Literature DB >> 28886543

Assessing river water quality using water quality index in Lake Taihu Basin, China.

Zhaoshi Wu1, Xiaolong Wang2, Yuwei Chen3, Yongjiu Cai4, Jiancai Deng5.   

Abstract

Lake Taihu Basin, one of the most developed regions in China, has received considerable attention due to its severe pollution. Our study provides a clear understanding of the water quality in the rivers of Lake Taihu Basin based on basin-scale monitoring and a water quality index (WQI) method. From September 2014 to January 2016, four samplings across four seasons were conducted at 96 sites along main rivers. Fifteen parameters, including water temperature, pH, dissolved oxygen (DO), conductivity, turbidity (tur), permanganate index (CODMn), total nitrogen, total phosphorus, ammonium (NH4-N), nitrite, nitrate (NO3-N), calcium, magnesium, chloride, and sulfate, were measured to calculate the WQI. The average WQI value during our study period was 59.33; consequently, the water quality was considered as generally "moderate". Significant differences in WQI values were detected among the 6 river systems, with better water quality in the Tiaoxi and Nanhe systems. The water quality presented distinct seasonal variation, with the highest WQI values in autumn, followed by spring and summer, and the lowest values in winter. The minimum WQI (WQImin), which was developed based on a stepwise linear regression analysis, consisted of five parameters: NH4-N, CODMn, NO3-N, DO, and tur. The model exhibited excellent performance in representing the water quality in Lake Taihu Basin, especially when weights were fully considered. Our results are beneficial for water quality management and could be used for rapid and low-cost water quality evaluation in Lake Taihu Basin. Additionally, we suggest that weights of environmental parameters should be fully considered in water quality assessments when using the WQImin method.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Lake Taihu Basin; River; WQI; WQI(min); Water quality assessment; Yangtze River Delta

Year:  2017        PMID: 28886543     DOI: 10.1016/j.scitotenv.2017.08.293

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  16 in total

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