Detecting the quantitative hydrological response to changes in climate and human activities

• Published in: The Science of the total environment 2017-05, Vol.586, p.328-337
• Main Authors: Wu, Jingwen, Miao, Chiyuan, Zhang, Xiaoming, Yang, Tiantian, Duan, Qingyun
• Format: Article
• Language: English
• Subjects: Budyko; Climate change; Human activities; Quantitative hydrological response; SWAT; Yanhe River basin
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2017.02.010

Understanding the relative contributions of climate change and human activities to changes in runoff is important for sustainable management of regional water resources. In this study, we systematically review ten commonly used quantitative methods drawn from three main categories—empirical statistics, elasticity-based methods, and hydrological modeling. We explain the calculation processes for the different methods and summarize their applications and characteristics. Then, using the Yanhe River basin as a case study, we employ all ten methods to separate out the effects of climate change and human activities on changes in runoff. The results show that climate change played a dominant role in the decline in runoff in the Yanhe River basin. Climate change was estimated to account for 46.1%–60.8% (mean 54.1%) of the total decrease in runoff, whereas human activities accounted for 39.1%–53.9% (mean 45.9%). Elasticity-based methods and hydrological modeling produced similar estimates, but the estimates made using empirical statistics were different. Empirical statistics were not a suitable method for the Yanhe River basin. We also discuss the factors that influence the different methods and the applicable conditions for each methodological category. [Display omitted] •Ten commonly used quantitative methods drawn from three main categories were reviewed.•All ten methods were used to assess the impacts of climate change and human activities on runoff in the Yanhe River basin.•Climate change had the larger effect on decreases in runoff, accounting for 54.1% (mean estimation).•Three main quantitative categories were compared and the relative merits were summarized.