Table 1.
Simulation scenarios for detecting climate variability and human activity on streamflow and its components.
Fig 1.
A schematic to determine the effects of climate change and human activities on streamflow change.
Fig 2.
Scatterplot comparing the RMSE values of the two algorithms for the monthly emissions during the calibration period (a). Objective function trajectories for the DEMC and SC-EUA algorithms (b, c).
Table 2.
Performance evaluation of the VIC simulation.
Fig 3.
Comparison of simulated streamflow with observed streamflow from two hydrological stations, detailed model performance is shown.
Fig 4.
Temporal changes of hydroclimatic variables at Bole station (p<0.05).
The gray line, red line, and gray area represent the runoff observation, breakpoint segmentation value, and coverage area, respectively.
Fig 5.
Temporal changes of hydroclimatic variables at Jinghe station (p<0.05).
The gray line, red line, and gray area represent the runoff observation, breakpoint segmentation value, and coverage area, respectively.
Fig 6.
Temporal changes of hydroclimatic variables at Wenquan station (p<0.05).
The gray line, red line, and gray area represent the runoff observation, breakpoint segmentation value, and coverage area, respectively.
Fig 7.
Comparison of average changes in hydroclimatic variables between the impact period and the base period.
Where Win_ET, Fal_ET, Sum_ET, Spr_ET, ET, Win_P, Fal_P, Sum_ET, Spr_P, P, Win_Q, Fal_Q, Sum_Q, Spr_Q, Q represent the average evapotranspiration value in winter, the average evapotranspiration value in autumn, the average evapotranspiration value in summer, the average evapotranspiration value in spring, the average annual average evapotranspiration, winter average precipitation, fall average precipitation, summer average precipitation, spring average precipitation, annual average precipitation, winter average runoff, fall average runoff, summer average runoff, spring average runoff, annual average runoff.
Fig 8.
Land cover type changes from 1980–2015: (a) area shift in land cover types from 1980 to 2000; (b) area shift in land cover types from 2000–2015; (c) area shift in land use from 1980–2015; (d) changes in the area of 8 land cover types in 2000 and 2015 relative to 1980.
Fig 9.
Average April-October LAI for each year from 1981-to 2019 for the entire ELB (a) and average monthly LAI for three different periods (b). The red dotted line shows the linear fit for 1981–2019, and "Tend (1981-)" denotes the trend for 19881–2019, p<0.05.
Fig 10.
Variations in runoff depth driven by VIC_1980, VIC_2000, and VIC_2017 for the entire ELB.
Fig 11.
Monthly average changes in streamflow, surface runoff, baseflow, and snowmelt are driven by the VIC_1980, VIC_2000, and VIC_2017 scenarios for the entire ELB during impact phase Ⅰ (a) and impact phase Ⅱ (b).
Fig 12.
Effects of climatic and human factors on increasing trends in streamflow, surface runoff, baseflow, and snowmelt in the ELB during different impact periods, where (a) denotes impact phase Ⅰ and (b) shows impact phase Ⅱ.
Table 3.
VIC-simulated values of streamflow and its components for different impact phases and scenarios.