Evaluating the Performance of Calibrated Temperature-based Equations as Compared to Standard FAO-56 Penman Monteith Equation in Humid Climatic Condition of Dehradun (India)

Authors

  • Arvind Singh Tomar Govind Ballabh Pant University of Agriculture & Technology, Pantnagar-263 145, Uttarakhand, India Author

DOI:

https://doi.org/10.52151/jae2022594.1790

Keywords:

calibration, Dehradun, FAO-56 Penman Monteith equation, global performance indicator, reference evapotranspiration, temperature-based ETo equations

Abstract

The present study was undertaken to calibrate, validate, and evaluate the performance of temperature-based evapotranspiration equations in comparison to the standard FAO-56 Penman Monteith (FAO-56 PM) model in humid climatic condition of Dehradun district of Uttarakhand using 31-years (1989-2019) daily meteorological dataset. The quality control of dataset was ensured by omitting days with missing data and outliers. The performance of 12 calibrated temperature-based ETo equations namely, Allen (1993) [AL93], Baier and Robertson (1965) [BR65], Bogawski and Bednorz (2014) [BB14], Droogers and Allen (2002) [DA02], Dorji et al. (2016) [DO16], Hargreaves (1994) [HA94], Heydari and Heydari (2014) [HH14], Kharrufa (1985) [KA85], Ravazzani et al. (2012) [RA12], Samani (2004) [SA04], Schendel (1967) [SC67], and Trajkovic (2007) [TR07] were evaluated in comparison to standard FAO-56 PM model in terms of daily ETo estimates. The analysis showed that calibrated temperature-based equations performed well with higher value of agreement index (0.85-0.98) and reduced errors. The values of Root mean square error (RMSE), Mean bias error (MBE), Maximum absolute error (MAXE), Percent error of estimate (PE), and Standard error of estimate (SEE) for calibrated equations ranged from 0.29 to 1.15 mm.day-1, (-)0.39 to 0.53 mm.day-1, 0.64 to 3.95 mm.day-1, 4.71 to 19.11%, and 0.17 to 1.00 mm.day-1, respectively; whereas for original equations they varied in the range from 0.47 to 3.64 mm.day-1, (-)0.32 to 2.92 mm.day-1, 0.95 to 10.65 mm.day-1, 11.74 to 106.15%, and 0.18 to 1.72 mm.day-1, respectively, indicating improved performance of calibrated equations. The ranking of calibrated ETo equations on the basis of Global Performance Indicator (GPI) values confirmed that calibrated Dorji et al. (2016) equation produced best result, while Samani (2004) equation with its lowest value performed poorly. Based on GPI values, calibrated equations can be ranked (best to worst performing) as DO16> AL93> TR07> RA12> DA02> HA94> SC67> KH85> BR65> HH14>BB14> SA04. Thus, calibrated Dorji et al. (2016) equation can be used as substitute for FAO-56 PM model in the absence of large number of meteorological parameters for accurate estimation of ETo values in the study area.

Author Biography

  • Arvind Singh Tomar, Govind Ballabh Pant University of Agriculture & Technology, Pantnagar-263 145, Uttarakhand, India

    Assistant Professor, Department of Irrigation and Drainage Engineering, College of Technology

References

Abtew W. 1996. Evapotranspiration measurements and modeling for three wetland systems in south Florida. J. Amer. Water Resour. Assoc., 32(3): 465-473.

Ahmadi S H; Fooladmand H R. 2008. Spatially distributed monthly reference evapotranspiration derived from the calibration of Thornthwaite equation: A case study, south of Iran. Irrig. Sci., 26, 303-312.

Allen R G. 1993. Evaluation of a temperature difference method for computing grass reference evapotranspiration. Report submitted to Water Resources Development and Management Service Land and Water Development Division, FAO, Rome, Italy, pp: 49.

Allen R G; Jensen M E; Wright J L; Burman R D. 1989. Operational estimates of reference evapotranspiration. Agron. J., 81, 650-662.

Allen R G; Smith, M; Perrier A; Pereira L S. 1994. An update for the definition of reference evapotranspiration. ICID Bull., 43(2), 1- 34.

