Located in the northeast of the Tibetan Plateau, the headwaters of the Yellow River basin (HYRB) are very vulnerable to climate change. In this study, we used the Soil and Water Assessment Tool (SWAT) model to assess the impact of future climate change on this region's hydrological components for the near future period of 2013-2042 under three emission scenarios A1B, A2 and B1. The uncertainty in this evaluation was considered by employing Bayesian model averaging approach on global climate model (GCM) multimodel ensemble projections. First, we evaluated the capability of the SWAT model for streamflow simulation in this basin. Second, the GCMs' monthly ensemble projections were downscaled to daily climate data using the biascorrection and spatial-disaggregation method and then were utilized as input into the SWAT model. The results indicate the following: (1) The SWAT model exhibits a good performance for both calibration and validation periods after adjusting parameters in snowmelt module and establishing elevation bands in sub-basins. (2) The projected precipitation suggests a general increase under all three scenarios, with a larger extent in both A1B and B1 and a slight variation for A2. With regard to temperature, all scenarios show pronounced warming trends, of which A2 displays the largest amplitude. (3) In the terms of total runoff from the whole basin, there is an increasing trend in the future streamflow at Tangnaihai gauge under A1B and B1, while the A2 scenario is characterized by a declining trend. Spatially, A1B and B1 scenarios demonstrate increasing trends across most of the region. Groundwater and surface runoffs indicate similar trends with total runoff, whereas all three scenarios exhibit an increase in actual evapotranspiration. Generally, both A1B and B1 scenarios suggest a warmer and wetter tendency over the HYRB in the forthcoming decades, while the case for A2 indicates a warmer and drier trend. Findings from this study can provide beneficial reference to water resource and eco-environment management strategies for governmental policymakers.

Located in the Tibetan Plateau, the upstream regions of the Mekong River (UM) and the Salween River (US) are very sensitive to climate change. The ‘VIC-glacier‘ model, which links a degree-day glacier algorithm with variable infiltration capacity (VIC) model, was employed and the model parameters were calibrated on observed streamflow, glacier mass balance and MODIS snowcover data. Results indicate that: (1) glacier-melt runoff exhibits a significant increase in both areas by the Mann–Kendall test. Snowmelt runoff shows an increasing trend in the UM, while the US is characterized by a decreasing tendency. In the UM, the snowmelt runoff peak shifts from June in the baseline period 1964–1990 to May for both the 1990s and 2000s; (2) rainfall runoff was considered as the first dominant factor driving changes of river discharge, which could be responsible for over 84% in total runoff trend over the two regions. The glacial runoff illustrates the secondary influence on the total runoff tendency; (3) although the hydrological regime is rain dominated in these two basins, the glacier compensation effect in these regions is obvious, especially in dry years.

To fully understand potential changes in hydrological regime over the Lhasa River Basin (LRB) and the upstream of Niyang River Basin (UNRB) in Tibetan Plateau under global warming, the VIC-glacier model was employed to analyze the responses of rainfall runoff and melt water to recent climate change, and we also quantify their roles in controlling the trend of river streamflow during 1963–2012. The hydrological model was calibrated using the observed streamflow, glacier mass balance, and MODIS snow cover. The simulations indicate that there is a significant increasing trend in glacier runoff for both basins during 1963–2012, especially in the period of 2000s when it exhibits a large increment up to about 45% relative to baseline period. Rainfall runoff suggests a rising tendency whereas snowmelt runoff displays a general decreasing tendency. For both basins, increasing rainfall runoff was identified as the dominant driver for the upward trend in total runoff during 1963–2012. The role of glacier runoff in controlling the trend of total runoff is also obvious, especially in the more glaciated UNRB where increased glacier runoff accounts for up to 41% of the tendency in river discharge. Snowmelt runoff plays a minor role in affecting the trend of total runoff.

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Reliable precipitation is crucial for hydrological studies over Tibetan Plateau (TP) basins with sparsely distributed rainfall gauges. In this study, four widely used precipitation products, including the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of the water resources (APHRODITE), the High Asia Reanalysis (HAR), and the satellite-based precipitation estimates from Global Precipitation Measurement (GPM) and Tropical Rainfall Measurement Mission (TRMM), were comprehensively evaluated by combining statistical analysis and hydrological simulation over the Upper Brahmaputra (UB) River Basin of TP during 2001–2013. In respect to the statistical assessment, the overall performances of GPM and HAR are comparable to each other, and both are superior to the other two datasets. For hydrological assessment, both daily and monthly GPM-based streamflow simulations perform the best not only at the UB outlet with very good results, but they also illustrate satisfactory results at Yangcun and Lhasa hydrological stations within the UB. Runoff simulation using HAR only performs well at the UB outlet, whereas it shows poor results at both Yangcun and Lhasa stations. The simulated results based on APHRODITE and TRMM show poor performances at UB. Generally, the GPM shows an encouraging potential for hydro-meteorological investigation over UB, although with some bias in flood simulation.

Sensitivity analysis of hydrological model parameters is a crucial step in the calibration process of hydrological simulation. In this paper, the improved Morris method with the double-Latin hypercube sampling is proposed for global sensitivity analysis of 10 parameters of the Xin'anjiang model. In addition, the local sensitivity is analyzed based on the rate validation of the model parameters. In general, the results show those parameters about evaporation coefficient in the deep layer (C), free water storage capacity (SM), impervious area as a percentage of total watershed area (IMP), free water storage capacity curve index (EX), groundwater outflow coefficient (KG) and subsurface runoff abatement factor (KKG) are all less than 0.01, insensitive parameters; the parameters about evaporation conversion factor (K) and square times of the storage capacity curve(B) are in the range of [0.01, 0.1], less sensitive parameters; the parameter about flow out coefficient in soil (KSS) is in the range of [0.1, 0.2], a low-sensitivity parameter; the parameter abatement coefficient of mid-soil flow (KKSS) is greater than 1, a high-sensitivity parameter; the improved Morris method better reflects the existence of interactions between parameters. This research result provides a new technical approach for the sensitivity analysis of hydrological model parameters.

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