Performance of Different Surface Incoming Solar Radiation Models and Their Impacts on Reference Evapotranspiration

Abstract

Reference evapotranspiration (ET 0 ) from FAO-Penman-Monteith equation is highly sensitive to the surface incoming solar radiation (SISR) and therefore accurate estimate of this parameter would result in more accurate estimation of ET 0 . In this study, the accuracy of three main approaches for SISR estimation including empirical models (Angstrom and Hargreaves-Samani), physically-based data assimilation models (Global Land Data Assimilation System-Noah, GLDAS/Noah, and National Centers of Environmental Predictions/National Center for Atmospheric Research, NCEP/NCAR), and a satellite observation model (Satellite Application Facility on Climate Monitoring, CM-SAF) were evaluated using ground-based measurements from 2012 to 2015. Then SISR outputs from introduced approaches were implemented in FAO-Penman-Monteith equation for ET 0 estimation on daily and monthly basis. The Angstrom calibrated model was the most accurate model with a coefficient of determination (R 2 ) of 0.9 and standard error of estimate (SEE) of 2.58 MJ. m −2 . d −1 , and GLDAS/Noah, Hargreaves-Samani, NCEP/NCAR, and CM-SAF, had lower accuracy, respectively. However, the lack of the meteorological data and required empirical coefficients are the main limitations of applying the empirical models, however, satellite-based approaches are more practical for operational purposes. The results indicated that, in spite of slight overestimation in warm months, GLDAS/Noah model had better performance with R 2 =0.87 and SEE = 3.5 MJ. m −2 . d −1 in case of lack of meteorological data. The accuracy of ET 0 derived from FAO-Penman-Monteith equation was directly depended on the accuracy of SISR estimation. The ET 0 estimation error was related to SISR estimation error with a fourth-degree function and had a linear relationship with SISR error at daily and monthly scales, respectively.

Characteristics and Drivers of Reference Evapotranspiration in Hilly Regions in Southern China

“…The average reference evapotranspiration for several years was 1284 mm, with its highest value in 2013 (indicating a surface evapotranspiration peak) and lowest value in 1952 (indicating the lowest point in surface evapotranspiration). Although average reference evapotranspiration had seen increments and reductions over 5 years, it revealed an overall fluctuating and rising trend, and it increased significantly in 2001, mainly due to the increase in solar radiation after 2001, resulting in significant fluctuations in temperature and evapotranspiration [35]. Figure 4 shows the seasonal changes and annual average change in reference evapotranspiration in the hilly regions in southern China over the last 63 years.…”

How Ångström–Prescott Coefficients Alter the Estimation of Agricultural Water Demand in South Korea

“…There can be many uncertainties associated with the use of the P-M equation other than those concerning the A-P coefficients [29][30][31]. However, as shown in the results of this study, the use of A-P coefficients can cause considerable uncertainty in estimating ET 0 using the P-M equation and its applications.…”

Land Cover Changes Implications in Energy Flow and Water Cycle in São Francisco Basin, Brazil, over the Past Seven Decades

“…Investigating Earth's energy and water cycle is essential to understand global climate dynamics and how it impacts and is in uenced by human actions (Seyoum and Milewski, 2017;Umair et al, 2019). The terrestrial climate is susceptible to radiation ows, both those of short-wave originating from solar activities and those of long-wave from solar rays' irradiation on the planet's surface (Mokhtari et al, 2018;Yan et al, 2020;Yang et al, 2017).…”

“…In addition to the intensity of solar activities, the balance of terrestrial radiation will depend on atmosphere composition, land cover, relief, and the amount of surface water present in the upper lithosphere (Jiang et al, 2021;Mokhtari et al, 2018;Yan et al, 2020). It is already known, therefore, that the energy ux on Earth will depend on the interaction between its various spheres (Atmosphere, Lithosphere, Hydrosphere and Biosphere).…”