Allen R G. 1997. Self-calibrating method for estimating solar radiation from air temperature. J. Hydrol. Eng., 2(2), 56-67.

Allen R G; Pereira L S; Raes D; Smith M. 1998. Crop Evapotranspiration-Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper No. 56, FAO, Rome, pp: 300.

Allen R G; Pereira L S; Howell T A; Jensen M E. 2011. Evapotranspiration information reporting: I. Factors governing measurement accuracy. Agric. Water Manage., 98, 899-920.

Arellano G M; Irmak S. 2015. Reference (potential) evapotranspiration I: Comparison of temperature, radiation, and combination-based energy balance equations in humid, subhumid, arid, semiarid, and Mediterranean-type climates. J. Irrig. Drain. Eng., 142(4), 04015065.

Bachour R; Walker W R; Torres-Rua A F; McKee M. 2013. Assessment of reference evapotranspiration by the Hargreaves method in the Bekaa Valley, Lebanon. J. Irrig. Drain. Eng., 139(11), 933-938.

Baier W; Robertson G W. 1965. Estimation of latent evaporation from simple weather observations. Can. J. Plant Sci., 45, 276–284.

Barthwal A; Swaroop N; Rao P S; Thomas P. 2019. Assessment of physical properties of soil in Dehradun district, Uttarakhand, India. Int. J. Chem. Stud., 7(3), 1623-1625.

Batra N; Islam S; Venturini V; Bisht G; Jiang L E. 2006. Estimation and comparison of evapotranspiration from MODIS and AVHRR sensors for clear sky days over the Southern Great Plains. Remote Sens. Environ., 103(1), 1-15.

Berti A; Tardivo G; Chiaudani A; Rech F; Borin M. 2014. Assessing reference evapotranspiration by the Hargreaves method in North-Eastern Italy. Agric. Water Manage., 140, 20-25.

Blaney H F; Criddle W D. 1962. Determining Consumptive Use and Irrigation Water Requirements. USDA ARS Tech. Bull. 1275, Washington, DC.

Bogawski P; Bednorz E. 2014. Comparison and validation of selected evapotranspiration models for conditions in Poland (Central Europe). Water Resour. Manage., 28, 5021-5038.

Cadro S; Uzunovic M; Zurovec J; Zurovec O. 2017. Validation and calibration of various reference evapotranspiration alternative methods under the climate conditions of Bosnia and Herzegovina. Int. Soil Water Conserv. Res., 5, 309-324.

Chavan M L; Khode U M; Patil A S. 2010. Comparison of several reference evapotranspiration methods for hot and humid regions of Maharashtra. Int. J. Agric. Eng., 2(2), 259-265.

CWC. 2019. Reassessment of Water Availability in India using Space Inputs. Basin Planning and Management Organization. Central Water Commission, New Delhi, pp: 100.

Despotovic M; Nedic V; Despotovic D; Cvetanovic S. 2015. Review and statistical analysis of different global solar radiation sunshine models. Renewable Sustain. Energy Rev., 2, 1869-1880.

Djaman K; Tabari H; Balde A B; Diop L; Futakuchi K; Irmak S. 2016. Analyses, calibration and validation of evapotranspiration models to predict grass-reference evapotranspiration in the Senegal river delta. J. Hydrol. Reg. Stud., 8, 82-94.

Doorenbos J; Pruitt W O. 1977. Guidelines for Predicting Crop Water Requirements. FAO Irrigation and Drainage Paper No. 24, second ed. FAO, Rome, pp: 156.

Dorji U; Olsen J E; Seidenkrantz M S. 2016. Water balance in the complex mountainous terrain of Bhutan and linkages to land use. J. Hydrol. Reg. Stud., 7, 55-68.

Droogers P; Allen R G. 2002. Estimating reference evapotranspiration under inaccurate data conditions. Irrig. Drain. Syst., 16(1), 33-45.

Fisher D K; Pringle H C. 2013. Evaluation of alternative methods for estimating reference evapotranspiration. Agric. Sci., 4(8A), 51-60.

