Automatic mapping of urban wastewater networks based on manhole cover locations

    Par
    Jean Cavailhès
    -
    (), Volume 78, November 2019, 101370

     Présentation (FED) : Les auteurs proposent deux algorithmes permettant de cartographier les réseaux d'assainissement des villes à partir de la localisation des plaques d’égout, connues via des enquêtes au sol, des techniques de télédétection ou des bases de données. Le réseau souterrain est reconstitué. La méthode est testée sur les réseaux d'assainissement de Prades-le-Lez et de Ramnonville Saint Agne, deux communes situées dans le sud de la France. Les résultats indiquent un bon accord global entre les réseaux réels et générés par l’algorithme.

    Abstract (authors) : Accurate maps of wastewater networks in cities are mandatory for an integrated management of water resources. However, in many countries around the world this information is unavailable or inaccurate. A new mapping method is put forward to create maps using manhole cover locations which could be available via ground surveys, remote sensing techniques or stakeholder's databases. A new algorithm is developed which considers manhole covers as the nodes of the network and connects them automatically by minimizing cost functions defined by industry rules thus generating an optimized network. The various input data and rules used to build the deterministic tree-shaped graph being uncertain, a stochastic version of the algorithm is also proposed to generate a set of probable networks in addition to the optimized one. The method is tested on the wastewater networks of Prades-le-Lez and Ramnonville Saint Agne, two towns located in Southern France. The shape and topology of the mapped networks are compared to the actual one. The results indicate an overall good agreement between the real and generated networks. The proposed algorithm may thus be used to map wastewater networks from sampled georeferenced manhole covers, elevation and street network databases.

    Lien : https://www.sciencedirect.com/science/article/pii/S0198971518306379#bb0170