Literature DB >> 35292895

Spatiotemporal heterogeneities and driving factors of water quality and trophic state of a typical urban shallow lake (Taihu, China).

Yonggui Wang1,2, Yanqi Guo1,2, Yanxin Zhao3, Lunche Wang1,2, Yan Chen4, Ling Yang1,2.   

Abstract

Water quality deterioration and eutrophication of urban shallow lakes are global ecological problems with increasing concern and greater environmental efforts. In this study, spatiotemporal changes of water quality and eutrophication were assessed by trophic level index (TLI), cluster analysis, and spatial interpolation methods in Lake Taihu and its sub-lakes from 2015 to 2019. Results showed that the Taihu had poor water quality and maintained a light-eutropher state overall, mainly astricted by the total nitrogen (TN) and the total phosphorus (TP). All nutrient parameters reached relatively higher concentrations in the northwestern and northern areas. Meiliang Bay was the most polluted and nutrient-rich area. In terms of trend, the Mann-Kendall test highlighted that the TP and chlorophyll-a (Chl-a) concentrations increased significantly while the TN and five-day biochemical oxygen demand (BOD5) decreased. The massive nutrient loads caused by human activity from the northwestern Taihu and the geomorphological characteristic of the north closed bays were the main contributors to the spatial heterogeneity in water quality. The main driving force of the alleviative nitrogen pollution was the declining river inflow nitrogen loading, and phosphorus pollution was affected more by accumulated endogenous pollution and decline in aquatic plants area, as well as closely linked with algae biomass. Further water pollution and eutrophication restoration of Taihu should focus on the nutrient reductions and those heavily polluted closed bays.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Driving factors; Eutrophication; Lake Taihu; Spatiotemporal heterogeneities; Urban shallow lakes; Water quality

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Year:  2022        PMID: 35292895     DOI: 10.1007/s11356-022-18519-1

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   5.190


  1 in total

1.  Water-Quality Assessment and Pollution-Risk Early-Warning System Based on Web Crawler Technology and LSTM.

Authors:  Guoliang Guan; Yonggui Wang; Ling Yang; Jinzhao Yue; Qiang Li; Jianyun Lin; Qiang Liu
Journal:  Int J Environ Res Public Health       Date:  2022-09-19       Impact factor: 4.614

  1 in total

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