Fontenot R L. 2004. An evaluation of reference evapotranspiration models in Louisiana. Unpublished M.Sc. Thesis, Louisiana State Univ., Baton Rouge, LA.

Gangopadhyaya M; Herbeck G E Jr.; Nordenson T J; Omar M H; Uryvahev V A. 1966. Measurement and Estimation of Evaporation and Evapotranspiration. World Meteorological Organization, Geneva, Switzerland, Technical Note No. 83, pp: 143.

Gavilan P; Lorite I J; Tornero S; Berenjena J. 2006. Regional calibration of Hargreaves equation for estimating Reference ET in a semiarid environment. Agric. Water Manage., 81, 257-281.

George B A; Reddy B R S; Raghuwanshi N S; Wallender W W. 2002. Decision support system for estimating reference evapotranspiration. J. Irrig. Drain. Eng., 128(1), 1-10.

Gong C; Xu C Y; Chen D; Halldin S; Chen Y D. 2006. Sensitivity of Penman Monteith reference evapotranspiration to key climatic variables in 400 the Changjiang (Yangtze River) basin. J. Hydrol. (Amsterdam), 329(3-4), 620–629.

Gul S; Ren J; Xiong N; Fawad M. 2022. An effective evapotranspiration estimation scheme based on statistical indicators for sustainable environments in humid and semi-arid area of Khyber Pakhtunkhwa, Pakistan. Water Supply, 22(3), 2493 - 2517. doi:10.2166/ws.2021.457.Hargreaves G H. 1994. Defining and using reference evapotranspiration. J. Irrig. Drain. Eng., 120, 1132- 1139.

Heydari M M; Heydari M. 2014. Calibration of Hargreaves-Samani equation for estimating reference evapotranspiration in semiarid and arid regions. Arch. Agron. Soil Sci., 60(5), 695-713.

Igbadun H; Mahoo H; Tarimo A; Salim B. 2006. Performance two temperature based reference evapotranspiration models in the Mkoji sub-catchment in Tanzania. Agric. Water Manage., 85(1), 141-150.

Irmak S; Irmak A; Allen R G; Jones J W. 2003. Solar and net radiation-based equations to estimate reference evapotranspiration in humid climates. J. Irrig. Drain. Eng., ASCE, 129(5), 336–347.

Islam A; Ahuja L; Garcia L A; Ma L; Saseendran A S. 2012a. Modeling the effect of elevated CO2 and climate change on reference evapotranspiration in the semi-arid Central Great Plains. Trans. ASABE, 55, 2135-2146.

Islam A; Ahuja L; Garcia L A; Ma L; Saseendran A S; Trout T J. 2012b. Modeling the impacts of climate change on irrigated corn production in the Central Great Plains. Agric. Water Manage., 110, 94-108.

Issaka A I; Paek J; Abdella K; Pollanen M; Huda A K S; Kaitibie S; Moustafa A T. 2017. Analysis and calibration of empirical relationships for estimating evapotranspiration in Qatar: Case study.J. Irrig. Drain. Eng., 143(2), 05016013. https://doi.org/10.1061/(ASCE)IR.1943-4774.0001106

Jacobs J M; Satti S R. 2001. Evaluation of Reference Evapotranspiration Methodologies and AFSIRS Crop Water Use Simulation Model (Final Report). St. Johns River Water Management District, Palatka, FL, pp: 114p.

Jensen M E. 1974. Consumptive Use of Water and Irrigation Water Requirements. Rep. Tech. Com. on Irrig. Water Requirements, Irrigation and Drainage Division, ASCE, pp: 227.

Jensen M E; Burman R D; Allen R G. 1990. Evapotranspiration and Irrigation Water Requirements, ASCE Manuals and Reports on Engineering Practice No. 70, pp: 332.

Jensen M E; Haise H R. 1963. Estimating evapotranspiration from solar radiation. J. Irrig. Drain. Eng., 89(IR4), 15-41.

Katsoulas N; Stanghellini C. 2019. Modelling crop transpiration in greenhouses: Different models for different applications. Agron., 9(7), 1-17. Kharrufa N S. 1985. Simplified equation for evapotranspiration in arid regions. Beiträge Hydrol., 5(1), 39-47.

