2134/9095
Ahmed Moustafa
Ahmed
Moustafa
Deducing water parameters in rivers via statistical modelling
Loughborough University
2011
Acoustic-Doppler
Online
Drinking Water
Sensors
Turbidity
Colour
Conductivity
Flow
Rive
2011-11-18 13:14:08
Thesis
https://repository.lboro.ac.uk/articles/thesis/Deducing_water_parameters_in_rivers_via_statistical_modelling/9579212
Advanced monitoring of water quality in order to perform a real-time hazard analysis prior to
Water Treatment Works (WTW) is more of a necessity nowadays, both to give warning of
any contamination and also to avoid downtime of the WTW. Downtimes could be a major
contributor to risk. Any serious accident will cause a significant loss in customer and investor
confidence. This has challenged the industry to become more efficient, integrated and
attractive, with benefits for its workforce and society as a whole.
The reality is that water companies are not yet prepared to invest heavily in trials, before
another company announces its success in implementing a new monitoring strategy. This has
slowed down the development of the water industry.
This research has taken the theoretical idea that the use of advanced online monitoring
technique in the water industry would be beneficial and a step further; demonstrating by
means of a state-of-the-art assessment, usability trials, case studies and demonstration that the
barriers to mainstream adoption can be overcome. The findings of this work have been
presented in four peer-reviewed papers.
The research undertaken has shown that Turbidity levels in rivers can be measured from the
rivers’ mean flow rate, using either Doppler Ultrasound device for real-time readings or based
on past performance history. In both cases, the Turbidity level can also help estimate both the
Colour and Conductivity levels of the subject river. Recalibration of the equations used is a
prerequisite as each individual river has its own unique “finger print”.