As one of the major agricultural regions in the world, water scarcity problems in Northeast China have drawn much attention recently. Because of cold and long winter period, snow is an important component in the hydrological system. Yet few studies have been conducted to systematically assess its role. This study quantified the effects of snow on runoff and soil moisture in the entire region in a 30‐year time period (1982–2011) for the first time. A water and energy budget‐based distributed biosphere hydrological model with improved snow physics after calibration and validation is employed. A Standardized Snow depth Index (SSdI) is also proposed to quantify snow variations. Result shows that snow contributes 11% to runoff annually on average and 66% and 33% in April and May (main months for crop planting). Soil moisture could decrease by at least 20% in March–May if there would be no snow, and the major agriculture area suffers more than other regions. We also found that SSdI is indicative of standardized soil moisture index and standardized runoff index in spring, particularly useful for supporting water management in agriculture. These results indicate that snow performs like an important reservoir: redistribute water resources among months. This study provides unique insights into the importance of snow in the entire region. The results improve the awareness of the importance of snow to water resources management and indicate that it is worth paying attention to snow in water resources management in this region.

Hydroclimatic data are of importance to understand the water cycle and therefore for water resource assessment. Such data are of paramount importance for the Tibetan Plateau (TP), which is the source region of several large rivers in Asia. The Global Land Data Assimilation System (GLDAS) 2.0 and 2.1 provide abundant fine resolution hydroclimatic data. However, evaluations on their applicability have not been carried out for the TP. This study aims to evaluate and improve their applicability in basin‐scale hydrological applications in the TP. Gauge‐based data, a hydrological model including biosphere and seven state‐of‐the‐art global precipitation products are utilized to carry out the study in four large basins in the TP. We find that GLDAS2.1 shows significant warming trends from 2001 to 2010, whereas GLDAS2.0 shows cooling trends, although only significant in the Upper Yellow River basin. The contrasting trends imply that caution should be taken when using them to analyze climate change impacts. On a monthly scale, GLDAS2.1 precipitation on average is closer to the gauge‐based data than GLDAS2.0, but both of them have high uncertainty. Therefore, further quality improvements in precipitation are of importance. We also find CMORPH‐BLD has better performance than other products in terms of Nash‐Sutcliffe Efficiency (NSE), Relative Bias (RB), and root‐mean‐square error. Combining CMORPH‐BLD with GLDAS2.0 forcing data generates more realistic runoff simulation than GLDAS2.1, with NSE and RB being 0.85 and 16% on average. The results provide unique insights into the studied data and are beneficial for water resource assessment in the TP.

Hydropower plays an important role as renewable and clean energy in the world's overall energy supply. Electricity generation from hydropower represented approximately 16.6% of the world's total electricity and 70% of all renewable electricity in 2015. Determining the different effects of 1.5 and 2 °C of global warming has become a hot spot in water resources research. However, there are still few studies on the impacts of different global warming levels on gross hydropower potential. This study used a coupled hydrological and techno‐economic model framework to assess hydropower production under global warming levels of 1.5 and 2 °C, while also considering gross hydropower potential, power consumption, and economic factors. The results show that both global warming levels will have a positive impact on the hydropower production of a tropical island (Sumatra) relative to the historical period; however, the ratio of hydropower production versus power demand provided by 1.5 °C of global warming is 40% higher than that provided by 2 °C of global warming under RCP6.0. The power generation by hydropower plants shows incongruous changing trends with hydropower potential under the same global warming levels. This inconformity occurs because the optimal sites for hydropower plants were chosen by considering not only hydropower potential but also economic factors. In addition, the reduction in CO₂ emissions under global warming of 1.5 °C (39.06 × 10⁶ t) is greater than that under global warming of 2 °C (10.20 × 10⁶ t), which reveals that global warming decreases the benefits necessary to relieve global warming levels. However, the hydropower generation and the reduction in CO₂ emissions will be far less than the energy demand when protected areas are excluded as potential sites for hydropower plants, with a sharp decrease of 40–80%. Thus, government policy‐makers should consider the trade‐off between hydropower generation and forest coverage area in nationally determined contributions.