Quantifying the impact of climate change on hydrologic features is essential for the scientific planning, management and sustainable use of water resources in Northwest China. Based on hydrometeorological data and glacier inventory data, the Spatial Processes in Hydrology (SPHY) model was used to simulate the changes of hydrologic processes in the Upper Shule River (USR) from 1971 to 2020, and variations of runoff and runoff components were quantitatively analyzed using the simulations and observations. The results showed that the glacier area has decreased by 21.8% with a reduction rate of 2.06 km²/a. Significant increasing trends in rainfall runoff, glacier runoff (GR) and baseflow indicate there has been a consistent increase in total runoff due to increasing rainfall and glacier melting. The baseflow has made the largest contribution to total runoff, followed by GR, rainfall runoff and snow runoff, with mean annual contributions of 38%, 28%, 18% and 16%, respectively. The annual contribution of glacier and snow runoff to the total runoff shows a decreasing trend with decreasing glacier area and increasing temperature. Any increase of total runoff in the future will depend on an increase of rainfall, which will exacerbate the impact of drought and flood disasters.

The impacts of climate change and human activities on water resources are a complex and integrated process and a key factor for effective water resource management in semi-arid regions, especially in relation to the Jinghe River basin (JRB), a major tributary of the Yellow River basin. The Sen’s slope estimator and the Mann–Kendall test (M–K test) are implemented to examine the spatial and temporal trends of the hydrological factors, while the elasticity coefficient method based on Budyko’s theory of hydrothermal coupling is employed to quantify the degree of runoff response to the various influencing factors, from 1971 to 2020. The results reveal that the runoff at Pingliang (PL), Jingchuan (JC), and Yangjiaping (YJP) hydrological stations shows an obvious and gradual decreasing trend during the study period, with a sudden change in about 1986, while precipitation shows a fluctuating and increasing trend alongside a potential evapotranspiration-induced fluctuating and decreasing trend. Compared to the previous period, a change of −29%, in relative terms, in the runoff at the YJP hydrological station is observed. The interaction of human activities and climate change in the watershed contributes to the sharp decrease in runoff, with precipitation, potential evapotranspiration, and human activities accounting for −14.3%, −15.1%, and 70.6% of the causes of the change in runoff, respectively. Human activities (e.g., construction of water conservancy projects), precipitation, and potential evapotranspiration are the main factors contributing to the change in runoff.

Analyzing trends in flood magnitude changes, and their underlying causes, under climate change, is a key challenge for the effective management of water resources in arid and semi-arid regions, particularly for inland rivers originating in the Qilian Mountains (QMs). Sen’s slope estimator and the Mann–Kendall test were used to investigate the spatial and temporal trends in flood magnitude, based on the annual maximum peak discharge (AMPD) and Peaks Over Threshold magnitude (POT3M) flood series, of twelve typical rivers, from 1970 to 2021. The results showed that, in the AMPD series, 42% of the rivers had significantly decreasing trends, while 8% had significantly increasing trends; in the POT3M series, 25% of the rivers had significantly decreasing trends, while 8% had significantly increasing trends. The regional differences in the QMs from east to west were that, rivers in the eastern region (e.g., Gulang, Zamu, and Xiying rivers) showed significantly decreasing trends in the AMPD and POT3M series; most rivers in the central region had non-significant trends, while the Shule river in the western region showed a significantly increasing trend. Temperatures and precipitation showed a fluctuating increasing trend after 1987, which were the main factors contributing to the change in flood magnitude trends of the AMPD and POT3M flood series in the QMs. Regional differences in precipitation, precipitation intensity, and the ratio of glacial meltwater in the eastern, central and western regions, resulted in the differences in flood magnitude trends between the east and west.

