  This article presents a leak localization methodology based on state
estimation and learning. The first is handled by an interpolation scheme,
whereas dictionary learning is considered for the second stage. The novel
proposed interpolation technique exploits the physics of the interconnections
between hydraulic heads of neighboring nodes in water distribution networks.
Additionally, residuals are directly interpolated instead of hydraulic head
values. The results of applying the proposed method to a well-known case study
(Modena) demonstrated the improvements of the new interpolation method with
respect to a state-of-the-art approach, both in terms of interpolation error
(considering state and residual estimation) and posterior localization.
