Improved thermal conductivity parameterization of SHAW model in permafrost regions on the Qinghai-Tibet Plateau

Soil thermal conductivity is critical for determining the hydrological and energy transfer processes in permafrost regions and simulating hydrological and thermal dynamic processes with land surface models. In this study, improved thermal conductivity parameterizations of the Simultaneous Heat and Water model (SHAW) were assessed using observation data from permafrost regions on the Qinghai-Tibet Plateau (QTP). The results indicated that the SHAW could precisely describe soil hydrological and thermal processes at the Tanggula (TGL) site. In general, the performances of Johansen's, Luo's, and the ORCHIDEE-MICT model's soil organic matter (SOM) parameterizations were superior to the original De Vries's parameterization. The SOM parameterization per-formed the best. The root mean square error (RMSE) of the active layer's soil temperature was 0.42 degrees C lower than that of the original parameterization at the Xidatan (XDT) site and 0.2 degrees C lower at the TGL site. In particular, the RMSE of the soil temperature at 3 m depth at TGL was 0.8 degrees C lower than that of the original parameterization. The average Nash-Sutcliffe Efficiency (NSE) for simulating the active layer soil temperature using the SOM parameterization was 0.915 at TGL site and 0.806 at XDT site. While De Vries parameterization yielded average NSE values of 0.771 and 0.627 for soil temperature simulations at the two sites, respectively. The results indicate that the soil organic carbon cannot be ignored in the simulation of hydrological and thermal processes in permafrost areas with a high soil organic carbon content. Notably, the simulated soil temperatures during the freezing period and the soil liquid water content during the thawing period improved significantly after modifying the thermal conductivity parameterization of SHAW. Therefore, the revised SHAW more accurately reflects the water and heat transfer processes of permafrost and can be used to analyze land-atmosphere interactions.