Climate variation and human activities are commonly recognized as two major factors affecting basin hydrology. However, quantifying their individual effect on runoff is challenging. In this study, long-term (1960–2009) river discharge and weather data in the Songhua River Basin (SRB, 556,800 km²), Northeast China, were gathered to separate the impacts of climate variation and human activities on runoff in five sub basins of the SRB. Mann-Kendall test, moving t-test and precipitation-runoff double cumulative curve were utilized to identify trends and change points of the hydrometeorlogical variables. Based on the change point, the 50-year study period was divided into two time series: 1960–1974 where minimal human activities took place and 1975–2009 where extensive land use change occurred and river engineering projects were undertaken. Subsequently, individual contributions of climate and human factors were assessed through a hydrologic sensitivity analysis. Our study found a significant decline in runoff of the SRB over the past 50 years. Contribution of climate variation and human activities to the change varied temporally and spatially. For the 1975–2009 period, human activities made a greater contribution (62%–82%) to the total runoff decline of the SRB. However, climate variation played a bigger role in runoff reduction in two sub river basins (63%–65%) between 1975 and 1989, as well as in runoff increase in other two sub river basins (85%–86%) between 1990 and 1999. Spatially, the effect of human activities on runoff decline was relatively stronger in the lower basin areas in the 1960s and 1970s while showing an increasing role in the upper basin areas in the past two decades.

The Songhua River Basin (SRB) in Northeast China is one of the areas most sensitive to global climate change because of its high-latitude location. In this study, we conducted a modeling assessment on the potential change of water resources in this region for the coming three decades using the Soil and Water Assessment Tool (SWAT). First, we calibrated and validated the model with historical streamflow records in this basin. Then, we applied the calibrated model for the period from 2020 to 2049 with the projected and downscaled climatic data under two emission scenarios (RCP 4.5 and RCP 8.5). The study results show: (1) The SWAT model performed very well for both the calibration and validation periods in the SRB; (2) The projected temperatures showed a steady, significant increase across the SRB under both scenarios, especially in two sub-basins, the Nenjiang River Basin (NRB) and the Lower SRB (LSRB). With regard to precipitation, both scenarios showed a decreasing trend in the NRB and LSRB but an increasing trend in the Upper Songhua River Basin (USRB); and (3), generally, the hydrologic modeling suggested a decreasing trend of streamflow for 2020–2049. Compared to baseline conditions (1980–2009), the streamflow in the NRB and LSRB would decrease by 20.3%–37.8%, while streamflow in the USRB would experience an increase of 9.68%–17.7%. These findings provide relevant insights into future surface water resources, and such information can be helpful for resource managers and policymakers to develop effective eco-environment management plans and strategies in the face of climate change.

The objectives of this study were to assess land use changes and their hydrological impacts in the Nenjiang River Basin (NRB). The Soil and Water Assessment Tool (SWAT) model was employed to evaluate the impacts of land use changes. The Cellular Automata-Markov model was used to predict a land use map in 2038. Streamflow under each land use state was simulated by the SWAT model. The results showed that there was a significant expansion of agriculture area at the expense of large areas of grassland, wetland, and forest during 1975–2000. The land use changes during the period of 1975 to 2000 had decreased the water yield (3.5%), surface runoff (1.7%), and baseflow (19%) while they increased the annual evapotranspiration (2.1%). For impacts of individual land use type, the forest proved to have reduced streamflow in the flood season (10%–28%) and increased surface runoff in the drought season (20%–38%). Conversely, grassland, dry land, and paddy land scenarios resulted in increase of streamflow during summer months by 7%–37% and a decrease of streamflow in the cold seasons by 11.7%–59.7%. When the entire basin was changed to wetland, streamflow reduced over the whole year, with the largest reduction during January to March. The 2038 land use condition is expected to increase the annual water yield, surface runoff and wet season flow, and reduce evapotranspiration and baseflow. These results could help to improve sustainable land use management and water utilization in the NRB.

Low Impact Development (LID) is one of the sustainable approaches to urban stormwater management in areas with rapid urbanization. Although LID has been shown to have a positive effect in flood reduction, the hydrological balance regulation effect of LID under a variety of rainfall events is not fully understood. In this study, we assessed the hydrological efficiency of LID at two residential–commercial mixed sites in Korea to investigate the main function of LID in terms of diverse rainfall characteristics. Storm Water Management Model (SWMM) was constructed to simulate the hydrological process numerical simulations in the pre-development, post-development and LID design scenarios, respectively. The model was calibrated and validated by using five observed rainfall–runoff events. Then, four single and four multiple LID practices (LIDs) were used to estimate their effectiveness under seven different designed rainfall events. The results indicate that LIDs substantially influence the hydrology cycle system, while the regulating effect varies with rainfall amounts. The efficiency of LIDs in flood reduction is proved to be more effective during lower storm events. However, LIDs should be designed to primarily prioritize the restoration of hydrological balance when the rainfall return period is longer.

The calculation of hydrologic frequency is an important basic step in the planning and design stage of any water conservancy project. The purpose of the frequency analysis is to deduce the hydrologic variables under different guarantee rates, and to provide hydrologic information for water conservancy project planning and design. The calculation of hydrologic frequency requires that the sample size is large enough, as only then can the statistical characteristics of samples take the place of the total statistical eigenvalues. This means that the samples can reveal the statistical characteristics of hydrologic variables and identify the randomness rule of hydrologic phenomena. Many countries in the East Asian monsoon climate zone (China, Japan and South Korea) have stipulated a sample size of 30 years for hydrologic frequency analysis. In this paper the rationality of the 30-year sample size is proved by analyzing the periodic and random rules of hydrologic phenomenon and the influencing mechanism of solar activity, and by adopting the general conclusion of the sampling theorem. Then, using the wavelet analysis method to examine annual precipitation data in a long series generated from representative precipitation observation stations in China, the strong-weak cycle of solar activity is proved to be 10 years, which is consistent with the wet-dry cycle of the representative precipitation stations (10–12 years). Finally, adopting numerical modeling to analyze the normal distribution of randomly generated samples and long-range annual precipitation data collected from representative stations, hypothesis testing (u, F and t) is used to prove that a 30-year sample size is reasonable. This research provides a reference as to how to prove the necessary sample size for relevant statistical analyses (for example, how large the sample should be for analyzing hydrologic factors trend evolution, hydrologic data consistency and ergodicity of statistical samples), thus ensuring the reliability of the analytical results.

Changes in hydrological cycles and water resources will certainly be a direct consequence of climate change, making the forecast of hydrological components essential for water resource assessment and management. This research was thus carried out to estimate water balance components and water yield under current and future climate change scenarios and trends in the Guder Catchment of the Upper Blue Nile, Ethiopia, using the soil and water assessment tool (SWAT). Hydrological modeling was efficaciously calibrated and validated using the SUFI-2 algorithm of the SWAT model. The results showed that water yield varied from 926 mm to 1340 mm per year (1986–2016). Regional climate model (RCM) data showed, under representative concentration pathways (RCP 8.5), that the precipitation will decrease by up to 14.4% relative to the baseline (1986–2016) precipitation of 1228 mm/year, while the air temperature will rise under RCP 8.5 by +4.4 °C in the period from 2057 to 2086, possibly reducing the future basin water yield output, suggesting that the RCP 8.5 prediction will be warmer than RCP 4.5. Under RCP 8.5, the total water yield from 2024 to 2086 may be reduced by 3.2 mm per year, and a significant trend was observed. Local government agencies can arrange projects to solve community water-related issues based on these findings.