Open Access Open Access  Restricted Access Subscription Access

Comparative Evaluation of Reference Evapotranspiration Estimation Models In New Bhupania Minor Command, Jhajjar, Haryana, India


Affiliations
1 Division of Agricultural Engineering, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India., India
2 Water Science and Technology, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India., India
3 Division of Agricultural Physics, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India., India
4 Centre for Environment Science and Climate Resilient Agriculture, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India., India
5 ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India., India
 

Accurate quantification of reference crop evapotran-spiration (ETo) plays a significant role in determining crop water requirements in irrigated agriculture. A plethora of methods for the estimation of ETo are available. However, the regional suitability of these methods needs to be assessed given the limited availa-bility of meteorological data. In this study, daily estimates of 11 ETo models were selected and compared with the FAO-Penman–Monteith equation (FAO-PM). The select-ed methods were Blaney–Criddle (BC), Jaisen–Haise (JH), Hargreaves method (HM), McGuinness–Borndne (MB), Chapman (CM), Abtew model (AM), Turc method (TM), FAO-PM equation, Penman equation (PM), Prie-stley–Taylor (PT) and Matt–Shuttleworth (MS). Evalua-tion of these models was carried out during 2016–20 in the New Bhupania Minor Command of the Dulhera dis-tributary, Western Yamuna Canal Command (WYCC), Haryana, India. The selected models were evaluated to find a substitute for the FAO-PM equation based on different statistical indices. It was observed that the PT method performed best and was in line with the FAO-PM equation with correlation coefficient, root mean square error, mean absolute error, Nash–Sutcliffe co-efficient and mean bias error as 0.92, 0.74, 0.48, 0.83, 0.171 respectively. Based on this study and statistical error indices values, the models can be ranked as PT > CM > TM > JH > AM > PM > MS > HM > BC > MB. Thus, we recommend using the PT model for the esti-mation of ETo in the study area with available meteoro-logical parameters for irrigation scheduling.

Keywords

Canal Command, Climatological Data, Comparative Evaluation, Evapotranspiration Estimation Models, Irrigated Agriculture.
User
Notifications
Font Size

