The Qinghai-Tibetan Plateau (QTP), named the Asian Water Towers, feeds more than 2.5 billion people in downstream regions. It is still unknown how much water outflows from this region owing to lack of observations. The main objective of this study is to clarify availability of water flowed out of this region and is contribution to large Asian rivers. The Global Land Data Assimilation System (GLDAS) products are evaluated with the help of observations of the QTP. In addition, a velocity-based Fouling method is embedded into the GLDAS model W route runoff products W the basin outlet in this study. The results show that the simulated dry season runoff in the GLDAS model is generally lower than the observed value, which is mainly because most hydrological models only consider the potential evapotranspiration (ET) when simulating ET, while ignoring the water constraint factor. Noah I 0 v2.0 has the highest precision at the QTP. For the monthly precipitation and runoff series, the relative error is within 5%, the correlation coefficient is greater than 0.90, and the Nash -Sutcliffe efficiencies are 0.95 and 0.76, respectively. Glacier melt runoff plays an important role in the QTP runoff, with a proportion of approximately 22%. It is relatively high in the Tarim River basin (83%), Syr Darya River and Amu Darya River basins (69%), and Indus River basin (60%,). The contribution ratio also reaches 23% in the Yarlung ZangboBrahmaputra River and Ganges River basins, whereas it is the lowest in the Irrawaddy River basin (2%,). According W the NoahlO_v2.0 simulations, the mean annual runoff provided by the QTP exceeds 620 billion cubic metres, of which approximately 440 billion cubic metres flow out of the QTP and supply downstream regions of international rivers. The contribution ratio of the QTP runoff to the total runoff of its affected basins is approximately 16%. (C) 2020 The Authors. Published by Elsevier B.V.

The upper Nu-Salween River basin in the Tibetan Plateau is mainly covered with seasonal frozen soils. We used daily surface freeze-thaw states, detected from Special Sensor Microwave/Imager (SSM/I) daily brightness temperature data, to analyze the variations in surface freeze-thaw states and the relationship with air temperature. We also examined baseflow to explore the influences of interannual variations in the start time of soil freezing on hydrological processes. The results showed that (1) interannual air temperature fluctuations led to differences in the area and start time of surface freezing. When surface soil froze, flow was mainly dependent on existing groundwater storage. (2) The interannual variation in the surface freezing time directly affected the flow generation processes. When soil water froze and remained in the frozen layer, it was hard to generate surface flow, so flow mainly consisted of baseflow, causing the proportion of the baseflow in the total flow to gradually increase. (3) The surface freeze-thaw states obtained from the passive microwave remote sensing data may be applied to support further research on the hydrological impacts of freeze-thaw cycle variations in plateau mountain basins.