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Estimating Reference Evapotranspiration by Hargreaves and Blaney-Criddle Methods in Humid Subtropical Conditions

Author

Listed:
  • Muhammad Hafeez
  • Zia Ahmad Chatha
  • Alamgir Akhtar Khan
  • Allah Bakhsh
  • Abdul Basit
  • Fatima Tahira

Abstract

Various methods are available to predict reference evapotranspiration (ETo) but the Penman-Monteith (PM) ETo method has been considered to be the most accurate ETo method to determine ETo. The PM ETo method can be solved by various weather parameters like atmospheric temperature, wind velocity, moisture content and net solar radiations. There are many weather stations in the world that have no complete set of weather parameters to predict ETo by applying PM ETo method. So alternative ETo methods like Hargreaves (HG) and Blaney-Criddle (BC) ETo methods are used which need only a fewer number of weather parameters. In this paper, two ETo methods, HG and BC are compared with PM ETo method in humid subtropical climatic conditions of Islamabad and Kakul (Abbottabad) weather stations. The study indicate that HG ETo method overestimated PM ETo method by 23.78% at Islamabad weather station and 28.47% at Kakul station. The BC ETo method overestimated PM ETo method by 37.93% at Islamabad weather station and by 22.68% at Kakul weather station. The dissimilarity of HG ETo method with PM ETo method with RMSE was 1.09 mm/day at Islamabad weather station and 1.17 mm/day at Kakul weather station. The dissimilarity of BC ETo method with PM ETo method has Root Mean Square Error (RMSE) of 2.86 mm/day at Islamabad weather station and 1.48 mm/day at Kakul weather station.

Suggested Citation

  • Muhammad Hafeez & Zia Ahmad Chatha & Alamgir Akhtar Khan & Allah Bakhsh & Abdul Basit & Fatima Tahira, 2020. "Estimating Reference Evapotranspiration by Hargreaves and Blaney-Criddle Methods in Humid Subtropical Conditions," Current Research in Agricultural Sciences, Conscientia Beam, vol. 7(1), pages 15-22.
    • Handle: RePEc:pkp:criasc:v:7:y:2020:i:1:p:15-22:id:130
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    Cited by:

    1. Junaid Maqsood & Aitazaz A. Farooque & Farhat Abbas & Travis Esau & Xander Wang & Bishnu Acharya & Hassan Afzaal, 2022. "Application of Artificial Neural Networks to Project Reference Evapotranspiration Under Climate Change Scenarios," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(3), pages 835-851, February.

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