Identifying biases in deterioration models using synthetic sewer data

Water Science and Technology

Volumn 66, Issue 11, 2012, Pages 2363-2369

  Scheidegger, A ^a   Maurer, M ^a  

^a SWISS FEDERAL INSTITUTE OF AQUATIC SCIENCE AND TECHNOLOGY   (Switzerland)

Author keywords

Cohort model; Markov model; NetCoS; Semi Markov chain; Sewer deterioration; Synthetic data

Indexed keywords

MARKOV MODEL; NETCOS; SEMI-MARKOV CHAIN; SEWER DETERIORATION; SYNTHETIC DATA;

DETERIORATION; ERRORS; MARKOV PROCESSES; PARAMETER ESTIMATION;

SEWERS;

COHORT ANALYSIS; ERROR ANALYSIS; MARKOV CHAIN; MODEL VALIDATION; PIPE; SEWER NETWORK; UNCERTAINTY ANALYSIS;

ARTICLE; CALIBRATION; CLASSIFICATION; DATA ANALYSIS; MEASUREMENT ERROR; PROBABILITY; SEWER; SEWER DETERIORATION MODEL; STATISTICAL MODEL;

DRAINAGE, SANITARY; MARKOV CHAINS; MODELS, THEORETICAL; SEWAGE; TIME FACTORS;

EID: 84872735910     PISSN: 02731223     EISSN: None     Source Type: Journal    
DOI: 10.2166/wst.2012.471     Document Type: Article

References (15)

1. Ana, E. V. & Bauwens, W. 2010 Modeling the structural deterioration of urban drainage pipes: the state-of-the-art in statistical methods. Urban Water 7 (1), 47.
2. Baur, R. & Herz, R. 2002 Selective inspection planning with ageing forecast for sewer types. Water Science and Technology 46 (6), 389-396.
3. Davies, J. P., Clarke, B. A., Whiter, J. T. & Cunningham, R J. 2001 Factors influencing the structural deterioration and collapse of rigid sewer pipes. Urban Water 3 (1-2), 73-89.
4. Dirksen, J. & Clemens, F. H. L. R 2008 Probabilistic modeling of sewer deterioration using inspection data. Water Science and Technology 57 (10), 1635-1641.
5. Dirksen, J., Clemens, F. H. L. R., Korving, H., Cherqui, F., Le Gauffre, P., Ertl, T., Plihal, H., Müller, K. & Snaterse, C. T. M. 2011 The consistency of visual sewer inspection data. Structure and Infrastructure Engineering.
6. Herz, R 1995 Alterung und Erneuerung von Infrastrukturbeständen - ein Kohortenüberlebensmodell (Aging and renewal of infrastructure - a cohort survival model). Jahrbuch für Regionalwissenschaft 14-15, 5-29.
7. Hüben, S. 2002 Einflüsse auf die Qualität der Zustandsklassifizierung von Kanalhaltungen (Effects on the quality of the condition state classification of sewers). Diploma thesis, RWTH Aachen, Germany.
8. Kleiner, Y. 2001 Scheduling inspection and renewal of large infrastructure assets. Journal of Infrastructure Systems 7 (4), 136.
9. Kleiner, Y. & Rajani, B. 2001 Comprehensive review of structural deterioration of water mains: statistical models. Urban Water 3 (3), 131-150.
10. Maurer, M. 2009 Specific net present value: an improved method for assessing modularisation costs in water services with growing demand. Water Research 43 (8), 2121-2130.
11. Müller, K 2006 Strategien zur Zustandserfassung von Kanalisationen (Strategies to capture the condition state of sewers). Aachner Schriften zur Stadtentwässerung 7.
12. Scheidegger, A., Hug, T., Rieckermann, J. & Maur, M. 2011 Network condition simulator for benchmarking sewer deterioration models. Water Research 45 (16), 4983-4994.
13. Tran, H. D. 2007 Investigation of deterioration models for stormwater pipe systems. PhD thesis, Victoria University, Melbourne, Australia.
14. Wirahadikusumah, R., Abraham, D. & Iseley, T 2001 Challenging issues in modeling deterioration of combined sewers. Journal of Infrastructure Systems 7 (2), 77.
15. WRc 1986 Sewer Rehabilitation Manual, 2nd edition. Water Research Centre plc, UK.