Khoob A R. 2008. Comparative study of Hargreaves’s and artificial neural network’s methodologies in estimating reference evapotranspiration in a semiarid environment. Irrig. Sci., 26(3), 253-259.

Legates D R; McCabe G J Jr. 1999. Evaluating the use of goodness of fit measures in hydrologic and hydroclimatic model validation. Water Resour. Res., 35(1), 233-241.

Lima J R D S; Antonino A C D; Souza E S D; Hammecker C; Montenegro S M G L; Lira C A B D O. 2013. Calibration of Hargreaves-Samani equation for estimating reference evapotranspiration in subhumid region of Brazil. J. Water Resour. Protec., 5, 1-5.

Lu J; Sun G; McNulty S G; Amatya D M. 2005. A comparison of six potential evapotranspiration methods for regional use in the southeastern United States. J. Am. Water Resour. Assoc., 41(3), 621–633.

Makkink G P. 1957. Testing the Penman formula by means of lysimeters. J. Inst. Water Eng., 11, 277–288.

Makwana J J; Deora B S; Parmar B S; Patel C K; Saini A K. 2022. Modelling of reference evapotranspiration using Artificial Neural Network in semi-arid region of North Gujarat. J. Agric. Eng., 59(2), 193-200.

Mallikarjuna P; Jyothy S A; Murthy D S; Reddy K C. 2014. Performance of recalibrated equations for the estimation of daily reference evapotranspiration. Water Resour. Manage., 28, 4513-4535.

Monteith J L. 1965. Evaporation and Environment. Arvind Singh Tomar JAEI : 59 (4) 401 In: Fogg G E (Ed.) Symposium of the Society for Experimental Biology, The State and Movement of Water in Living Organisms, Academic Press Inc., NY, 205-234.

Nandagiri L; Kovoor G M. 2006. Performance evaluation of reference evapotranspiration equations across a range of Indian climates. J. Irrig. Drain Eng., 132(3), 238-249.

NCIWRD. 1995. Integrated Water Resources Development, A Plan for the Action. Report of the National Commission for Integrated Water Resources Development, Ministry of Water Resources, Government of India, Vol. 1, pp: 515.

Oudin L; Michel C; Anctil F. 2005. Which potential evapotranspiration input for a lumped rainfall-runoff model?: Part 2- Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modeling. J. Hydrol., 303(1/4), 290-306.

Page J K; Rodgers G G; Souster C G; Le Sage S A. 1979. Predetermination of Irradiation on Inclined Surfaces for Different European Centres. Final Report No. PB-82-200510, EEC Solar Energy Programme, Project F, Sheffield, Vol. 2, pp: 122.

Pandey P K; Dabral P P; Pandey V. 2016. Evaluation of reference evapotranspiration methods for the north eastern region of India. Int. Soil Water Conserv. Res., 4(1), 52-63.

Paramaguru P K; Mali S S; Shirsath P B. 2022. Impact of gridded weather data sources and its temporal resolution on crop evapotranspiration and effective rainfall of major crops in eastern region of India. J. Agric. Eng., 59(2), 179-192.

Patel J; Patel H; Bhatt C. 2015. Modified Hargreaves equation for accurate estimation of evapotranspiration of diverse climate locations in India. In: Proc. Nat. Acad. Sci. India Section B, Biol. Sci., 85(1), 161-166. Penman H L. 1948. Natural evaporation from open water, bare soil and grass. Math. Phys. Sci., 193, 120- 145.

Poddar A; Gupta P; Kumar N; Shankar V; Ojha C S P. 2021. Evaluation of reference evapotranspiration methods and sensitivity analysis of climatic parameters for sub-humid sub-tropical locations in western Himalayas (India). ISH J. Hydraul. Eng., 27(3), 336-346.

Poyen F B; Kundu P; Ghosh A K. 2018. Temperature based ET method selection for Burdwan district in WB, India. Int. J. Appl. Eng. Res., 13(16), 12753-12763.

