Streamflow is likely affected by climate change and human activities. In this study, hydro-meteorological data from six rivers upstream of Beijing, namely, the Yongdinghe, Baihe, Heihe, Chaohe, Juhe, and Jumahe Rivers, were analyzed to quantify the spatial and temporal variability of streamflow and their responses to climate change and human activities over the period of 1956–2016. The Mann–Kendall test and moving t-test were used to detect trends and changing points of the annual streamflow. Results showed that the streamflow into Beijing experienced a statistically significant downward trend (p < 0.05), abruptly changing after the early 1980s, owing to climate and human effects. The climate elasticities of the streamflow showed that a 10% decrease in precipitation would result in a 24.5% decrease in total streamflow, whereas a 10% decrease in potential evapotranspiration would induce a 37.7% increase in total streamflow. Human activities accounted for 87% of the reduction in total streamflow, whereas 13% was attributed to climate change. Lastly, recommendations are provided for adaptive management of water resources at different spatial scales.

The Yellow River is one of the major rivers with severe runoff declines in China, but there are significant differences in runoff changes in the upper and lower reaches of the basin and among different tributaries. However, the characteristic of runoff change and its spatial heterogeneity are not well understood in the whole basin. In this paper, 48 hydrological stations located in the mainstream and major tributaries were selected, and the meteorological and runoff data from 1956 to 2017 were collected. The multi-year and intra-year changes in runoff were analyzed, and then the attribution of climate change and human activity to runoff change was quantified by the climate elasticity coefficients. The results showed that: (1) in the past 60 years, the runoff of the Yellow River showed a serious decrease trend of −8.25 mm/10a. Moreover, most tributaries decreased significantly in runoff with a rate of −1.42 mm/10a to −28.99 mm/10a; (2) for the whole basin, the contribution of climate change and human activity to runoff changes was 13% and 87%, respectively. Moreover, the contribution of the two factors varied considerably in different tributaries. Finally, focusing on different runoff regime and socioeconomic characteristics, this study provided corresponding water resources adaptive management suggestions.

A good water budget involving four variables, including precipitation (P), evapotranspiration (ET), streamflow (R), and terrestrial water storage change (TWSC), is reflected in two aspects: a high accuracy against observations for each budget component and the low water budget closure residual error (ΔRes). Due to the lack of consideration of observations of budget components in existing water budget closure assessment methods (BCMs), when the ΔRes of budget components is low, their error against respective observations may still be high. In this study, we assess the water budget closure accuracy of satellite/reanalysis-based hydrological data products over mainland China based on six popular P products and multiple datasets of additional budget components (ET, R, and TWSC). The results indicated that the ΔRes changes between ±15 mm over mainland China. Satellite P products such as GPM IMERG showed better performance by comparing them with rain gauge-based observations. However, reanalysis P products such as GLDAS and FLDAS showed a better water budget closure since the selected datasets of additional budget components (ET and R) are also derived from reanalysis datasets. This indicates that these same data sources for budget components make it easier to close the water budget. The further development of satellite P products should consider the closure of the water budget with other water cycle variables.

Since the launch of the Grain for Green (GFG) program in 1999, the Loess Plateau has undergone significant vegetation changes. However, the driving mechanisms behind these changes in the post-GFG period remain insufficiently understood. This study analyzes the spatiotemporal dynamics of vegetation on the Loess Plateau from 1982 to 2015, based on long-term NDVI time series, and quantitatively identifies the relative contributions of climate variability and human activities using partial correlation and multiple regression residual analysis. The results reveal a significant increase in NDVI after 2000, with the annual variation rate rising from 0.0009 to 0.0028, and the proportion of rapidly greening areas expanding from 13.3% to 62.9%. Spatially, vegetation recovery was more prominent in the eastern and lower-latitude regions. While both climate and anthropogenic factors influenced vegetation changes, the latter became dominant after 2000. The area where human activities significantly enhanced vegetation increased from 1.9% to 60.6%, with the most notable improvements observed in forests, followed by croplands and grasslands. Vegetation in the southern plateau was more sensitive to temperature, while the northern region responded more strongly to precipitation. From 2000 to 2015, the GFG program contributed to increases of 17,059.46 km² in grasslands and 10,105.78 km² in forests. These findings improve our understanding of vegetation change drivers on the Loess Plateau and offer a scientific basis for ecological restoration, policy-making, and sustainable development in the Yellow River Basin.

Distributed hydrological simulation in karst regions has always been a challenging task because of their unique hydrogeological characteristics. The karst mountain region of southwest China (KMRSC), one of the largest continuous karst areas in the world, contributes to about 54 percent of water supply in the basins. In spite of its importance, we have a poor understanding of the evolution laws of hydrological cycle and water resources in KMRSC. We developed a physically-based, distributed hydrological model, called Water and Energy transfer Processes (WEP)-karst model, for KMRSC by introducing the equivalent porous medium approach to the WEP-L model, and dividing the modelling domain into 2021 sub-watersheds. The area of sub-watersheds ranges from 55 to 920 km², with an average value of 170 km². The model showed a good performance in simulating the monthly discharge at 18 representative hydrological stations, with the Nash–Sutcliffe efficiency (NSE) values ranging from 0.71 to 0.94, and the relative error (RE) values from −9.8% to 8.3% during the validation period (1980–2000). Then, we employed an in-depth analysis of the temporal and spatial variation of main water cycle fluxes, including precipitation, infiltration, evapotranspiration, blue water (i.e., river runoff), and green water (i.e., vegetation transpiration) over 1956–2015. In addition, the impact of climate change on these fluxes was evaluated under the median emission scenario (RCP4.5). The results showed that: (1) annual average precipitation of KMRSC reached 1506 mm, which is 2.4 times of the national average level, and about 47% (701 mm) of it contributed to river runoff. The infiltration and evapotranspiration were 862 and 870 mm, respectively. The transpiration from plants and trees accounted for 51% of the evapotranspiration. (2) Except for the green water, other fluxes experienced a significant decrease over the past 60 years. Blue water showed the largest interannual fluctuation and the strongest sensitivity to climate change. (3) Both precipitation and infiltration concentrated from May to August, and blue water increased notably from May to June and peaked in June. Blue water and precipitation were more likely to decrease in the future over 2021–2050 due to the climate change.

Northeast China serves as a crucial grain production base and ecological security barrier, playing an essential role in ensuring national food security and maintaining ecosystem stability. However, extensive land reclamation and intensive water resource exploitation have gradually weakened the region's ecological functions. This study revealed the critical challenges between agricultural expansion and ecosystem conservation, including the encroachment upon riverine wetlands, reduction in wetland water inflows, alterations of natural hydrological patterns, depletion of groundwater resources, and fragmentation of aquatic habitats. Moreover, the study introduced novel methodologies for hydrological and hydrodynamic modeling, determining agricultural and ecological water consumption thresholds, and assessing ecological connectivity. These approaches offer critical support for the rational resource allocation and spatial distribution of agriculture and ecology. In conclusion, a comprehensive set of regulatory strategies was proposed, including the establishment of a wetland compensation mechanism; the rational regulation of agricultural reclamation scale and total water consumption; the optimization of the spatial distribution of farmland and wetlands; the development of an efficient and systematic water replenishment mechanism for wetlands; and the protection and restoration of priority areas of wetlands. Importantly, the methodologies and findings possess considerable potential for application to analogous river basins.