Accurate precipitation estimation is essential for hydrological modeling and water resource management in arid regions; however, complex terrain and sparse meteorological station networks introduce substantial uncertainties into gridded precipitation datasets. This study evaluates the performance of nine widely used precipitation products in the arid region of Northwest China (ARNC) at both the meteorological station scale and the sub-basin scale, and applies the Bayesian Model Averaging (BMA) approach to merge multi-source precipitation estimates. The results reveal pronounced spatial heterogeneity and significant differences in performance among datasets, with the Integrated Multi-Satellite Retrievals for the Global Precipitation Measurement mission performing best at the station scale and the Famine Early Warning Systems Network Land Data Assimilation System performing best at the sub-basin scale. Compared with individual products, the BMA-merged precipitation demonstrates substantial improvements at both scales, providing higher coefficients of determination and agreement indices, and lower relative mean absolute error and relative root mean square error, indicating enhanced accuracy and robustness. The BMA-merged precipitation product generally exhibits superior and more spatially consistent performance than the individual datasets across the ARNC, thereby providing a more reliable basis for regional hydrological and climate-related applications. The merged dataset shows that the mean annual precipitation in the ARNC during 2000–2024 is approximately 230.4 mm, exhibiting a statistically significant increasing trend of 1.4 mm per year, with the strongest increases occurring in the Tianshan and Qilian Mountains. This study provides a reliable foundation for hydrological modeling and climate-change assessments in data-limited arid environments.

Analyzing trends in flood magnitude changes and their underlying causes under climate change is a key challenge for the effective management of water resources in arid and semi-arid regions, particularly for inland rivers originating in the Qilian Mountains (QMs). Sen’s slope estimator and Mann-Kendall test were used to investigate spatial and temporal trends in flood magnitude based on the annual maximum peak discharge (AMPD) and Peaks-Over-Threshold (POT3M) flood series of twelve typical rivers from 1970 to 2021. The results showed that in the AMPD series, 42% of the rivers had significantly decreasing trends, while 8% had significantly increasing trends; in the POT3M series, 25% of the rivers had significantly decreasing trends, while 8% had significantly increasing trends. The regional differences in the QMs from east to west were that rivers in the eastern region (e.g., Gulang, Zamu, and Xiying rivers) showed significantly decreasing trends in the AMPD and POT3M series; most rivers in the central region had non-significant trends, while the Shule river in the western region showed a significantly increasing trend. Temperatures and precipitation showed a fluctuating increasing trend after 1987, which were the main factor contributing to the change in flood magnitude trends of the AMPD and POT3M flood series in the QMs. Regional differences in precipitation, precipitation intensity, and the ratio of glacial meltwater in the eastern, central and western regions resulted in the differences in flood magnitude trends between the east and west.

Climate change is altering hydrological processes in alpine regions, and changes in streamflow seasonality and its relationship with precipitation inputs have important implications for regional water resource management. Based on monthly streamflow records from three hydrological stations (Zhamashike, Qilian, and Yingluoxia) in the upper Heihe River Basin during 1970–2025, together with corresponding precipitation data, this study investigated long-term variations in seasonal precipitation and streamflow distributions and their relationships using seasonal contribution analysis, Mann–Kendall tests, Sen’s slope estimation, and regression analysis. The results showed that: (1) precipitation remained strongly concentrated in summer, with a broadly stable seasonal pattern despite a significant increase in the spring precipitation fraction (0.946 percentage points per decade); (2) streamflow exhibited significant seasonal redistribution, with decreases in the summer streamflow fractions at Qilian and Yingluoxia and an increase in the spring fraction at Yingluoxia; (3) precipitation–streamflow relationships varied among seasons, with stronger contemporaneous relationships generally occurring in summer and weaker relationships in winter; and (4) the observed differences between precipitation and streamflow seasonality suggest that precipitation timing alone cannot fully explain seasonal runoff variability. Catchment storage and delayed water-release processes may contribute to these differences, although their individual contributions were not quantitatively assessed. These findings highlight the importance of considering seasonal runoff redistribution in water-resource assessments of alpine river basins.