Calibration and Performance Verification of Hargreaves Samani Equation in a Humid Region

Abstract

The Hargreaves Samani (HS) equation is one of the most promising approaches for estimation of reference evapotranspiration under data-scarce conditions. Many modifications of the HS equation have been performed under different climatic conditions using different approaches to improve the precision of the evapotranspiration (ET 0 ) estimates for use at different locations; the results have not been consistent.The purpose of this study was to review and to evaluate the two most promising parameters used for the calibration of the HS evapotranspiration equation, under the climatic conditions of Gangtok, East Sikkim, India. The calibration was based on solar radiation and temperature difference. The equation was calibrated for solar radiation coefficient, C H first and then for temperature constant, T H and temperature exponent, E H to estimate the extent of improvement in estimation. The resulting modification shows a significant reduction in error. When only C H is modified, the percentage bias error (PBIAS) value was reduced from 23.3 to 0.8%, 26.1 to 10.19% and 30.1 to 3.6% for daily, weekly and monthly scales respectively. Consistent results for all three time spaces were observed, when, C H = 0.001 and T H = 13.9 and E H = 0.56. The PBIAS value was À1.9, 7.7 and 1.3% respectively for the three time spans, with index of agreement near to 1. The proposed equation may be an alternative to the Penman-Monteith method under limiting data conditions.

Three decades of reference evapotranspiration estimates for a tropical watershed in the eastern Amazon

“…This model has been validated in relation to the data measured by lysimeters under various climatic conditions. For this reason, it has been considered the best method to estimate ETo and is widely used as a standard for comparison with other empirical methods (Allen et al 2005, 1998, ASCE-EWRI 2005, Berti et al 2014, Djaman et al 2015, Dehghani Sanij et al 2004, Ghamarnia et al 2015, Itenfisu et al 2003, Jain et al 2008, Lima et al 2013, Pandey et al 2014, Pereira et al 2015, Tabari et al 2013, Widmoser 2009, Mohan and Arumugam 1996. Empirical or deterministic models with a physical basis, with or without random or probabilistic components, are used to calculate ETo (Soares et al 2003, Borges andMendiondo 2007).…”

Ajuste Dos Parâmetros Do Modelo De Hargreaves E Samani Para Estimativa Da Evapotranspiração De Referência Em Escala Diária Para Maceió-Al

“…O ajuste de parâmetros deste modelo deve ser realizado principalmente em regiões úmidas, pois, os maiores erros registrados deste método são para tais condições, que ocorrem principalmente em regiões litorâneas ou com altitude elevada (RAVAZZANI et al, 2012;TABARI et al, 2013;PANDEY et al, 2014;FENG et al, 2016). Este trabalho teve como objetivo ajustar a equação de Hargreaves e Samani (1985) de três formas distintas e analisar qual modelo ajustado obteve a melhor estimativa da ETo para a cidade de Maceió-AL.…”

Creating long-term gridded fields of reference evapotranspiration in Alpine terrain based on a recalibrated Hargreaves method

“…The HM is calibrated to the PM in a station-wise assessment. Many studies describe recalibration procedures for ET0 estimations in general (Tegos et al, 2015;Oudin et al, 2005) and for the HM in particular (Pandey et al, 2014;Tabari and Talaee, 2011;Bautista et al, 2009;Gavilán et al, 2006) in order to achieve results comparable to PM. There are also some studies describing methods for creating interpolated ET0 estimates (e. g. Aguila and Polo, 2011;Todorovic et al, 2011).…”