Exploring the Extraction of Knowledge from Previous Lessons and Disruptive Events in Water Distribution Networks

This work explores the various relationships between several parameters in an incident hub of a small real WDN. To facilitate analysis, incident data were previously categorised depending on the nature of the cause of the incident. The data are analysed through spatial analysis, based on the transmission of information from the surrounding areas, and are also incorporated to add certain uncertainty to the information. The results of this characterisation are presented and analysed in this contribution. The results are promising in providing water distribution networks with key parameters that promote prediction and classification processes from the lessons learned.