The relevance of sewer deterioration modelling to support asset management strategies

References

• Ahmadi, M., et al., 2014a. Influence of available data on sewer inspection program efficiency. Urban Water Journal, 11 (8), 641–656.10.1080/1573062X.2013.831910
   Web of Science ®Google Scholar
• Ahmadi, M., et al., 2014b. Condition grading for dysfunction indicators in sewer asset management. Structure and Infrastructure Engineering: Maintenance, Management, Life-Cycle Design and Performance, 10 (3), 346–358.10.1080/15732479.2012.756916
   Web of Science ®Google Scholar
• Ahmadi, M., et al., 2015. Benefits of using basic, imprecise or uncertain data for elaborating sewer inspection programmes. Structure and Infrastructure Engineering: Maintenance, Management, Life-Cycle Design and Performance, 11 (3), 376–388.10.1080/15732479.2014.887122
   Web of Science ®Google Scholar
• Alegre, H. and Matos, R., 2009. Paving the way for a sustainable asset management of urban water infrastructures: outcomes of the 5th World Water Forum. Water Asset Management International, 5 (2), 2.
   Google Scholar
• American Water Works Association, 2012. Buried no longer: confronting America’s water infrastructure challenge, AWWA’s infrastructure financing report, Boulder, CO.
   Google Scholar
• Ana, E.V. and Bauwens, W., 2010. Modeling the structural deterioration of urban drainage pipes: the state-of-the-art in statistical methods. Urban Water Journal, 7 (1), 47–59.10.1080/15730620903447597
   Web of Science ®Google Scholar
• Ana, E.V., et al., 2009. An investigation of the factors influencing sewer structural deterioration. Urban Water Journal, 6 (4), 303–312.10.1080/15730620902810902
   Web of Science ®Google Scholar
• Ariaratnam, S., El-Assaly, A. and Yang, Y., 2001. Assessment of infrastructure inspection needs using logistic models. Journal of Infrastructure Systems, 7 (4), 160–165.10.1061/(ASCE)1076-0342(2001)7:4(160)
   Google Scholar
• ASCE, 2011. Failure to act: the economic impact of current investment trends in water and wastewater treatment infrastructure, ASCE report, Reston, VA.
   Google Scholar
• Baur, R. and Herz, R., 2002. Selective inspection planning with ageing forecast for sewer types. Water Science and Technology, 46 (6–7), 389–396.
   PubMed Web of Science ®Google Scholar
• Black and Veatch, 2013. 2013 Strategic direction in the U.S. water industry, Black and Veatch report, Overland Park, KS.
   Google Scholar
• Chughtai, F. and Zayed, T., 2008. Infrastructure condition prediction models for sustainable sewer pipelines. Journal of Performance of Constructed Facilities, 22 (5), 333–341.10.1061/(ASCE)0887-3828(2008)22:5(333)
   Web of Science ®Google Scholar
• Davies, J.P., et al., 2001. Factors influencing the structural deterioration and collapse of rigid sewer pipes. Urban Water, 3 (1-2), 73–89.10.1016/S1462-0758(01)00017-6
   Google Scholar
• Fuchs-Hanusch, D., et al., 2015. Cause and effect oriented sewer degradation evaluation to support scheduled inspection planning. Water Science and Technology, 72 (7), 1176–1183.10.2166/wst.2015.320
   PubMed Web of Science ®Google Scholar
• Harvey, R. and McBean, E., 2014. Predicting the structural condition of individual sanitary sewer pipes with random forests. Canadian Journal of Civil Engineering, 41 (4), 294–303.10.1139/cjce-2013-0431
   Web of Science ®Google Scholar
• IPK, Impulse Pro Kanalbau, 2014. Forderungskatalog 2014: Forderungskatalog für funktionsfähige öffentliche und private Abwasseranlage [Requirements for operational public and private sewer systems].
