Control approach and evaluation framework of scaling in drinking water distribution systems: A review.

ABSTRACT

The United Nations Sustainable Development Goals call for innovative proposals to ensure access to clean water and sanitation. While significant strides have been made in enhancing drinking water purification technologies, the role of drinking water distribution systems (DWDS) in maintaining water quality safety has increasingly become a focal point of concern. The presence of scale within DWDS can impede the secure and efficient functioning of the drinking water supply system, posing risks to the safety of drinking water quality. Previous research has identified that the primary constituents of scale in DWDS are insoluble minerals, such as calcium and magnesium carbonate. Elevated levels of hardness and alkalinity in the water can exacerbate scale formation. To address the scaling issue, softening technologies like induced crystallization, nanofiltration/reverse osmosis, and ion exchange are currently in widespread use. These methods effectively mitigate the scaling in DWDS by reducing the water's hardness and alkalinity. However, the application of softening technologies not only alters the hardness and alkalinity but also induces changes in the fundamental characteristics of water quality, leading to transition effects within the DWDS. This article reviews the impact of various softening technologies on the intrinsic properties of water quality and highlights the merits of electrochemical characteristic indicators in the assessment of water quality stability. Additionally, the paper delves into the factors that influence the transition effects in DWDS. It concludes with a forward-looking proposal to leverage artificial intelligence, specifically machine learning and neural networks, to develop an evaluation and predictive framework for the stability of drinking water quality and the transition effects observed in DWDS. This approach aims to provide a more accurate and proactive method for managing and predicting the impacts of water treatment processes on distribution system integrity and water quality over time.