Climate change has been shown to directly influence evapotranspiration, which is one of the crucial watershed processes. The common approach to its calculation is via mathematical equations, such as 1985… Click to show full abstract
Climate change has been shown to directly influence evapotranspiration, which is one of the crucial watershed processes. The common approach to its calculation is via mathematical equations, such as 1985 Hargreaves-Samani (HS85). It computes reference evapotranspiration (ETo) through three climatic variables and one constant: RA (extra-terrestrial radiation), TC (mean temperature), TR (temperature range) and KR (empirical coefficient). To make HS85 more accurate, one of its authors proposed an equation for KR as a function of TR in 2000 (HS00). Both models are 4D and their internal behaviours are difficult to understand, hence, the data driven applications prevalent among experts and managers. In this study, we introduce an innovative research by trying to respond to two questions. What are the relationships between TC and TR? What are the internal patterns of HS hyperspace (4D domain) and the changes in ETo possibilities of the two models? In the proposed approach, thresholds for the four variables are utilized to cover majority of the agroclimatic situations in the world and the hyperspace is discretized with more than 50,000 calculation nodes. The ETo results show that under various climatic conditions, the behaviour of HS is nonlinear (more for HS00) leading to an increased uncertainty particularly for data driven applications. TC and TR show patterns useful for regions with less data.
               
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