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The major undetermined problem in evaporation (ET) retrieval using thermal infrared (TIR) remote sensing is the lack of a physically based ground heat flux (G) model and its amalgamation with surface energy balance (SEB) model. Here, we present a novel approach based on coupling a thermal inertia (TI)-based mechanistic G model with an analytical SEB model (Surface Temperature Initiated Closure) (STIC, version STIC1.2). The coupled model is named as STIC-TI and it uses noon-night land surface temperature (TS), surface albedo and vegetation index from MODIS Aqua in conjunction with a clear-sky net radiation model and ancillary meteorological information. The SEB flux estimates from STIC-TI were evaluated with respect to the in-situ fluxes from Eddy Covariance (EC) measurements in diverse agriculture and natural ecosystems of contrasting aridity in the northern hemisphere (e.g., India, United States of America) and southern hemisphere (e.g., Australia). Sensitivity analysis revealed substantial sensitivity of the STIC-TI derived fluxes due to TS uncertainty and partial compensation of sensitivity of G to TS due to the nature of the equations used in the TI-based G model. An evaluation of STIC-TI G estimates with respect to in-situ measurements showed an error range of 12-21% across six flux tower sites in both the hemispheres. A comparison of STIC-TI G estimates with other G models revealed substantially better performance of the former. While the instantaneous noontime net radiation (RNi) and latent heat flux (LEi) was overestimated (15% and 25%), sensible heat flux (Hi) was underestimated with error of 22%. The errors in Gi were associated with the errors in daytime TS and mismatch of footprint between the model estimates and measurements. Overestimation (underestimation) of LEi (Hi) was associated with the overestimation of net available energy (RNi - Gi) and use of unclosed SEB measurements. Being independent of any leaf-scale conductance parameterization and having a coupled sub-model of G, STIC-TI can make valuable contribution to map and monitor water stress and evaporation in the terrestrial ecosystems using noon-night thermal infrared observations from existing and future EO missions such as INSAT 4th generation and TRISHNA. [ABSTRACT FROM AUTHOR]