monteith procedure. European Water Journal 42:19–34

    Google Scholar 

  • Esmi Jahromi M, Afzali SH (2014) Application of the HBMO approach to predict the total sediment discharge. Iranian Journal of Science and Technology 38:123–135

    Google Scholar 

  • Gundekar H, Khodke U, Sarkar S, Rai R (2008) Evaluation of pan coefficient for reference crop evapotranspiration for semi-arid region. Irrig Sci 26:169–175

    Article  Google Scholar 

  • Hamon WR (1961) Estimating potential evapotranspiration. J Hydraul Div 87:107–120

  • Hargreaves GH, Allen RG (2003) History and evaluation of Hargreaves evapotranspiration equation. J Irrig Drain Eng 129:53–63

    Article  Google Scholar 

  • Hargreaves GH, Samani ZA (1985) Reference crop evapotranspiration from ambient air temperature. American Society of Agricultural Engineers (Microfiche collection)(USA) no fiche no 85–2517.

  • Heydari MM, Heydari M (2014) Calibration of Hargreaves–Samani equation for estimating reference evapotranspiration in semiarid and arid regions. Arch Agron Soil Sci 60:695–713

    Article  Google Scholar 

  • Irmak S, Irmak A, Allen R, Jones J (2003a) Solar and net radiation-based equations to estimate reference evapotranspiration in humid climates. J Irrig Drain Eng 129:336–347

    Article  Google Scholar 

  • Irmak S, Allen R, Whitty E (2003b) Daily grass and alfalfa-reference evapotranspiration estimates and alfalfa-to-grass evapotranspiration ratios in Florida. J Irrig Drain Eng 129:360–370

    Article  Google Scholar 

  • Itenfisu D, Elliott RL, Allen RG, Walter IA (2003) Comparison of reference evapotranspiration calculations as part of the ASCE standardization effort. J Irrig Drain Eng 129:440–448

    Article  Google Scholar 

  • Jabloun M, Sahli A (2008) Evaluation of FAO-56 methodology for estimating reference evapotranspiration using limited climatic data: application to Tunisia. Agric Water Manag 95:707–715

    Article  Google Scholar 

  • Jacovides C, Kontoyiannis H (1995) Statistical procedures for the evaluation of evapotranspiration computing models. Agric Water Manag 27:365–371

    Article  Google Scholar 

  • Jahromi ME, Ehsan M, Meyabadi AF (2012) A dynamic fuzzy interactive approach for DG expansion planning. Int J Electr Power Energy Syst 43:1094–1105

    Article  Google Scholar 

  • Jensen ME (1967) Empirical methods of estimating or predicting evapotranspiration using radiation.

  • Jensen ME, Haise HR (1963) Estimating evapotranspiration from solar radiation. Proceedings of the American Society of Civil Engineers. Journal of the Irrigation and Drainage Division 89:15–41

    Google Scholar 

  • Jensen ME, Robb DC, Franzoy CE (1970) Scheduling irrigations using climate-crop-soil data. Proceedings of the American Society of Civil Engineers. Journal of the Irrigation and Drainage Division 96:25–38

    Google Scholar 

  • Jensen ME, Burman RD, Allen RG (1990) Evapotranspiration and irrigation water requirements. ASCE

  • Johnson S, Wright A (2003) Mine void water resource issues in Western Australia. Water and Rivers Commission, Perth, Australia

    Google Scholar 

  • Kisi O (2013) Comparison of different empirical methods for estimating daily reference evapotranspiration in Mediterranean climate. J Irrig Drain Eng 140:04013002

    Article  Google Scholar 

  • Kisi O, Cengiz TM (2013) Fuzzy genetic approach for estimating reference evapotranspiration of Turkey: Mediterranean region. Water Resour Manag 27:3541–3553

    Article  Google Scholar 

  • Landeras G, Ortiz-Barredo A, López JJ (2008) Comparison of artificial neural network models and empirical and semi-empirical equations for daily reference evapotranspiration estimation in the Basque Country (northern Spain). Agric Water Manag 95:553–565

    Article  Google Scholar 

  • Martí P, González-Altozano P, Gasque M (2011) Reference evapotranspiration estimation without local climatic data. Irrig Sci 29:479–495

    Article  Google Scholar 

  • McGuinness JL, Bordne EF (1972) A comparison of lysimeter-derived potential evapotranspiration with computed values. US Dept. of Agriculture, Washington, DC

  • Moritz RF, Southwick EE (1992) Bees as superorganisms: an evolutionary reality. Springer Verlag

  • Oudin L, Moulin L, Bendjoudi H, Ribstein P (2010) Estimating potential evapotranspiration without continuous daily data: possible errors and impact on water balance simulations. Hydrol Sci J 55:209–222

    Article  Google Scholar 

  • Penman HL (1963) Vegetation and hydrology. Soil Science:357.

  • Sabziparvar AA, Tabari H, Aeini A, Ghafouri M (2010) Evaluation of class a pan coefficient models for estimation of reference crop evapotranspiration in cold semi-arid and warm arid climates. Water Resour Manag 24:909–920

    Article  Google Scholar 

  • Shuttleworth W (1993) Evaporation. Handbook of Hydrology, DR Maidment, Ed. McGraw-Hill

    Google Scholar 

  • Temesgen B, Eching S, Davidoff B, Frame K (2005) Comparison of some reference evapotranspiration equations for California. J Irrig Drain Eng 131:73–84

    Article  Google Scholar 

  • Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38:55–94

  • Trajkovic S (2007) Hargreaves versus penman-Monteith under humid conditions. J Irrig Drain Eng 133:38–42

    Article  Google Scholar 

  • Trajkovic S, Kolakovic S (2009) Wind-adjusted Turc equation for estimating reference evapotranspiration at humid European locations. Hydrol Res 40:45–52

    Google Scholar 

  • Valiantzas JD (2006) Simplified versions for the penman evaporation equation using routine weather data. J Hydrol 331:690–702

    Article  Google Scholar 

  • Valiantzas JD (2012a) Simple ET 0 forms of Penman’s equation without wind and/or humidity data. I: Theoretical development Journal of Irrigation and Drainage Engineering 139:1–8

    Google Scholar 

  • Valiantzas JD (2012b) Simple ET 0 forms of Penman’s equation without wind and/or humidity data. II: Comparisons with reduced set-FAO and other methodologies Journal of Irrigation and Drainage Engineering 139:9–19

    Google Scholar 

  • Valipour M (2014) Investigation of Valiantzas’ evapotranspiration equation in Iran. Theor Appl Climatol 121:1–12

    Google Scholar 

  • Van Vreeswyk AME (2004) An inventory and condition survey of the Pilbara region, Western Australia. Department of Agriculture, Australia

    Google Scholar 

  • Xu J, Wang J, Wei Q, Wang Y (2016) Symbolic regression equations for calculating daily reference evapotranspiration with the same input to Hargreaves-Samani in arid China. Water Resour Manag 1:1–19

    Google Scholar 

  • Yuce B, Packianather MS, Mastrocinque E, Pham DT, Lambiase A (2013) Honey bees inspired optimization method: the bees algorithm. Insects 4:646–662

    Article  Google Scholar 

Download references

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Correspondence to Mehdi Khiadani.

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Ahooghalandari, M., Khiadani, M. & Jahromi, M.E. Developing Equations for Estimating Reference Evapotranspiration in Australia. Water Resour Manage 30, 3815–3828 (2016). https://doi.org/10.1007/s11269-016-1386-7

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  • DOI: https://doi.org/10.1007/s11269-016-1386-7

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