The main objective of the project ShERLOcK (A StEp forward in the ResiLient management Of drinKing water utilities) is to move towards a resilient, robust and effective management of Drinking Water, from source to tap, under evolving circumstances.
Drinking water treatment plants (DWTPs) are tasked with providing safe water to the inhabitants by means of several treatment units that act as chemical and physical barriers against microbial pathogens and chemical pollutants. Natural organic matter (NOM) is the major precursor of disinfection by-products (DBPs), the unintended outcome of water disinfection practices, are the major contributors for the chemical risk for human health of drinking water. Approximately 700 DBPs have been already reported, with trihalomethanes (THMs) and haloacetic acids (HAAs) being the most frequently found groups and at the highest concentrations in water supplies worldwide. Overall, managing the trade-off between chemical and microbial risks of water has been one of the biggest challenges of the water treatment industry over the past years.
Enhanced coagulation, adsorption and ion exchange, membrane-based technologies, or advanced oxidation processes are widely used advance technologies in the treatment train for purification of drinking water. However, these technologies may be high cost demanding processes, encouraging its optimiszed usage with a focus on DBPs precursors removal by advanced control strategies. Thus, it is needed an integrated assessment of treatment operations at bench, pilot and full-scale operations to get further insights into the mechanisms and
reasons for water treatment (in)efficiency.
Decisions on the most appropriate treatment conditions depend on an undeterminable number of factors influencing the water complex composition, including catchment characteristics and seasonal variations. Thus, in most of the cases plant operation is operatordependent, subjective, and variable, which leads to suboptimal results in terms of product quality, costs, and environmental performance. Stricter legislation on water quality will increase the complexity of water treatment, requiring an integrated approach. Within this context, the development of a Decision Support Systems (DSS) is the SHERLOCKs proposed tool to manage DWTP. DSS provide the users with a better understanding of the problem and augment their decision capacity, potentially being the most useful tool to cope with the complex decision-making. For operational improvements toward greater resiliency, the developed DSS should allow for realtime predictive risk assessment, and enhanced prioritization of control actions reflecting the consequences of managing decisions along the treatment train and the distribution system.
To develop and implement the proposed DSS, it is necessary to identify parameters, patterns, and reasoning mechanisms to design new indicators and control strategies. Besides laboratory tests, experimental, advanced knowledge will be acquired through bench, pilot and full-scale assessment linking advanced NOM characterisation techniques with regulated DPBs formation. Moreover, the obtained knowledge will be complemented with accredited information, experienced practitioners and data mining methodologies applied to historical databases. This overarching, ambitious proposal relies on the support of 3 companies (ATL, AGiSST, FISERSA) operating 4 facilities with a total nominal treatment capacity of 1,250,000 m3/day.
Principal Investigator: Dr Hèctor Monclús