A novel multi-scale parameter estimation approach to the Hargreaves-Samani equation for estimation of Penman-Monteith reference evapotranspiration.
The main focus of this study is to develop a multi-scale surrogate model for the FAO-56 Penman-Monteith (PM) evapotranspiration using Hargreaves-Samani (HS) equation, which uses only temperature as a hydrometeorological variable to estimate ET. This feature is particularly useful for scarce data regions and climate change impact assessment studies, where the direct estimation of from the PM equation can be problematic. As the parameters of the HS equation may vary across space, a Bayesian approach was adopted to estimate (or recalibrate) them rather than relying on the fixed values as suggested in the traditional model. The proposed and reference models are applied and tested using meteorological data from 17 stations located across the Han river basin in South Korea. The results indicate that the traditional HS equation with fixed parameters and without reca
libration tends to overestimate the ET0 for all stations. In contrast, the proposed multi-scale surrogate model offers a more precise estimation of the ET0 at a daily timescale as well as at the aggregated monthly and annual temporal scales.