  • Pandey, P. K., Dabral, P. P. and Pandey, V., Evaluation of reference evapotranspiration methods for the northeastern region of India. Int. Soil Water Conserv. Res., 2016, 4, 52–63.
  • Shirmohammadi-Aliakbarkhani, Z. and Saberali, S. F., Evaluating of eight evapotranspiration estimation methods in arid regions of Iran. Agric. Water Manage., 2020, 239, 106243.
  • Djaman, K., Koudahe, K., Akinbile, C. O. and Irmak, S., Evaluation of eleven reference evapotranspiration models in semiarid conditions. J. Water Resour. Prot., 2017, 9, 1469–1490.
  • Saggi, M. K. and Jain, S., Reference evapotranspiration estimation and modeling of the Punjab, Northern India using deep learning. Comput. Electron. Agric., 2019, 156, 387–398.
  • Song, X., Lu, F., Xiao, W., Zhu, K., Zhou, Y. and Xie, Z., Performance of 12 reference evapotranspiration estimation methods compared with the Penman–Monteith method and the potential influences in Northeast China. Meteorol. Appl., 2019, 26, 83–96.
  • Allen, R. G. et al., Crop evapotranspiration – guidelines for compu-ting crop water requirements FAO Irrigation and Drainage paper 56. FAO, Rome, Italy, 1998, vol. 300(9), pp. 65–79.
  • Zhao, L. B., Zhao, Y. L. and Jiang, Z. D., Design and fabrication of a piezoresistive pressure sensor for ultra high temperature environ-ment. J. Phys. Conf. Ser., 2006, 48, 178–183.
  • Lang, D. et al., A comparative study of potential evapotranspiration estimation by eight methods with FAO Penman–Monteith method in southwestern China. Water, 2017, 9, 734.
  • Todorovic, M., Karic, B. and Pereira, L. S., Reference evapo-transpiration estimate with limited weather data across a range of Mediterranean climates. J. Hydrol., 2013, 481, 166–176.
  • Gupta, R. and Misra, A. K., Groundwater quality analysis of qua-ternary aquifers in Jhajjar district, Haryana, India: focus on ground-water fluoride and health implications. Alexandria Eng. J., 2018, 57, 375–381.
  • NABARD, District Project Plan. PLP – 2016–17, Jhajjar district, Haryana, 2016; https://www.nabard.org/demo/auth/writereaddata/ tender/2110161208Haryana-StateFocusPaper-2016-17.split-and-mer-ged.pdf
  • Doorenbos, J. and Pruitt, W. O., Guidelines for predicting crop water requirements. FAO Irrigation Drainage Paper, 1977, no. 24, pp. 1–144.
  • Abtew, W., Evapotranspiration measurements and modeling for three wetland systems in South Florida. J. Am. Water Resour. Assoc., 1996, 32, 465–473; https://doi.org/10.1111/k.1752-1688.1996.tb0-4044.x.
  • Jensen, M. E. and Haise, H. R., Estimating evapotranspiration from solar radiation. J. Irrig. Drain. Div., 1963, 89, 15–41.
  • Hargreaves, G. H. and Samani, Z. A., Reference crop evapotrans-piration from temperature. Appl. Eng. Agric., 1985, 1, 96–99.
  • Turc, L., Water requirements assessment of irrigation, potential evapotranspiration: simplified and updated climatic formula. Ann. Agronom., 1961, 12, 13–49.
  • Penman, H. L., Natural evaporation from open water, bare soil and grass. Proc. R. Soc. London, Ser. A, 1948, 193, 120–145.
  • Feddes, R. A. and Lenselink, K. J., Evaporation from Open Water: The Penman Method. Drainage Principles and Application (ed. Ritzema, H. P.), International Institute for Land Reclamation and Improvement, The Netherlands, pp. 145–172.
  • Bapuji Rao, B., Sandeep, V. M., Rao, V. U. M. and Venkateswarlu, B., Potential Evapotranspiration estimation for Indian conditions: Improving accuracy through calibration coefficients. Tech. Bull. No 1/2012. All India Co-ordinated Research Project on Agromete-orology, Central Research Institute for Dryland Agriculture, Hy-derabad, 2012, p. 60.
  • Allen, R. G. and Pruitt, W. O., FAO-24 reference evapotranspira-tion factors. J. Irrig. Drain. Eng., 1991, 117, 758–773.
  • Chapman, T. G., Estimation of evaporation in rainfall-runoff mod-els. In Proceedings MODSIM 2003. International Congress on Modelling and Simulation, Modelling and Simulation Society of Australia, 2003, vol. 1, pp. 148–153.
  • Shuttleworth, W. J. and Wallace, J. S., Calculating the water requi-rements of irrigated crops in Australia using the Matt–Shuttleworth approach. Trans. ASABE, 2009, 52(6), 1895–1906.
  • Khan, R., Ali, I., Asif Suryani, M., Ahmad, M. and Zakarya, M., Wireless sensor network based irrigation management system for container grown crops in Pakistan. World Appl. Sci. J., 2013, 24, 1111–1118.
  • Lhomme, J. P., Boudhina, N. and Masmoudi, M. M., Technical note: on the Matt–Shuttleworth approach to estimate crop water requi-rements. Hydrol. Earth Syst. Sci., 2014, 18, 4341–4348.
  • Oudin, L. et al., Which potential evapotranspiration input for a lumped rainfall-runoff model? Part 2 – towards a simple and effi-cient potential evapotranspiration model for rainfall-runoff modelling. J. Hydrol., 2005, 303, 290–306.
  • McGuinness, J. L. and Bordne, E. F., A Comparison of Lysimeter-derived Potential Evapotranspiration with Computed Values, US Department of Agriculture, 1972.
  • Singh, P., Sarangi, A., Singh, D. K., Sehegal, V. K., Dash, S. and Chakrabarti, B., Performance evaluation of evapotranspiration esti-mation methods in Sultanpur, Uttar Pradesh, India. Indian J. Agric. Sci., 2021, 91, 421–425.
  • Borah, R. S. M. K., Comparative evaluation of different reference evapotranspiration estimation methods for Lakhimpur district of Assam, India. Int. J. Sci. Res., 2017, 6, 2162–2168.
  • Heydari, M. M., Aghamajidi, R., Beygipoor, G. and Heydari, M., Comparison and evaluation of 38 equations for estimating reference evapotranspiration in an arid region. Fresenius Environ. Bull., 2014, 23, 1985–1996.
  • Xu, C. Y. and Chen, D., Comparison of seven models for estimation of evapotranspiration and groundwater recharge using lysimeter measurement data in Germany. Hydrol. Process., 2005, 19, 3717– 3734.
  • Patle, G. T. and Singh, D. K., Sensitivity of annual and seasonal reference crop evapotranspiration to principal climatic variables. J. Earth Syst. Sci., 2015, 124(4), 819–828.
  • Efthimiou, N., Alexandris, S., Karavitis, C. and Mamassis, N., Comparative analysis of reference evapotranspiration estimation between various methods and the FAO-56 Penman–Monteith procedure. Eur. Water, 2013, 42, 19–34.
  • Chowdhury, A., Gupta, D., Das, D. P. and Bhowmick, A., Compari-son of different evapotranspiration estimation techniques for Mohan-pur, Nadia District, West Bengal. Int. J. Comput. Eng. Res., 2017, 7(4), 33–39.
  • Zheng, H. et al., Assessing the ability of potential evapotranspi-ration models in capturing dynamics of evaporative demand across various biomes and climatic regimes with ChinaFLUX measure-ments. J. Hydrol., 2017, 551, 70–80.
  • Liu, X., Xu, C., Zhong, X., Li, Y., Yuan, X. and Cao, J., Comparison of 16 models for reference crop evapotranspiration against weighing lysimeter measurement. Agric. Water Manage., 2017, 184, 145–155.

