The regional surface soil heat flux (G0) estimation is very important for the large-scale land surface process modeling. However, most of the regional G0 estimation methods are based on the empirical relationship between G0 and the net radiation flux. A physical model based on harmonic analysis was improved (referred to as “HM model”) and applied over the Heihe River Basin northwest China with multiple remote sensing data, e.g., FY-2C, AMSR-E, and MODIS, and soil map data. The sensitivity analysis of the model was studied as well. The results show that the improved model describes the variation of G0 well. Land surface temperature (LST) and thermal inertia (Γ) are the two key input variables to the HM model. Compared with in situG0, there are some differences, mainly due to the differences between remote-sensed LST and the in situ LST. The sensitivity analysis shows that the errors from −7 to −0.5 K in LST amplitude and from −300 to 300 J m−2 K−1 s−0.5 in Γ will cause about 20% errors, which are acceptable for G0 estimation.
Surface soil heat flux(G0) is an important component of surface energy balance, and it causes large uncertainty in
evapotranspiration estimation. In present study, soil heat flux was calculated at different depths based on the harmonic
analysis method (HM) using field data in Heihe River Basin, northwestern China. The soil heat fluxes at a certain depth
and at the surface were validated by heat-plate measurements and G0 derived from thermal diffusion equation,
respectively. Results showed that HM method obtained good result during the daytime, yet the errors were relatively
large at nighttime mostly due to the assumption of symmetry of G0 during daytime and nighttime. Moreover, a regional
G0 map was provided based on remote sensing data. This study highlighted the simplicity of HM method and its
potential application in large spatial scale mapping. Its internal limit was also discussed here.