Water quality modelling of a grossly polluted stream using continuous monitoring.

HAFFERTY, Brendan P. (1978). Water quality modelling of a grossly polluted stream using continuous monitoring. Doctoral, Sheffield Hallam University (United Kingdom)..

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Abstract

The development of a statistical water quality model for a grossly polluted stream in an industrial environment, is examined. The data used for model development was obtained from a continuous water quality monitoring station (WQMS), which recorded five quality determinands each quarter hour. The continuous monitoring was performed in conjunction with a discrete sampling and analysis programme, which covered eight sites upstream of the WQMS. Continuous flow gauging was also performed, with a stream flowmodel based on unit hydrograph theory being developed for the period prior to flow gauge installation. The applications of continuous water quality monitors are discussed and necessary precautions for the operation of the WQMS in a grossly polluted environment are described. The literature concerning water quality monitoring has been surveyed, particularly that appertaining to continuous monitoring. The monitored data was subjected to various handling techniques with subsequent statistical analyses being performed by computer. The analyses indicated various interrelationships within the determinands,which were quantified and upon which the model was built. Multiple regression was found to be most effective at describing the system under study. The model has been evaluated and it is shown that grossly polluted systems can be effectively monitored by continuous techniques. The increased reliability and utility of the model, built upon large volumes of continuous monitored data is illustrated. Conclusions are given, with suggestions for future work being made.

Item Type: Thesis (Doctoral)
Additional Information: Thesis (Ph.D.)--Sheffield Hallam University (United Kingdom), 1978.
Research Institute, Centre or Group: Sheffield Hallam Doctoral Theses
Depositing User: EPrints Services
Date Deposited: 10 Apr 2018 17:20
Last Modified: 11 May 2018 14:18
URI: http://shura.shu.ac.uk/id/eprint/19739

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