The Biome-BGC (biome biogeochemical cycles) model is widely used for modeling the net primary productivity (NPP) of ecosystems. However, this model ignores soil water changes during the freeze-thaw process in permafrost regions, which may lead to considerable errors in the NPP estimations. In this study, we proposed a numerical simulation method for improving soil water during the freeze-thaw process based on the field observation data of soil water and temperature. This approach does not require new parameters and has no impact on other modules. The improvement of soil water content during the freeze-thaw process was then incorporated in the Biome-BGC model for NPP in an alpine meadow in the central Qinghai-Tibetan Plateau (QTP). The results indicated that this method effectively reduced the RMSEs (root mean square errors) of the simulated soil moisture, leaf area index, and NPP, indicating that this approach performs well in the Biome-BGC model. This study suggested that the improvement of soil water content during the freeze-thaw process is also applicable to other models and, thus, could be a useful method to reduce the uncertainty of NPP estimations in permafrost regions.
