Journal
ECOLOGICAL INDICATORS
Volume 126, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.ecolind.2021.107628
Keywords
Climate change; Human activities; Baseflow separation; Climate elasticity method; The SCRCQ method; Karst basin
Categories
Funding
- National Natural Science Foundation of China [51969004, 51579059]
- National Key Research and Development Programme of China [2017YFC1502405, 2016YFC0401303]
- Guangxi Natural Science Foundation of China [2017GXNSFAA198361]
- Innovation Project of Guangxi Graduate Education [YCBZ2019022]
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Baseflow is a crucial component of river runoff and serves as an important ecological indicator. Analyzing the impact of climate change and human activities on baseflow is essential for maintaining river health and water resource management. Human activities are estimated to be the main factor influencing changes in baseflow values, with climate change also playing a significant role.
Baseflow is an important component of river runoff and an important ecological indicator of environmental health. A quantitative analysis of the impact of climate change and human activities on baseflow based on a scientific and reasonable baseflow separation scheme is helpful for the maintenance of river ecological health and the rational allocation of water resources, especially in the karst basins of Southwest China. The major difficulties and challenges lie in how to select the best baseflow separation scheme for karst basins and how to quantitatively analyse the impacts of climate change and human activity on the baseflow value and the baseflow intra-annual distribution characteristics. Therefore, the original achievement and objective of this study were to further contribute to the literature to fill the gap in the knowledge of how to analyse the impacts of climate change and human activities on baseflow more reasonably and comprehensively in a karst basin. The proposed framework consists of a trend analysis of the precipitation, mean temperature and potential evapotranspiration, an ensemble method for selecting the optimal baseflow separation scheme, the climate elasticity method and the slope change ratio of the cumulative quantity method to quantitatively estimate the contributions from climate change and human activities to changes in baseflow values and baseflow intra-annual distribution characteristics. The methodology was successfully implemented using a 55-year time series (1963?2017) of meteorological data and flow data recorded by the stations in the Chengbi River Karst Basin (Southwest China). The results show that annual rainfall and annual potential evapotranspiration display an upward and downward trend, respectively, while the average annual temperature is relatively stable. The Chapman-Maxwell method with a parameter of 0.970 outperforms the other methods and is the best baseflow separation scheme. Human activities are estimated to be the main factors influencing the variation of baseflow values and the variation of the baseflow annual distribution characteristics, with a contribution rate of 65.89%?149.83%, and the contribution rate of climate change is - 49.83%?34.11%.
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