Ahmadi, M., Werey, C., Cherqui, F., Pffeifer, W., Le Gauffre, P., Stiftelsen for INdustriell og TEknisk Forskning [Trondheim] (SINTEF), Gestion Territoriale de l'Eau et de l'environnement (UMR GESTE), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Déchets Eaux Environnement Pollutions (DEEP), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon, Stiftelsen for INdustriell og TEknisk Forskning Digital [Trondheim] (SINTEF Digital), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon, Groupe Altéréo (G2C), Laboratoire de Génie Civil et d'Ingénierie Environnementale (LGCIE), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA), SDEA ALSACE FRA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Cherqui, Frédéric, and Irstea Publications, Migration
International audience; Infrastructure asset management (AM) ensures that the best decisions are made throughout asset life cycles in order to reduce risks, optimize performance and minimize costs (Marlow et al. 2009). Therefore, utilities need to produce and apply proactive AM programs in order to prioritize inspection, maintenance and rehabilitation requirements of their sewer assets, and thereby make best use of the limited funds available for this purpose (Ahmadi et al., 2014). However, even though most utilities are aware of the benefits of implementing AM practices, some important lacks related to data availability, human skills and organisational issues prevent them from realising these practices. According to a step-by-step implementation policy of these AM levels within utilities in France, in order to gear them up towards the application of strategic AM level, in the first step, a run-to-failure approach (level 1) was carried out on a part of a utility in the east of France (SDEA with a total length of sewer segments of 6000 km). The annual inspection rate of sewer segments within the studied area is equal to 3%. After an intensive phase of data gathering and reorganisation of the studied utility that we will report in the main article, the developed risk-based approach (Le Gauffre et al., 2010) was implemented in order to prioritise the rehabilitation needs of sewer network thanks to multicriteria analysis approaches.