In this paper it was shown which water quality information is required to be measured online to ensure the production of good-quality drinking water. This was determined by following a seven-step approach, which helped to understand the processes taking place as well as their dynamics. It was shown that the use of a single instrument able to measure different parameters can be beneficial.

Drinking-water quality monitoring is essential before consumption, as the available water is contaminated and can cause illness in an individual. The traditional methods for water quality monitoring require sample collection at different sites and a subsequent laboratory test which is labor- and cost-intensive. To, overcome this problem, a real-time drinking water quality measurement platform is designed which can provide on-site efficient water quality monitoring.

Using real-time uncertain measurements from a real water transport network, the proposed Iterative Hydraulic Interval State Estimation algorithm generates bounds on hydraulic states, by taking into account the measurement uncertainty and modeling uncertainty in the form of uncertain pipe parameters. The applicability of this methodology was demonstrated by using it to estimate the unaccounted-for water in the network. This methodology can be used as a tool for fault detection in water networks.

TOC (total organics carbon) analysis, as a laboratory and online technology, offers new perspectives to organic measurements in waters and waste water, supplementing regulatory oxygen demand tests. TOC monitoring, implemented as a tool to make informative and rapid treatment decisions, becomes a useful process control parameter. This paper discusses the various technologies available and details how three municipal plants gained insights into their processes and saved on their spending with TOC.

About 20 % of the world population lives in areas without sufficient portable water; 97 % of the water on the earth is seawater. Understanding the level of salinity/TDS of seawater is a necessity. Currently, determination of salt content is by chemical analysis and is time-consuming. Our research is to develop a lab on chip optical sensor to measure the percentage of salinity in water. Even a small % of salinity change in water can be detected in real time by the sensor continuously with accuracy.