   Google Scholar
• Khan, Z., Zayed, T. and Moselhi, O., 2010. Structural condition assessment of sewer pipelines. Journal of Performance of Constructed Facilities, 24 (2), 170–179.10.1061/(ASCE)CF.1943-5509.0000081
   Web of Science ®Google Scholar
• Kley, G., Caradot, N., 2013. Review of sewer deterioration models, KWB project SEMA, Report 1.2, available on KWB website, 43, Berlin, Germany.
   Google Scholar
• Kley, G., et al., 2013. Review of technologies and methodologies for sewer condition evaluation, KWB project SEMA, Report 1.1, available on KWB website, 39, Berlin, Germany.
   Google Scholar
• Le Gat, Y., 2008. Modelling the deterioration process of drainage pipelines. Urban Water Journal, 5 (2), 97–106.10.1080/15730620801939398
   Web of Science ®Google Scholar
• Le Gauffre, P., et al., 2004. Gestion patrimoniale des réseaux d’assainissement urbains, Guide méthodologique [Asset Management of urban sewer networks. Methodological guide], 416. Paris: Lavoisier Tec & Doc.
   Google Scholar
• Marlow, D. and Beale, D., 2012. Towards an economic decision methodology for remaining asset life. CSIRO, Report Water Environment Research Foundation (WERF).
   Google Scholar
• Micevski, T., Kuczera, G. and Coombes, P., 2002. Markov model for storm water pipe deterioration. Journal of Infrastructure Systems, 8 (2), 49–56.10.1061/(ASCE)1076-0342(2002)8:2(49)
   Google Scholar
• ONEMA, 2012. Observatory on public water and sanitation services, overview of services and of their performance. France: French National Agency for Water and Aquatic Environments.
   Google Scholar
• Rajani, B. and Kleiner, Y., 2001. Comprehensive review of structural deterioration of water mains: statistical models. Urban Water Journal, 3 (3), 131–150.10.1016/S1462-0758(01)00033-4
   Google Scholar
• Rokstad, M.M. and Ugarelli, R., 2015. Evaluating the role of deterioration models for condition assessment of sewers. Journal of Hydroinformatics, 17 (5), 789–804.10.2166/hydro.2015.122
   Web of Science ®Google Scholar
• Scheidegger, A., et al., 2011. Network condition simulator for benchmarking sewer deterioration models. Water Research, 45 (16), 4983–4994.10.1016/j.watres.2011.07.008
   PubMed Web of Science ®Google Scholar
• Scheidegger, A., et al., 2013. Extension of pipe failure models to consider the absence of data from replaced pipes. Water Research, 47 (11), 3696–3705.10.1016/j.watres.2013.04.017
   PubMed Web of Science ®Google Scholar
• Schmidt, T., 2009. Modellierung von Kanalalterungsprozessen auf der Basis von Zustandsdaten [Modelling sewer deterioration processes using condition data]. Thesis (PhD). Institut für Stadtbauwesen und Straßenbau, Technical University Dresden, Dresden, Germany.
   Google Scholar
• Sousa, V., Matos, J.P. and Matias, N., 2014. Evaluation of artificial intelligence tool performance and uncertainty for predicting sewer structural condition. Automation in Construction, 44, 84–91.10.1016/j.autcon.2014.04.004
   Web of Science ®Google Scholar
• Syachrani, S., Jeong, H. and Chung, C., 2013. Decision tree–based deterioration model for buried wastewater pipelines. Journal of Performance of Constructed Facilities, 27 (5), 633–645.10.1061/(ASCE)CF.1943-5509.0000349
   Web of Science ®Google Scholar
• Tran, D., Perera, A.W.M. and Davis, P., 2006. Application of probabilistic neural networks in modeling structural deterioration of stormwater pipes. Urban Water Journal, 3 (3), 175–184.10.1080/15730620600961684
   Google Scholar
• WERF, 2007. Infrastructure management final report: condition assessment strategies and protocols for water and wastewater utility assets. US: Water Environment Research Foundation.
   Google Scholar
• Wirahadikusumah, R., Abraham, D. and Iseley, T., 2001. Challenging issues in modeling deterioration of combined sewers. Journal of Infrastructure Systems, 7 (2), 77–84.10.1061/(ASCE)1076-0342(2001)7:2(77)
   Google Scholar