Adequate disinfection of drinking water is the most important priority to ensure a safe water supply and the avoidance of harmful pathogens. However, some naturally occurring organic matter (NOM), anthropogenic contaminants, bromide, and iodide are also present in water, and when a chemical disinfectant such as chlorine is added to water, it tends to react with organic matter to form organic and inorganic disinfection by-products (DBPs) which are known to have adverse health effects on humans. To date, around 700 DBPs have been identified in drinking water, although only a few of them are regulated.

Furthermore, climate change is impacting river water quality and quantity and produces temperature increases. All these aspects affect the stability of supply of high-quality drinking water, especially in Mediterranean regions, for which water utilities need to adapt. No cheap, reliable and affordable on-line sensors for DBPs or biofilm growth exist. Models based on basic water characterisation for the prediction of water quality can help utilities to manage their drinking water distribution networks (DWDNs). Several models calibrated and validated at laboratory are available in the literature but a few of them have been implemented on-line in full-scale DWDNs. There is the need for a simple but useful model that can be easily calibrated and implemented in any DWDN.

Apart from DBPs, other emerging contaminants are raising interest in drinking water. These are: per- and polyfluoroalkyl substances (PFAS), pharmaceuticals and personal care products (PPCPs), microplastics, cyanotoxins and industrial chemicals. Their behaviour and interaction with other compounds in drinking water is not known.

The proposed research aims at validating and implementing, in actual DWDNs, formation models for selected DBPs and other emerging pollutants when they are available in the literature and to develop new models for those which are not. In the latter case, data from the development may come from published scientific material, experimentation at laboratory scale or from DWDN utilities. Once developed, the goal is also to implement them in the numerical simulation of actual DWDNs.