Development of an environmental decision support system to enhance coagulation in drinking water treatment plants

Population access to safe drinking water is crucial for mankind development. Due to the geographical context, climate change and unsustainable management, there are some regions where future generations will suffer water scarcity. Water resources include surface waters, which are freshwater catchments. Part of the produced drinking water comes from surface freshwater sources. Hence, surface freshwater becomes a key element not only for the hydrological cycle but also for the anthropogenic water cycle, and plays a key role for drinking water and wastewater treatments.

Drinking water treatment includes a series of processes and some specific treatments applied to remove water pollutants for the generation of safe drinking water for human consumption, always within the limits regulated by national and international directives. Among these pollutants, natural organic matter (NOM) is group of organic components present in all surface waters, which are derived from decomposition and microbiological activity. NOM represents a challenge for drinking water treatment and its removal is essential to ensure water quality. NOM is heterogeneous, its concentration/fractionation fluctuates and has the capacity to react with some reagents used for water disinfection, generating disinfection by-products (DBPs).

Regarding drinking water treatment, coagulation is a widespread physicochemical treatment, located at the beginning of the conventional treatment and presents high potential for NOM removal. From here, full-scale coagulation optimization can be achieved aimed to remove NOM. There are a number of factors that determine coagulation performance, including the NOM characterization and the optimisation of reagents doses.

Digitalisation strikes the entire society and water sector is no exception. Research and development efforts allowed to install competitive online sensors and analysers, which offer an online measurement of NOM-related parameters during the water treatment, including coagulation. All these data are continuously recorded in databases, providing valuable information to detect trends and behaviours as well as to determine the optimal operating conditions.

The main objective of this thesis is the development of enhanced coagulation decision support systems (EDSS) at three drinking water treatment plants (DWTPs) located in the Mediterranean region. The development of an enhanced coagulation EDSS has included several analyses related to data and knowledge acquisition as well as databases evaluation and the development of specific models for enhanced coagulation. This thesis comprises tasks related to sampling campaigns, laboratory analysis, enhanced coagulation experiments, historical data evaluation, scenarios identification, enhanced coagulation models development and its integration for the enhanced coagulation EDSS.