A comparison between joint and dual UKF implementations for state estimation and leak localization in water distribution networks
Abstract
The sustainability of modern cities highly depends on efficient water distribution management, including effective pressure control and leak detection and localization. Accurate information about the network hydraulic state is therefore essential. This article presents a comparison between two data-driven state estimation methods based on the Unscented Kalman Filter (UKF), fusing pressure, demand and flow data for head and flow estimation. One approach uses a joint state vector with a single estimator, while the other uses a dual-estimator scheme. We analyse their main characteristics, discussing differences, advantages and limitations, and compare them theoretically in terms of accuracy and complexity. Finally, we show several estimation results for the L-TOWN benchmark, allowing to discuss their properties in a real implementation.
Keywords
Cite
@article{arxiv.2510.24228,
title = {A comparison between joint and dual UKF implementations for state estimation and leak localization in water distribution networks},
author = {Luis Romero-Ben and Paul Irofti and Florin Stoican and Vicenç Puig},
journal= {arXiv preprint arXiv:2510.24228},
year = {2025}
}
Comments
This work has been submitted to ECC2026 for review. It has 7 pages and 2 figures