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 investigate the degree of spatial variability and variance structure of salinization parameters using classical and geostatistical method in Songnen Plain of China, which is one of largest saline-sodic areas in the World, and to analyze the relationship between salinization parameters, including soil salinity content (SC), electrical conductivity (EC), sodium adsorption ratio (SAR), and pH, and seven environmental factors by Pearson and stepwise regression analysis. The environmental factors were ground elevation, surface ponding time, surface ponding depth, and soil moistures at four layers (0–10 cm, 10–30 cm, 30–60 cm, and 60–100 cm). The results indicated that SC, EC, and SAR showed great variations, whereas pH exhibited low variations. Four salinization parameters showed strongly spatial autocorrelation resulting from the compound impact of structural factors. The empirical semivariograms in the four parameters could be simulated by spherical and exponential models. The spatial distributions of SC, EC, SAR and pH showed similar patterns, with the coexistence of high salinity and sodicity in the areas with high ground elevation. By Pearson analysis, the soil salinization parameters showed a significant positive relationship with ground elevation, but a negative correlation with surface ponding time, surface ponding depth, and soil moistures. Both correlation and stepwise regression analysis showed that ground elevation is the most important environmental factor for spatial variation of soil sanilization. The results from this research can provide some useful information for explaining mechanism of salinization process and utilization of saline-sodic soils in the Western Songnen Plain.

Identifying the spatiotemporal change of the groundwater table to precipitation at the river basin scale can be important for regional water resource management. In this study, we proposed a method that combines singular value decomposition and cross-wavelet approaches to analyze the relationship between groundwater level dynamics and precipitation. The method was applied to the Naoli River Basin, Northeast China. Moreover, the method of continuous wavelet using fast Fourier transform was also used to reveal clearly the relationship between groundwater level and heavy precipitation. The results showed that the major mode of relationship between groundwater and precipitation was divided into four patterns in the study area. In general, the lag time is 27.4 (standard deviation: ±8.1) days in pattern 1, 107.5 (standard deviation: ±13.2) days in pattern 2, 139.9 (standard deviation: ±11.2) days in pattern 3, and 173.4 (standard deviation: ±20.3) days in pattern 4, respectively. In addition, the response of groundwater level dynamics is very sensitive to heavy precipitation in all patterns. Therefore, enhancing the utilization of heavy rainfall and flood resources is an effective way to increase groundwater recharge in this basin.