Arman Moradi
Hydraulic Modelling and Machine Learning Solutions for Leak Monitoring in Municipal Water Distribution Networks.
Rel. Gianvito Urgese, Walter Gallego Gomez, Salvatore Tilocca. Politecnico di Torino, Master of science program in Digital Skills For Sustainable Societal Transitions, 2025
|
Preview |
PDF (Tesi_di_laurea)
- Thesis
Licence: Creative Commons Attribution. Download (15MB) | Preview |
Abstract
Urban water distribution networks (WDNs) are essential infrastructures that ensure the continuous supply of clean and safe water to communities. Due to population growth, climate variability, and aging infrastructure, improving operational efficiency and minimizing losses have become critical objectives for water utilities. Among the major challenges faced by modern WDNs, leakages represent a significant source of inefficiency; in Italy, networks lose approximately 42% of the treated water before it reaches consumers. Such losses impose substantial economic costs, reduce system resilience, and hinder the sustainable management of water resources. This thesis work involved the development of a hydraulic digital model and the evaluation of algorithms for leakage monitoring in two municipalities in the Province of Cuneo, Piedmont, Italy: Cavallermaggiore and Marene.
The thesis was developed in collaboration with Alpiacque, the water utility manager, and the support of Tesisquare and Fondazione DIG421
Relators
Academic year
Publication type
Number of Pages
Course of studies
Classe di laurea
URI
![]() |
Modify record (reserved for operators) |
