Runoff reduction in most river basins in China has become a hotpot in recent years. The Gushanchuan river, a primary tributary of the middle Yellow river, Northern China, showed a significant downward trend in the last century. Little is known regarding the relative contributions of changing environment to the observed hydrological trends and response on the runoff generation process in its watershed. On the basis of observed hydrological and meteorological data from 1965–2010, the Mann-Kendall trend test and climate elasticity method were used to distinguish the effects of climate change and human activities on runoff in the Gushanchuan basin. The results indicate that the runoff in the Gushanchuan Basin has experienced significant declines as large as 77% from 1965 to 2010, and a mutation point occurred around 1997; the contribution rate of climate change to runoff change is 12.9–15.1%, and the contribution rate of human activities to runoff change is 84.9–87.1%. Then we divided long-term data sequence into two stages around the mutation point, and analyzed runoff generation mechanisms based on land use and cover changes (LUCC). We found that the floods in the Gushanchuan Basin were still dominated by Excess-infiltration runoff, but the proportion in 1965–1997 and 1998–2010 decreased gradually (68.46% and 45.83% in turn). The proportion of Excess-storage runoff and Mixed runoff has increased, which means that the runoff is made up of more runoff components. The variation law of the LUCC indicates that the forest area increased by 49.61%, the confluence time increased by 50.42%, and the water storage capacity of the watershed increased by 30.35%.

Pakistan is water stressed, and its water resources are vulnerable due to uncertain climatic changes. Uncertainties are inherent when it comes to the modeling of water resources. The predicted flow variation in the Kunhar River Basin was modeled using the statistically decreased high-resolution general circulation model (GCM) as an input for the Hydrologiska Byråns Vattenbalansavdelning (HBV) model to assess the hydrological response of the Kunhar River Basin under prevailing climate changes. The model’s best performance during the calibration and validation stages was obtained with a regular 0.87 and 0.79 Nash–Sutcliffe efficiency in the basin, respectively. Under the high-end emission scenario, a 122% increase was expected in evapotranspiration in the rising season of months during the winter period 2059–2079, and such developments were attributed to an immense increase in liquid precipitation and temperature. The model’s output reflects a potential for basin stream flow in terms of increasing liquid precipitation up to 182% at the beginning of the monsoon season in the period 2059–2079 in the scenario of high-end emissions. Moreover, the study produced possible uncertainties in high-elevation zones, where the modeling of a catchment can lead to typical snow ablation and accumulation in future projections. This study revealed that the precipitation rate will increase annually, resulting in an increase in the summer stream flow over the basin, though snow is hardly expected to accumulate in the basin’s future climate.

Storm runoff in basins is comprised of various runoff processes with widely disparate infiltration and storage capacities, such as Hortonian overland flow (HOF), saturated overland flow (SOF), sub-surface flow (SSF), and deep percolation (DP). Areas may be classified according to these various runoff processes based on the soil characteristics, geology, topography, and land-use. This study analyzes changes in runoff components in the Jialu River basin and the Fen River (Jingle sub-basin) during runoff generation from 1980 to 2013 using the runoff segmentation method. Based on the decision scheme, the dominant runoff process (DRP) in the basins was distinguished using geographic information system (GIS) tools. The impact of different runoff process distributions on the changes in the runoff for the basin was determined. The results show that the floods in the Jialu River basin and Jingle sub-basin were dominated by overland flow components. Compared with 1980–1999, the proportion of overland flow components for 2000–2013 in two basins showed a decreasing trend by 8.3% and 7.1%, respectively, while the interflow and underground runoff components increased. In addition, HOF was the DRP in the Jialu River basin and Jingle sub-basin from 2000 to 2013. The area of the rapid runoff processes (HOF, SOF1, and SSF1) in the Jialu River basin and Jingle sub-basin accounted for 89% and 78% of the entire basin, respectively. In contrast, the slow runoff processes (SOF2, SSF2, and DP) accounted for 11% and 22% of the entire basin, respectively. The runoff of the Jingle sub-basin was substantially lower than that of the Jialu River basin under the same rainfall conditions, because of the influence of the distribution of different runoff processes. Compared with the Jialu River Basin, the peak discharge and runoff of Jingle sub-basin were 190.4 m³/s and 2.85 mm lower on average, respectively. The results of this study provide useful information to understand land-use changes and formulate management practices to reduce flooding in the Yellow River.