Prasad S; Kumar V; Sinha A K; Singh A K P. 2012. Evaluation of Hargreaves method for estimating reference evapotranspiration at Pusa, India. Int. Agric. Eng. J., 21(3-4), 90-95.

Priestley C H B; Taylor R J. 1972. On the assessment of surface heat flux and evaporation using large scale parameters. Mon. Weather Rev., 100, 81-92.

Priya A; Nema A K; Islam A. 2014. Effect of climate change and elevated CO2 on reference evapotranspiration in Varanasi, India - A case study. J. Agrometeol., 16(1), 44-51.

Priya A; Nema A K; Islam A; Sikka A K. 2015. Assessing sensitivity of reference evapotranspiration to changes in climatic variables: A case study of Akola, India. Mausam, 66(4), 777-784.

Ravazzani G; Corbari C; Morella S; Gianoli P; Mancini M. 2012. Modified Hargreaves Samani equation for the assessment of reference evapotranspiration in Alpine River basins. J. Irrig. Eng., 138(7), 592-599.

Rodrigues G C; Braga R P. 2021. Estimation of reference evapotranspiration during the irrigation season using nine temperature-based methods in a hot-summer Mediterranean climate. Agric., 11(124), 11020124. https://doi.org/10.3390/agriculture11020124

Romanenko V. 1961. Computation of the autumn soil moisture using a universal relationship for a large area. In: Proc. Ukrainian Hydrometeorology Research Institute, 3, 12-25.

Samani Z. 2004. Discussion of “History and Evaluation of Hargreaves Evapotranspiration Equation” by Hargreaves G H; Allen R G. J. Irrig. Drain. Eng., 130, 447-448.

Schendel U. 1967. Vegetations Wasserverbrauch und Wasserbedarf. Habilitation, Kiel, pp: 137.

Sharda V N; Sikka A K; Samra J S; Islam A. 2017. Water Harvesting and Recycling: Indian Experiences. Indian Council of Agricultural Research, New Delhi, Deluxe edition, pp. 15.

Sharifi S; Ghaleni M M. 2021. Calibration of empirical equations for estimating reference evapotranspiration in different climates of Iran. Theor. Appl. Clim., 145, 925-931.

Smith M; Allen R G; Monteith J L; Pereira L; Segeren A. 1991. Report of the Expert Consultation on Procedures for Revision of FAO Guidelines for Prediction of Crop Water Requirements. UN-FAO, Rome, pp: 60.

Song X; Lu F; Xiao W; Zhu K; Zhou Y; Xie Z. 2018. Performance of 12 reference evapotranspiration estimation methods compared with the Penman– Monteith method and the potential influences in northeast China. Meteorol. Appl., 26, 83-96.

Srivastava A; Sahoo B; Raghuwanshi N S; Singh R. 2017. Evaluation of variable-infiltration capacity model and MODIS-Terra satellite-derived grid-scale evapotranspiration estimates in a river basin with Tropical monsoon-type climatology. J. Irrig. Drain. Eng., 143(8), 04017028. https://doi.org/10.1061/(ASCE)IR.1943-4774.0001199

Srivastava A; Sahoo B; Raghuwanshi N S; Chatterjee C. 2018. Modelling the dynamics of evapotranspiration using variable infiltration capacity model and regionally calibrated Hargreaves approach. Irrig. Sci., 36, 289–300.

Subburayan S; Murugappan A; Mohan S. 2011. Modified Hargreaves equation for estimation of ET0 in a hot and humid location in Tamilnadu State, India. Int. J. Eng. Sci. Technol., 3(1), 592-600.

Subedi A; Chávez J L. 2015. Crop evapotranspiration (ET) estimation models: A review and discussion of the applicability and limitations of ET methods. J. Agric. Sci., 7, 50-68.

Tabari H and Talaee P H. 2011. Local calibration of the Hargreaves and Priestley-Taylor equations for estimating reference evapotranspiration in arid and cold climates of Iran based on the Penman-Monteith model. J. Hydrol. Eng., 16(10), 837-845.

Tabari H; Talaee P H; Some B. 2013. Spatial modeling of reference evapotranspiration using adjusted Blaney Criddle equation in an arid environment. J. Hydrol. Sci., 58(2), 408-419.

