CALIBRATION OF TWO MODELS FOR ESTIMATING REFERENCE EVAPOTRANSPIRATION BY USING FAO-56 PENMAN-MONTEITH MODEL UNDER ARID CONDITIONS
Journal: Engineering Heritage Journal (GWK)
Author: Ahmed Bin Abdullah Al-Dughairi, Mohamed Foudil Bourouba
This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
The Penman-Monteith method (P-M) to estimate the reference evapotranspiration (ETo) is the most reliable method and recommended by the FAO as the standard to verify other empi- rical methods. However, the Thornthwaite (Th) and Hargreaves-Samani (H-S) models are widely used because they are based on measurements of air temperature, frequently recorded in any meteorological stations. In this study, the daily meteorological parameters of air temperature, relative humidity, wind velocity, were available at six stations (Riyadh), (Ha’il), (Tabuk), (Turayf), (Makkah) and (Jazan). The net radiation was computed using a mathematical model based on a serie of related equations. Therefore, the application of Penman-Monteith became possible to calibrate the Thornthwaite and Hargreaves-Samani models. The local calibration of the both models (Th and H-S) in arid conditions is based on modifying the original coefficients of the named models using the ratio for estimated ET (Th and H-S mpdels) and the reference ETo of (P-M model). In the comparison, the indices of concordance (D), confidence (C), correlation coefficient (r) were analyzed, together with the root mean square error (RMSE) and Nash-Stucliff Efficiency (NSE). So, the ET of H-S model without adjustment were greater than the ETo of P-M during all the months at the total of the studied stations. Contrary, the use of non-adjusted Th ET show a smaller values of the monthly average in a total of the selected stations. After adjustment of the original coefficients of (0.0023) for H-S model and (1.6) for the Th model, we can obtain the new equations of estimating the monthly average of ET fitting better with the P-M Eto model.