Description: DBPFinder is an open-source web-based tool designed to perform strategic sensor placement in chlorinated water distribution networks, aiming to optimize the detection of dissinfection byproducts (DBPs), formed when chlorinated water interacts with natural occurring matter. Developed with Streamlit using EPANET hydraulic models, it integrates environmental data and customizable DBP predictive equations (only linear regression supported at this version), in order to identify the most effective sensor locations for monitoring compounds like trihalomethanes (THMs) and haloacetic acids (HAAs).

Key features:

• EPANET-Compatible: Upload .inp network models along with environmental datasets (Excel or CSV).
• Customizable DBP Modeling: Define or select THM and HAA formation equations for tailored analysis.
• Contract-Based Risk Assessment: Optionally include population/contract data to minimize DBP exposure risk.
• Multi-Criteria Optimization: The following options are available: a) Time of detection; b) Normalized DBP Score; c) Mass consumption minimization; d) Event frequency for specific DBPs.

Added value:

• By integrating environmental data, DBP formation models, and hydraulic simulation, DBPFinder helps you determine where sensors should be placed to: Detect contamination early, monitor DBP formation effectively, reduce monitoring costs by avoiding redundant placements of sensing equipment.
• With support for customizable equations and weighting between THMs and HAAs, DBPFinder helps prioritize sensor placement based on: Regulatory thresholds, specific DBP risk levels and public health priorities.
• Users can upload field or modeled environmental data and run repeatable simulations, enabling: Evidence-based decision-making and rapid prototyping of “what-if” scenarios.

Source code: The source code of the DBPFinder simulator has been published as open source code; it can be found and downloaded here (SuPerWorld GitHub account).

User manual: The user manual of DBPFinder can be downloaded here. For questions or remarks, please send an email to Aristotelis Magklis.

Creator: Aristotelis Magklis, Research Associate of the SuPerWorld research group of CYENS Center of Excellence.

Publications:

• Aristotelis Magklis and Andreas Kamilaris, Data-driven strategic sensor placement for detecting disinfection by-products in water distribution networks, arXiv preprint arXiv:2511.11775, November, 2025.
• Aristotelis Magklis and Andreas Kamilaris, Strategic sensor placement for the identification of disinfection byproducts from chlorinated drinking water: Case study in the water distribution network of Coimbra, Portugal, Proceedings of the 38th edition of Environmental Informatics Conference (EnviroInfo 2024), Cairo, Egypt, November, 2024.

Snapshots:: Screenshots of the DBPFinder simulator are shown below:
br> br> br> br>