Quantitative impacts of population on river water quality in the Jinshui River basin of the South Qinling Mts., China

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• 作者：Hongmei Bu ; Wenzhi Liu ; Xianfang Song ; Quanfa Zhang
• 关键词：River water quality ; Population ; Elevational gradient ; Pollution index ; Regression model ; Mathematical functions ; Quantifying impact
• 刊名：Environmental Earth Sciences
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：75
• 期：4
• 全文大小：1,236 KB
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• 作者单位：Hongmei Bu (1)
  Wenzhi Liu (2)
  Xianfang Song (1)
  Quanfa Zhang (2)
  
  1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Datun Road, A 11, Beijing, 100101, People’s Republic of China
  2. Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, People’s Republic of China
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：None Assigned
• 出版者：Springer Berlin Heidelberg
• ISSN：1866-6299

文摘

Increasing population is generally responsible for the degraded river ecosystem. Using regression models and mathematical functions, the research quantitatively estimated the population and elevational gradient effects on river water quality during nine surveys from 2006 to 2008 in the Jinshui River basin of the South Qinling Mts., China. The total factor scores at 11 different sampling sites were calculated in factor analysis and first used as pollution index to represent the water quality levels. Population and elevational gradient both significantly linked with most water quality variables and pollution index in correlation analysis and explained 36.5–77.8 % of the total variances in regression analysis, indicating that human activities were gradually frequent with population growth and affected the input and output of pollutants in river water. On the basis of regression models and quadratic functions among population, elevational gradient, and pollution index, the population capacity of the river basin was estimated as 1815 people, and the threshold value of elevation was calculated as 1174 m. The results of multivariate linear models further confirmed that population and population distribution had direct influences on river water quality. This study will facilitate the ecosystem management for mountainous streams and provide quantitative models for understanding and mitigating human impacts on river system. Keywords River water quality Population Elevational gradient Pollution index Regression model Mathematical functions Quantifying impact