From CCTV Data to Strategic Planning: Deterioration Modelling for Large Sewer Networks in Germany and Colombia

5 pages•Published: September 20, 2018

Nicolas Caradot, Nathalie Hernandez, Hauke Sonnenberg, Andres Torres and Pascale Rouault

Abstract

Most cities are facing an aging sewer infrastructure in extensive and emerging need of repair, rehabilitation or renewal. Deterioration modelling can be a valued data mining tool to tackle this issue by supporting utilities in defining strategic investment planning. This study aims to demonstrate the benefits of deterioration modelling using sewer CCTV inspection data and GIS characteristics (material, age, depth, width, traffic load, etc.) of two different cities: Braunschweig in Germany and Bogota in Colombia. A probabilistic Markov-based model has been applied to identify and exploit relationships between sewer condition and characteristics in the extensive datasets of the two cities. The quality of prediction of the model has been evaluated by analyzing the deviation between model observations and model predictions. Results show relatively low deviations (< 15%) indicating a satisfying model performance in both cities and underlining the relevance of deterioration models to simulate the condition of sewer networks and to support strategic asset management.

Keyphrases: asset management, data mining, modeling, statistic, strategic planning

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 351-355.

Links:	https://easychair.org/publications/paper/fBtt
	https://doi.org/10.29007/nbx2

BibTeX entry

@inproceedings{HIC2018:From_CCTV_Data_Strategic,
  author    = {Nicolas Caradot and Nathalie Hernandez and Hauke Sonnenberg and Andres Torres and Pascale Rouault},
  title     = {From CCTV Data to Strategic Planning: Deterioration Modelling for Large Sewer Networks in Germany and Colombia},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/fBtt},
  doi       = {10.29007/nbx2},
  pages     = {351-355},
  year      = {2018}}

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