The objective of this study is to investigate how the complementarity between microwave and thermal infrared remote sensing can be exploited for a high‐resolution near‐surface freeze/thaw state estimation. The basic idea is to establish a feasible relationship between the microwave‐derived freeze/thaw state and thermal infrared observations. A quantitative freeze/thaw index from microwave observations at 18.7 and 36.5 GHz is innovatively defined and is assumed to be linearly correlated with land surface temperature from thermal infrared observations. Thus, a linear regression method is proposed and verified to be effective over a multiscale network of Naqu of the Tibetan Plateau. In order to demonstrate the potentiality of the proposed method, it is implemented in the entire Tibetan Plateau. It is found that the linear relationship is quite reliable for most areas and can obtain a high‐resolution near‐surface soil freeze/thaw state with integrated information from microwave and thermal infrared remote sensing. The validation of the high‐resolution freeze/thaw state against soil temperature measured at active layer monitoring sites along the Qinghai‐Tibet Highway illustrates a moderate accuracy over a decade scale. This study provides new insights for high‐resolution freeze/thaw mapping beyond the Soil Moisture Active Passive mission.

Watershed runoff is essential for water management. However, runoff materials are lacking in poorly gauged catchments and not always accessible. Microwave remote sensing offers emerging capabilities for hydrological simulation. In this study based on multi-satellite retrievals for Global Precipitation Measurement (IMERG), Tropical Rainfall Measuring Mission (TRMM) products, and World Meteorological Organization (WMO) interpolated precipitation data, we simulated runoff using a variable infiltration capacity (VIC) model and studied the differences among the results. Then, we analyzed the impacts of the runoff on a moderate-resolution imaging spectroradiometer vegetation leaf area index (LAI) during dry seasons. The results showed that (1) IMERG V5 and TRMM products are capable of monitoring the night-day rainfall diurnal cycle and have higher correlations than the WMO daily observation interpolations. However, the WMO shows less overestimation of total precipitation than remote-sensing precipitation; (2) in the downstream, the TRMM shows better runoff simulation accuracy in the tributaries, and the WMO shows better results in the mainstreams. Therefore, at basin outlets in mainstreams, the Nash–Sutcliffe efficiency coefficients of monthly runoff by the WMO are higher than the simulations by the TRMM; (3) for the whole basin during dry seasons, the LAI variation is correlated with the outlet runoff, which is similar to the correlation with three- to six-month accumulated precipitation. TRMM products can be used to depict both precipitation deficit and runoff deficit, which cause vegetation variations. Our research suggests the potential of microwave precipitation products for detailed watershed runoff simulations and water management.