The impact of socioeconomic system on the river system in a heavily disturbed basin.

Zengliang Luo, Qiting Zuo, Quanxi Shao, Xiangyi Ding
Author Information
  1. Zengliang Luo: School of Water Conservancy & Environment, Zhengzhou University, Zhengzhou 450001, China.
  2. Qiting Zuo: School of Water Conservancy & Environment, Zhengzhou University, Zhengzhou 450001, China.
  3. Quanxi Shao: CSIRO Data61, Leeuwin Centre, 65 Brockway Road, Floreat, WA 6014, Australia. Electronic address: Quanxi.Shao@data61.csiro.au.
  4. Xiangyi Ding: Department of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, China.

Abstract

The quantitative assessment of the impact of socioeconomic development on river water environment is important to the scientific management of river basins. However, current methods have high data requirements or are difficult to deal with the impact between systems (which is defined by a collection of indicators). This paper first uses canonical correlation analysis (CCA) to understand the relationship between socialeconomic system (defined by a set of indicators reflecting socioeconomic development) and river system (defined by a set of indicators reflecting river water environment), and then proposes a method to assess the impact of socioeconomic system on river system by integrating CCA and the degrees of influence of river system indicators. The proposed method and framework are applied to the Shaying River Basin with the characteristics of multi-sluices, high pollution, and dense population based on data from 2000 to 2015. Results indicate that socioeconomic and river systems are highly related to each other with the average influence degree of greater than 0.9, indicating very close relationships between socioeconomic and river systems. The changes of influence degree vary between 0.19 and 0.79 with a turning point in 2010. Most of the influence levels are "moderate" (influence degree between 0.4 and 0.6) or "high" (influence degrees between 0.6 and 0.8) before 2010 but become to "low" (influence degrees between 0.2 and 0.4) since then. In addition, the influence degree shows a significant increase from upstream to downstream with Zhoukou Station as the turning point, meaning that the stronger the human activity is, the greater the impact of the socioeconomic system on the river system is. The main influential factors are population density and sewage treatment rate. The proposed method contributes to the research in river management with limited data availability and the results can serve as an important reference for basin management.

Keywords

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