Online transient-based burst localization in water networks using a two-stage ensemble Kalman filter

Real-time burst localization in water distribution systems is essential for minimizing water loss, infrastructure damage, and service disruptions. However, traditional methods often struggle with scalability, accuracy, and responsiveness, particularly in large-scale networks. This study proposes a novel two-stage Ensemble Kalman Filter (EnKF) framework integrated with an efficient Elastic Water Column (EWC) model for transient-based burst localization. The EWC model reduces computational complexity by requiring fewer discretization points, significantly lowering the dimensionality of the state space. Moreover, a two-stage localization strategy is introduced: the first stage identifies the likely burst pipes, and the second stage pinpoints the precise burst location. This hierarchical approach further improves both computational efficiency and localization accuracy in complex networks. Numerical case studies on networks of different scales demonstrate the method's robustness, convergence, and accuracy, indicating its potential for real-time and accurate burst localization in practical water distribution systems.