Assessment of a Digital Coagulation Management Tool to Support Sustainable Drinking Water Treatment in Regional Operations

Chemical coagulation is a highly important step of the conventional treatment processes, determination of the optimum coagulant dose to meet the demand of particulate materials and natural organic matters (NOMs) in raw water is crucial for good drinking water quality. WTC-Coag is a universal non-site-specific coagulant prediction model using three raw water quality parameters, UV 254 , colour, and turbidity, as model inputs. The empirical model can determine the dose for maximum dissolved organic carbon (DOC) removal to achieve the conditions of enhanced coagulation; it also features an operator-selectable input—% setpoint (as % DOC removal)—to establish a dose for the desirable treated water quality. This hybrid modelling and control approach in practice is extremely useful for operators to be able to optimise the process by balancing between water quality and use of resources (chemical and sludge disposal costs) for sustainable operation. This paper discusses the practicality of this hybrid modelling approach via a long-term evaluation by comparing the plant dose against predicted dose using five years historical operations and water quality data. The assessment covered raw water quality change against treatment performance, predictability, usability and operator behaviour in response to the dose change situation. During the study period, five “black water” events were captured, and the performance of the predictability due to operational changes and operator’s response in these extreme events have been analysed. The comparison between the predicted enhanced dose and the plant dose indicated enhanced coagulation would not be always required. Furthermore, the selection of 50% setpoint from the targeted dose option matched well with the plant dose during which the lower-dose situation would be sufficient, with 90% of the predicted doses within ±10 mg/L of the plant dose and 95% of the predicted doses within ±15 mg/L of the plant dose during the normal period. The use of a correction factor to compensate for the particulate demand due to powdered activated carbon (PAC) dose during “black water” events has shown to be effective. The 50% setpoint matches with the plant alum dose over the entire period after accounting for the PAC dose, with 70% of the predicted doses within ±10 mg/L and 80% within ±15 mg/L of the plant dose. All the coagulation-related prediction functions have been evaluated and confirmed their non-site-specific nature. This study is unique in terms of using real operations data for an extended period to evaluate this novel hybrid modelling concept towards the sustainability goal.