Assessing the impact of climate variability and human activities on streamflow variation

作者：Chang, Jianxia^*; Zhang, Hongxue; Wang, Yimin; Zhu, Yuelu

来源：Hydrology and Earth System Sciences, 2016, 20(4): 1547-1560.

DOI：10.5194/hess-20-1547-2016

• WEI RIVER-BASIN
• YELLOW-RIVER
• WATER-RESOURCES
• LAND-USE
• VEGETATION CHANGES
• ENERGY-BALANCE
• ANNUAL RUNOFF
• SENSITIVITY
• TOPMODEL
• MODEL

Water resources in river systems have been changing under the impact of both climate variability and human activities. Assessing the respective impact on decadal stream-flow variation is important for water resource management. By using an elasticity-based method and calibrated TOP-MODEL and VIC hydrological models, we quantitatively isolated the relative contributions that human activities and climate variability made to decadal streamflow changes in the Jinghe basin, located in the northwest of China. This is an important watershed of the Shaanxi province that supplies drinking water for a population of over 6 million people. The results showed that the maximum value of the moisture index (E-0/P) was 1.91 and appeared in 1991-2000, and the decreased speed of streamflow was higher since 1990 compared with 1960-1990. The average annual streamflow from 1990 to 2010 was reduced by 26.96% compared with the multiyear average value (from 1960 to 2010). The estimates of the impacts of climate variability and human activities on streamflow decreases from the hydrological models were similar to those from the elasticity-based method. The maximum contribution value of human activities was 99% when averaged over the three methods, and appeared in 1981-1990 due to the effects of soil and water conservation measures and irrigation water withdrawal. Climate variability made the greatest contribution to streamflow reduction in 1991-2000, the values of which was 40.4%. We emphasized various source of errors and uncertainties that may occur in the hydrological model (parameter and structural uncertainty) and elasticity-based method (model parameter) in climate change impact studies.

• 出版日期2016
• 单位西安理工大学