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The streamflow on the Tibetan Plateau (TP) plays an important role in the water supply of Asia's main river basins. To enhance understanding of hydrologic cycle under the pronounced warming over the TP, this study comprehensively investigates the streamflow changes at the upstream of six major rivers (Yellow River, Yalong River, Jinsha River, Lancang River, Nu River, and Yarlung Zangbo River) originating from the TP, and then diagnoses their possible causes by analysing the impacts of climate variability and human activities. Results indicate that these six major rivers studied have generally insignificant increasing trends in annual streamflow during the last half century, except for two stations. The significant increase appears at the Tuotuohe station in the headwater area of Jinsha River, while the dramatic decrease occurs at the Yunjinghong station in the downstream of Lancang River. In terms of climate factors, the six river basins show a distinct warming trend, along with a noticeable increase in precipitation over the central and northern regions. Pan evaporation, wind speed, sunshine duration, and relative humidity have been found to gradually decrease in most areas. As for the Tuotuohe station, both warming‐induced meltwater and increasing precipitation might jointly contribute to the increasing streamflow. But for the Yunjinghong station, the results simulated by the Variable Infiltration Capacity (VIC) model indicate that human activities, especially for the impoundment processes of Xiaowan and Nuozhadu dams, significantly influenced the streamflow, contributing to approximately 69% of the streamflow reduction during 2009–2013. In the context of accelerated global warming, greater attention should be paid to hydrometeorological changes on the TP to offer further insights for the water resources management of the 'Asian Water Tower'. [ABSTRACT FROM AUTHOR]

Terrestrial water storage (TWS) is of great importance to the global water and energy budget, which modulates the hydrological cycle and then determines the spatiotemporal distributions of water resources availability. The Tibetan Plateau is the birthplace of the Yangtze, Yellow, and Lancang–Mekong River, where the water resources are directly related to the life of the Eastern and Southeastern Asian people. Based on multi-source datasets during the period 1981–2015, the long-term spatiotemporal variabilities of the TWS over the Tibetan Plateau were investigated by the Sen's slope and Mann–Kendall test trend analysis methods; the changing mechanisms were explored from two perspectives of components analysis and the hydrological cycle. The water conservation capacity of vegetation in the alpine mountainous areas was also discussed by geostatistical methods such as correlation analysis, extracted by attributes and zonal statistics. The results show that the TWS of the Tibetan Plateau increased with the speed of 0.7 mm/yr as the precipitation accumulated and the glaciers melted during the period 1981–2015. The TWS values were low and generally present a trend of obvious accumulation over the northern Tibetan Plateau, while the high and decreasing values were distributed in the south of Tibetan Plateau. The results of the components analysis indicate that the TWS mainly consisted of soil moisture at one-fourth layers, which are 0–200 cm underground in most areas of the Tibetan Plateau. The precipitation is mainly lost through evapotranspiration over the northern Tibetan Plateau, while in the northwestern corner of the Tibetan Plateau, the Himalayas, and northeastern Yarlung Zangbo River basin, the runoff coefficients were larger than 1.0 due to the influence of snow melting. In the alpine mountains, different climate and vegetation conditions have complex effects on water resources. The results are helpful for understanding the changing mechanism of water storage over the Tibetan Plateau and have scientific meaning for the development, utilization, and protection of regional water resources. [ABSTRACT FROM AUTHOR]

• Reveal spatial and upstream–downstream patterns of runoff change drivers in eastern Tibetan Plateau for the first time. • Climate change dominant runoff trend and change in eastern Qinghai-Tibetan Plateau. • Quantitatively explained climatic and underlying surface conditions change contributed to runoff change. • Both hydrological model and Budyko framework were employed for robust results. Quantitatively identifying the impact of climatic and underlying surface condition changes on runoff is crucial for the efficient utilization of water resources and understanding hydroclimatic variability processes. This study aims to employ both Grid-RCCC-WBM model and Fu's equation based on Budyko hypothesis to quantitatively analyze the spatial patterns of runoff changes, driving forces, and upstream–downstream relationships in ten typical basins across the eastern Qinghai-Tibet Plateau (QTP) for the first time. Breaks for Additive Season and Trend method was used to detect breakpoints in runoff series and both hydrological model and Budyko equation categorized driving forces of runoff change into change in climatic (including precipitation and potential evaporation) and underlying surface conditions. The results indicated (i) significant abrupt changes in the runoff time series around 1998, with runoff increasing in all basins except for the source region of the Yellow River. (ii) significant upstream–downstream differences in the trend and magnitude of runoff changes between breakpoints in the Yangtze and Lancang Rivers over the past 20 years, and (iii) significant runoff response to climate variability after the breakpoints in the source region of the Yangtze and Yellow river. Our findings revealed that, contrary to the backdrop of decreasing precipitation, the upstream basins maintained increasing runoff relying on permafrost and glacier meltwater, while the downstream basins exhibited decreasing trend. The differences in runoff changes after the detected breakpoints were dominated by changes in underlying surface conditions, with the highest contribution rates observed in the Dajin (494 %), Lanzhou (398%), and Tangnaihai (197%) basins. This study involved both spatial pattern and upstream–downstream relationship of runoff change that can be widely applied to other large-scale regions and especially holds important implications for the scientific and rational utilization of water resources in the QTP. [ABSTRACT FROM AUTHOR]

• We evaluated 12 mainstream global precipitation datasets on the Tibetan Plateau. • A regional reference map of the best precipitation dataset was given. • We summarized the unique advantages of ERA5 in alpine and complex terrain regions. • Practical advice is given to improve precipitation estimates on the Tibetan Plateau. Acquiring precipitation information is a critical yet challenging task for the Tibetan Plateau (TP) with sparse gauges and high altitudes. Presently, there is a multitude of operational precipitation products merged from different data sources. A major concern within the TP science community is which one of these available precipitation datasets performs best on the TP. To address this concern, we selected and compared twelve widely used global precipitation datasets, including six satellite-based precipitation estimates (GSMaP-Gauge, IMERG-Final, TMPA-v7, CMORPH-BLD, PERSIANN-CDR, CHIRPS), five reanalysis data (ERA5, JRA-55, MERRA2, GLDAS, NCEP2), and one multi-source fusion product (MSWEP). Benchmarked against both automatic weather stations and independent field observations, we comprehensively investigate the spatiotemporal accuracy and regional applicability of these global precipitation products on the TP. The evaluation results indicate that almost all the datasets have a consistent tendency to overestimate lower precipitation rates and underestimate higher ones. However, four out of the twelve studied datasets (i.e., GSMaP-Gauge, IMERG-Final, ERA5, and MSWEP) significantly outperform others. Specifically, the two GPM-based satellite precipitation products, GSMaP-Gauge and IMERG-Final, can better reflect the difference between different rain intensities and perform better at moderate rain rates. In contrast, the reanalysis-based ERA5 exhibits a more clustered data series, with relatively higher accuracy at low precipitation rates. Moreover, ERA5 demonstrates a stable superiority in the mountainous areas characterized by complex local terrains. Furthermore, we find that the applicability of different precipitation datasets has an obvious region-related feature. Thus, a regional distribution map was made to clearly outline the optimal choice of current mainstream global precipitation datasets over different climate zones within the TP. This study can offer valuable insights for TP researchers, especially aiding them to select the appropriate precipitation data for their specific studies. [ABSTRACT FROM AUTHOR]