Accuracy of five ground heat flux empirical simulation methods in the surface-energy-balance-based remote-sensing evapotranspiration models

Based on the assessment from 230 flux site observations, intra-day and daytime ground heat flux (G) accounted for 19.2 % and 28.8 % of the corresponding net radiation, respectively. This indicates that G plays an important role in remote-sensing (RS) energy-balance-based evapotranspiration (ET) models. The G empirical estimation methods have been evaluated at many individual sites, while there have been relatively few multi-site evaluation studies. The accuracy of the five empirical G simulation methods in the surface-energy-balance-based RS-ET models was evaluated using half-hourly observations. The linear coefficient (LC) method and the two methods embedded with the normalized difference vegetation index (NDVI) were able to accurately simulate a half-hourly G series at most sites. The mean and median Nash-Sutcliffe efficiency (NSE) values of all sites were generally higher than 0.50 in each half-hour period. The accuracy of each method varied significantly at different sites and at half-hour intervals. The highest accuracy was exhibited during 06:00-07:00 LST (all times hereafter are LST), followed by the period of 17:00-18:00. There were 92 % (211/230) sites with an NSE of the LC method greater than 0.50 at 06:30. It showed a slightly higher accuracy during nighttime periods than during daytime periods. The lowest accuracy was observed during the period of 10:00-15:30. The sites with an NSE exceeding 0.50 only accounted for 51 % (118/230) and 43 % (100/230) at 10:30 and 13:30, respectively. The accuracy of the model was generally higher in Northern Hemisphere sites than in Southern Hemisphere sites. In general, the highest and lowest accuracies were observed at the high- and low-latitude sites, respectively. The performance of the LC method and the methods embedded with NDVI were generally satisfactory at the Eurasian and North American sites, with the NSE values of most sites exceeding 0.70. Conversely, it exhibited relatively poor performance at the African, South American, and Oceanian sites, especially the African sites. Both the temporal and spatial distributions of the accuracy of the G simulation were positively correlated with the correlation between G and the net radiation. Although the G simulation methods accurately simulated the G series at most sites and time periods, their performance was poor at some sites and time periods. The application of RS ET datasets covering these sites requires caution. Further improvement of G simulations at these sites and time periods is recommended for the RS ET modelers. In addition, variable parameters are recommended in empirical methods of G simulation to improve accuracy. Instead of the Rn, finding another variable that has a physical connection and strong correlation with G might be a more efficient solution for the improvement, since the weak correlation between G and Rn is the main reason for the poor performance at these regions.