Predicting leakage rates through background losses and unreported burst modelling - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Communication Dans Un Congrès Année : 2007

Predicting leakage rates through background losses and unreported burst modelling

Résumé

Sustainable management of leaks in drinking water networks is a key issue for water distribution companies. Since it can reduce water losses and therefore groundwater abstraction operations, it is an important element in the assessment of facility and operator performance. The various phases in the process leading to the appearance and development of water losses are modelled. First, a distinction is made between background leaks and leaks due to larger bursts which are either detectable during a leak-finding operation or located visually. Next, a dynamic model for leakage (DML) is proposed, in order to explain the evolution of the volumes lost. The hypothesis of the DML model is that leaks evolve over time. They first appear as background leaks and then change into undetected bursts. Eventually they are located, either during a leak-finding operation or because they become visible. The model implements dynamic equilibriums between each stage in the form of differential equations. The model parameters are set by area of distribution in which there is a night flow history of around two years. The DML model can quantify the proportion of the leak flow which is retrievable by searching for and repairing leaks, and that which is due to background leaks and therefore retrievable by renewing pipes. It thus makes it possible to assess different asset management strategies.
Fichier non déposé

Dates et versions

hal-02590318 , version 1 (15-05-2020)

Identifiants

Citer

O. Chesneau, Bernard Brémond, Yves Le Gat. Predicting leakage rates through background losses and unreported burst modelling. WATER LOSS 2007 Bucarest, ROM, 2007, pp.12. ⟨hal-02590318⟩

Collections

IRSTEA INRAE
16 Consultations
0 Téléchargements

Partager

More