Multi-phase transformation model of water quality in the sluice-controlled river reaches of Shayinghe River in China.
Environ Sci Pollut Res Int
; 25(7): 6633-6647, 2018 Mar.
Article
em En
| MEDLINE
| ID: mdl-29260470
ABSTRACT
To better understand the complex transformation mechanisms of pollutants in different phases in sluice-controlled river reaches (SCRRs), a multi-phase transformation model of water quality is proposed. This model mainly describes the interactions of the water body, suspended matter, deposited sediments, and organisms. Mathematical expressions were first derived to describe the mass transportation processes in different phases of the river system. The multi-phase transformation model in SCRRs was then established with defined physical mechanisms. Monitored data from the operation of Huaidian sluice were used to identify and validate the parameters of the transformation model and to simulate the spatial and temporal changes of pollutants in different phases. Four findings were made from the results. Firstly, the concentration values of pollutants in each phase in the upper and lower river reaches of the sluice are affected by flow, mode of sluice operation, and algal growth and enrichment. Secondly, the reaction processes in the upper and lower river reaches of the sluice indicate different dominant mechanisms according to the change in sluice operation. Thirdly, sluice operation leads to stronger exchanges between the water body and external materials because of the increased water disturbance. Fourthly, in the early period of the experiment, changes in the alga concentrations were mainly affected by water movement. In the later period, changes in the alga concentrations were mainly affected by the obstruction of the sluice in the upstream section, while these were affected by flow velocity, flow volume, and changes in nutrient concentration in the downstream section.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Poluentes Químicos da Água
/
Qualidade da Água
/
Monitoramento Ambiental
/
Rios
Tipo de estudo:
Prognostic_studies
País como assunto:
Asia
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article