Integrated approach of water quality monitoring and hydraulic parameter analysis based on building information modeling in water distribution networks

Microbiological communities in building plumbing and water distribution systems (WDS) are water quality indicators with significant implications for public health, system efficiency and infrastructure maintenance. Thus, monitoring water quality and understanding WDS structures are essential for detecting contamination, assessing risks, and ensuring effective system management. However, some gaps exist, particularly in older buildings that often lack accessible floor plans, complicating WDS understanding. Furthermore, challenges in sharing and managing data on building structures and water quality analysis hinder collaboration and decision-making necessary for an adequate Water Safety Plan, increasing contamination risks. Finally, traditional assessments often focus primarily on microbiological aspects, overlooking hydraulic parameters, limiting comprehensive contamination mitigation, highlighting the need for a more holistic approach. An integrated approach is proposed to address the challenges by innovatively improving water quality and WDS management. This approach combines microbiological and hydraulic parameters analysis, supported by Building Information Modeling (BIM), enhancing coordination among professionals across various disciplines involved in water quality evaluation. It underlines the importance of considering water holistically, departing from the conventional fragmented approach to water quality assessment. By simultaneously analyzing both microbial and hydraulic aspects, water quality can be improved. BIM is a key element by streamlining data sharing and management, other than addressing the lack of correct and updated WDS layouts. In this context, BIM serves as a dynamic, shareable, and consultable model designed to contain several useful information for risk assessment. Integrating microbiological analysis with hydraulic parameter evaluation could ensure optimal water quality. This thesis shows how the proposed approach improves data flow and communication. Developing a model that correctly reproduces the WDS and includes the relevant information has proven useful for planning sampling campaigns, while integrating microbiological and hydraulic analysis identifies malfunctions within the WDS. This approach enhances water quality assessment, safeguarding public health, and optimizing infrastructure maintenance.