Framework for Standardizing Less Data-Intensive Methods of Reference Evapotranspiration Estimation

Abstract

Evapotranspiration is one of the vital components of water cycle and its accurate estimation is the key to sustainable management of irrigation water. The FAO Penman-Monteith (FAO-PM) method is recommended as the standard method for computing reference evapotranspiration (ETo) as well as for evaluating other indirect methods. However, due to the lack of weather data such as radiation, relative humidity and wind speed in many regions of the world, especially in developing countries, the FAO-PM method is difficult to use. To address this issue, a fairly robust methodology is proposed in this study to standardize two popular less data-intensive (temperature-based) ETo methods, viz., Hargreaves-Samani (HS) and Penman-Monteith Temperature (PMT) against the FAO-PM method. To achieve this goal, the daily and monthly biases of these two methods were adjusted using the weather data of 14 locations for the 1979–2003 period. Subsequently, the performance of the standardized (de-biased) less data-intensive methods were verified using salient statistical and graphical indicators for the 2004–2013 period. The results indicated that the HS and PMT methods underestimate ETo on a monthly time step by 9.62 and 14.77%, respectively. However, the performances of these methods significantly improve after the standardization. The estimates of ETo by the standardized less data-intensive methods were found to be in close agreement with those by the standard FAO-PM method, thereby suggesting the usefulness and applicability of the proposed framework in data-scarce situations irrespective of agro-climatic conditions.