Abstract Views: 148

PDF Views: 84




  • Comparative Evaluation of Reference Evapotranspiration Estimation Models In New Bhupania Minor Command, Jhajjar, Haryana, India

Abstract Views: 148  |  PDF Views: 84

Authors

Venkatesh Gaddikeri
Division of Agricultural Engineering, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India., India
A. Sarangi
Water Science and Technology, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India., India
D. K. Singh
Division of Agricultural Engineering, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India., India
K. K. Bandyopadhyay
Division of Agricultural Physics, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India., India
Bidisha Chakrabarti
Centre for Environment Science and Climate Resilient Agriculture, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India., India
S. K. Sarkar
ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India., India

Abstract


Accurate quantification of reference crop evapotran-spiration (ETo) plays a significant role in determining crop water requirements in irrigated agriculture. A plethora of methods for the estimation of ETo are available. However, the regional suitability of these methods needs to be assessed given the limited availa-bility of meteorological data. In this study, daily estimates of 11 ETo models were selected and compared with the FAO-Penman–Monteith equation (FAO-PM). The select-ed methods were Blaney–Criddle (BC), Jaisen–Haise (JH), Hargreaves method (HM), McGuinness–Borndne (MB), Chapman (CM), Abtew model (AM), Turc method (TM), FAO-PM equation, Penman equation (PM), Prie-stley–Taylor (PT) and Matt–Shuttleworth (MS). Evalua-tion of these models was carried out during 2016–20 in the New Bhupania Minor Command of the Dulhera dis-tributary, Western Yamuna Canal Command (WYCC), Haryana, India. The selected models were evaluated to find a substitute for the FAO-PM equation based on different statistical indices. It was observed that the PT method performed best and was in line with the FAO-PM equation with correlation coefficient, root mean square error, mean absolute error, Nash–Sutcliffe co-efficient and mean bias error as 0.92, 0.74, 0.48, 0.83, 0.171 respectively. Based on this study and statistical error indices values, the models can be ranked as PT > CM > TM > JH > AM > PM > MS > HM > BC > MB. Thus, we recommend using the PT model for the esti-mation of ETo in the study area with available meteoro-logical parameters for irrigation scheduling.

Keywords


Canal Command, Climatological Data, Comparative Evaluation, Evapotranspiration Estimation Models, Irrigated Agriculture.

References





DOI: https://doi.org/10.18520/cs%2Fv124%2Fi10%2F1181-1187