Parametric Modelling of Potential Evapotranspiration: A Global Survey

Abstract

Abstract:We present and validate a global parametric model of potential evapotranspiration (PET) with two parameters that are estimated through calibration, using as explanatory variables temperature and extraterrestrial radiation. The model is tested over the globe, taking advantage of the Food and Agriculture Organization (FAO CLIMWAT) database that provides monthly averaged values of meteorological inputs at 4300 locations worldwide. A preliminary analysis of these data allows for explaining the major drivers of PET over the globe and across seasons. The model calibration against the given Penman-Monteith values was carried out through an automatic optimization procedure. For the evaluation of the model, we present global maps of optimized model parameters and associated performance metrics, and also contrast its performance against the well-known Hargreaves-Samani method. Also, we use interpolated values of the optimized parameters to validate the predictive capacity of our model against monthly meteorological time series, at several stations worldwide. The results are very encouraging, since even with the use of abstract climatic information for model calibration and the use of interpolated parameters as local predictors, the model generally ensures reliable PET estimations. Exceptions are mainly attributed to irregular interactions between temperature and extraterrestrial radiation, as well as because the associated processes are influenced by additional drivers, e.g., relative humidity and wind speed. However, the analysis of the residuals shows that the model is consistent in terms of parameters estimation and model validation. The parameter maps allow for the direct use of the model wherever in the world, providing PET estimates in case of missing data, that can be further improved even with a short term acquisition of meteorological data.

Variability of Temperature and Its Impact on Reference Evapotranspiration: The Test Case of the Apulia Region (Southern Italy)

“…The Blaney-Criddle procedure is well known and has been used extensively in other scientific studies [40][41][42][43]. The usual form of the Blaney-Criddle equation converted to metric units is written as:…”

The Uncertainty of Penman‐Monteith Method and the Energy Balance Closure Problem

“…The last type is the Penman‐Monteith (PM) method, also called reference crop evapatranspiration ( ET 0 ), which is a result of multiple factors such as radiation, temperature, and aerodynamics (Allen et al, ). The PM method has been recommended as the standard potential evapotranspiration method by the Food and Agriculture Organization (FAO) and the World Meteorological Organization (WMO) because it is based on the physical mechanism and can be used globally in many regions without requiring the over parameterization (Tegos et al, ; J. Zhang et al, ; Zotarelli et al, ). In addition, a number of continental‐ and global‐scale evaporation models (Chen et al, ; Ferguson et al, ; Mu et al, ) and small‐scale vegetation transpiration models (Cleverly et al, ; Tukimat et al, ) have beenformed on the theoretical basis of the PM method.…”

“…The last type is the Penman-Monteith (PM) method, also called reference crop evapatranspiration (ET 0 ), which is a result of multiple factors such as radiation, temperature, and aerodynamics (Allen et al, 1998). The PM method has been recommended as the standard potential evapotranspiration method by the Food and Agriculture Organization (FAO) and the World Meteorological Organization (WMO) because it is based on the physical mechanism and can be used globally in many regions without requiring the over parameterization (Tegos et al, 2017;J. Zhang et al, 2016;Zotarelli et al, 2016).…”

Spatiotemporal Analysis of Actual Evapotranspiration and Its Causes in the Hai Basin

“…Previous research on spatiotemporal variations has been largely based on meteorological station data [11,26,30,32,34], which may result in misleading spatiotemporal characteristics at the regional scale; however, RS data can be used to explain these variations. Recently, with urbanization [35,36] and landscape changes [37] in China, the water resource crisis has become increasingly severe [38].…”