Tahashildar M; Bora P K; Ray L I; Thakuria D. 2017. Comparison of different reference evapotranspiration (ET0 ) models and determination of crop-coefficients of French bean (Phaseolus vulgaris L.) in mid hill region of Meghalaya. J. Agrometeorol., 19(3), 233-237.

Temesgen B; Eching S; Davidoff B; Frame K. 2005. Comparison of some reference evapotranspiration equations for California. J. Irrig. Drain. Eng., 131(1), 73-84.

Thornthwaite C W. 1948. An approach toward a rational classification of climate. Geograph. Rev., 38(1), 55-94.

Tomar A S; Kumar O P. 2015. Performance of radiation-based reference evapotranspiration equations vs FAO56-PM model at sub-humid region of Uttarakhand. Int. J. Res. Advent. Technol., 3(6), 51-57.

Trajkovic S. 2007. Hargreaves versus PenmanMonteith under humid conditions. J. Irrig. Drain. Eng., 133(1), 38-42.

Valiantzas J D. 2013. Simplified forms for the standardized FAO-56 Penman-Monteith reference evapotranspiration using limited weather data. J. Hydrol., 505, 13-23.

Valipour M. 2015a. Investigation of Valiantzas’ evapotranspiration equation in Iran. Theor. Appl. Climatol., 121(1), 267-278.

Valipour M. 2015b. Temperature analysis of reference evapotranspiration models. Meteorol. Appl., 22, 385- 394.

Valipour M. 2017. Calibration of mass transfer-based models to predict reference crop evapotranspiration. Appl. Water Sci., 7(2), 625-635.

Vishwakarma D K; Pandey K; Kaur A; Kushwaha N L; Kumar R; Ali R; Elbeltagi A; Kuriqi A. 2022. Methods to estimate evapotranspiration in humid and subtropical climate conditions. Agric. Water Manage., 261, 107378. https://doi.org/10.1016/j.agwat.2021.107378

Wang Y M; Namaona W; Traore S; Zhang Z C. 2009. Seasonal temperature-based models for reference evapotranspiration estimation under semi-arid condition of Malawi. Afr. J. Agric. Res., 4(9), 878-886.

Willmott C J. 1981. On the validation of models. Phys. Geog., 2, 184-194. Willmott C J. 1982. Some comments on the evaluation of model performance. Am. Meteol. Soc., 63(11), 1309-1312.

Willmott C J. 1984. On the Evaluation of Model Performance in Physical Geography. In: Gaile G L; Willmott C J (Eds.) Spatial Statistics and Models. Theory and Decision Library, Vol. 40. Springer, Arvind Singh Tomar JAEI : 59 (4) 403 Dordrecht. https://doi.org/10.1007/978-94-017-3048- 8_23

Willmott C J; Matsuura K. 2006. On the use of dimensioned measures of error to evaluate the performance of spatial interpolators. Int. J. Geograph. Info. Sci., 20(1), 89-102.

Wright J L. 1982. New evapotranspiration crop coefficients. J. Irrig. Drain. Eng., 108 (IR2), 57-74.

Xu C Y; Singh V P. 2000. Evaluation and generalization of radiation-based methods for calculating evaporation. Hydrol. Process., 14(2), 339-349.

Zacharias S; Heatwole C D; Coakley C W. 1996. Robust quantitative techniques for validating pesticide transport models. Trans. ASAE, 1, 47-54.

Zhang J; Bai Y; Yan H; Guo H; Yang S; Wang J. 2020. Linking observation, modelling and satellite based estimation of global land evapotranspiration. Big Earth Data, 4(2), 94-127.

Published

2022-12-12

Issue

Section

Regular Issue

How to Cite

Arvind Singh Tomar. (2022). Evaluating the Performance of Calibrated Temperature-based Equations as Compared to Standard FAO-56 Penman Monteith Equation in Humid Climatic Condition of Dehradun (India). Journal of Agricultural Engineering (India), 59(4). https://doi.org/10.52151/jae2022594.1790