Ecological Indicators (Oct 2021)

Improved water pollution index for determining spatiotemporal water quality dynamics: Case study in the Erdao Songhua River Basin, China

  • Binbin Wang,
  • Yuanyuan Wang,
  • Shuli Wang

Journal volume & issue
Vol. 129
p. 107931

Abstract

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The Erdao Songhua River provides drinking water for 16.82 million people; therefore, ensuring that the water quality adequate is of particular concern. In this study, an improved water pollution index (IWPI) and multiple statistical methods were employed to assess the overall water pollution situation and investigate spatiotemporal variations of seven physicochemical parameters such as the permanganate index (PI), dissolved oxygen (DO), chemical oxygen demand (CODcr), five-day biochemical oxygen demand (BOD5), total nitrogen (TN), total phosphorus (TP) and ammonia nitrogen (NH3-N), which were collected monthly at 20 sites within the mainstream and major tributaries of the Erdao Songhua River Basin (ESRB) from 2015 to 2020. Stepwise regression analysis was conducted to build a minimum improved water pollution index (IWPImin) model consisted of four key elements (PI, DO, CODcr, and BOD5) proposed from seven parameters. The results demonstrated water quality within the ESRB was considered to be “Good” with the mean IWPI values <40. However, the water quality deteriorated from the upstream to the downstream within the basin, manifested as the mean value of IWPI of the downstream is 1.7 times of upstream. Seasonally, an improving trend of water quality was observed during the monitoring period and the mean IWPI value decreased by 23%. Furthermore, Seasonal variation in the IWPI value was evident, and the best water quality was found in winter (lowest IWPI value of 14.1) and the worst in summer (highest IWPI value of 21.7). The proposed IWPImin model uses the selected four crucial parameters and the weights of those parameters has exhibited excellent performance in the water quality assessment, with the highest coefficient of determination (R2) and lowest Root Mean Square Error (RMSE) values of 0.996 and 0.51, respectively, which can be used to optimize water quality assessment strategies at a lower cost. For future management, the water quality of middle and downstream should be carefully inspected, and strictly control the effects of point source and non-point source pollution in the ESRB.

Keywords