Literature DB >> 28726227

Modelling the effects of water diversion and combined sewer overflow on urban inland river quality.

Xianyong Gu1, Zhenliang Liao2, Guangqian Zhang1, Jiaqiang Xie1, Jin Zhang3.   

Abstract

In order to assist and optimize the operation of a clean water diversion project for the medium-sized inland rivers in Chaohu, China, an integrated hydrodynamic and water quality model was used in this study. Sixteen diversion scenarios and five sewage interception scenarios were defined to assess the improvement of water quality parameters including ammonia nitrogen (NH3-N), total phosphorus (TP) and chemical oxygen demand (COD) under different diverted water flows, diverting times, diverting points, diverting routines and sewage interception proportions. An index of pollutant removal rate per unit diverted water flow (PRUWF) was proposed to evaluate the effect of the clean water diversion. Results show that operating conditions played important roles in water quality improvement of medium-sized inland rivers. The optimal clean water diversion was operated under the conditions of a flow rate of 5 m3/s for 48 h with an additional constructed bridge sluice. A global sensitivity analysis using the Latin Hypercube One-Factor-at-a-Time (LH-OAT) method was conducted to distinguish the contributions of various driving forces to inland river water restoration. Results show that sewage interception was more important than diverted water flow and diverting time with respect to water quality improvement, especially for COD.

Entities:  

Keywords:  Clean water diversion; Combined sewage overflow; Inland rivers; Sensitivity analysis; Water quality modelling

Mesh:

Substances:

Year:  2017        PMID: 28726227     DOI: 10.1007/s11356-017-9686-x

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  12 in total

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Journal:  Sci Total Environ       Date:  2015-08-04       Impact factor: 7.963

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Journal:  Environ Monit Assess       Date:  2019-05-04       Impact factor: 2.513

2.  Measuring performance of low impact development practices for the surface runoff management.

Authors:  Wenyu Yang; Kurt Brüggemann; Kiwanuka David Seguya; Ehtesham Ahmed; Thomas Kaeseberg; Heng Dai; Pei Hua; Jin Zhang; Peter Krebs
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