Challenges of integrated multi-infrastructure asset management: a review of pavement, sewer, and water distribution networks

References

• Abu-Samra, S., Ahmed, M., & Amador, L. (2020). Asset management framework for integrated municipal infrastructure. Journal of Infrastructure Systems, 26(4), 04020039. doi:10.1061/(ASCE)IS.1943-555X.0000580
   Web of Science ®Google Scholar
• Abu Samra, S., Ahmed, M., Hammad, A., & Zayed, T. (2018). Multiobjective framework for managing municipal integrated infrastructure. Journal of Construction Engineering and Management, 144(1), 04017091. doi:10.1061/(ASCE)CO.1943-7862.0001402
   Web of Science ®Google Scholar
• Alinizzi, M., Chen, S., Labi, S., & Kandil, A. (2018). A methodology to account for one-way infrastructure interdependency in preservation activity scheduling. Computer-Aided Civil and Infrastructure Engineering, 33(11), 905–925. doi:10.1111/mice.12380
   Web of Science ®Google Scholar
• Amador, L. E., & Magnuson, S. (2011). Adjacency modeling for coordination of investments in infrastructure asset management: Case study of Kindersley, Saskatchewan, Canada. Transportation Research Record: Journal of the Transportation Research Board, 2246(1), 8–15. doi:10.3141/2246-02
   Google Scholar
• Anbari, M. J., Tabesh, M., & Roozbahani, A. (2017). Risk assessment model to prioritize sewer pipes inspection in wastewater collection networks. Journal of Environmental Management, 190, 91–101. doi:10.1016/j.jenvman.2016.12.052.
   PubMed Web of Science ®Google Scholar
• Barton, N. A., Farewell, T. S., Hallett, S. H., & Acland, T. F. (2019). Improving pipe failure predictions: Factors effecting pipe failure in drinking water networks. Water Research, 164, 114926. doi:10.1016/j.watres.2019.114926.
   PubMed Web of Science ®Google Scholar
• Brous, P., Janssen, M., & Herder, P. (2019). Internet of Things adoption for reconfiguring decision-making processes in asset management. Business Process Management Journal, 25(3), 495–511. doi:10.1108/BPMJ-11-2017-0328
   Web of Science ®Google Scholar
• Callcut, M., Agliozzo, J.-P. C., Varga, L., & Mcmillan, L. (2021). Digital twins in civil infrastructure systems. Sustainability, 13(20), 11549. doi:10.3390/su132011549
   Web of Science ®Google Scholar
• Caradot, N., Riechel, M., Fesneau, M., Hernandez, N., Torres, A., Sonnenberg, H., … Rouault, P. (2018). Practical benchmarking of statistical and machine learning models for predicting the condition of sewer pipes in Berlin, Germany. Journal of Hydroinformatics, 20(5), 1131–1147. doi:10.2166/hydro.2018.217
   Web of Science ®Google Scholar
• Caradot, N., Riechel, M., Rouault, P., Caradot, A., Lengemann, N., Eckert, E., … Cherqui, F. (2020). The influence of condition assessment uncertainties on sewer deterioration modelling. Structure and Infrastructure Engineering, 16(2), 287–296. doi:10.1080/15732479.2019.1653938
   Web of Science ®Google Scholar
• Carey, B. D., & Lueke, J. S. (2013). Optimized holistic municipal right-of-way capital improvement planning. Canadian Journal of Civil Engineering, 40(12), 1244–1251. doi:10.1139/cjce-2012-0183
   Web of Science ®Google Scholar
• Conejos Fuertes, P., Martínez Alzamora, F., Hervás Carot, M., & Alonso Campos, J. (2020). Building and exploiting a digital twin for the management of drinking water distribution networks. Urban Water Journal, 17, 704–713. doi:10.1080/1573062X.2020.1771382
   Web of Science ®Google Scholar
• Costin, A., Adibfar, A., Hu, H., & Chen, S. S. (2018). Building Information Modeling (BIM) for transportation infrastructure – Literature review, applications, challenges, and recommendations. Automation in Construction, 94, 257–281. doi:10.1016/j.autcon.2018.07.001
   Web of Science ®Google Scholar
• Dawood, T., Elwakil, E., Novoa, H. M., & Gárate Delgado, J. F. (2020). Water pipe failure prediction and risk models: State-of-the-art review. Canadian Journal of Civil Engineering, 47(10), 1117–1127. doi:10.1139/cjce-2019-0481
   Web of Science ®Google Scholar
• Dirksen, J., Clemens, F. H. L. R., Korving, H., Cherqui, F., Le Gauffre, P., Ertl, T., … Snaterse, C. T. M. (2013). The consistency of visual sewer inspection data. Structure and Infrastructure Engineering, 9(3), 214–228. doi:10.1080/15732479.2010.541265
   Web of Science ®Google Scholar
• Dubbeldam, F., Begeer, R., Smiers, R., van Hoek, H., de Jong, J., Vlaar, T., … Veerkamp, J. (2020). Werkplan Ondergrond 2020: Integrale benadering Amsterdamse Ondergrond [Underground work plan 2020: Integrated approach to the Amsterdam’s underground]. Amsterdam, the Netherlands: Gemeente Amsterdam.
   Google Scholar
• Elsawah, H., Bakry, I., & Moselhi, O. (2016). Decision support model for integrated risk assessment and prioritization of intervention plans of municipal infrastructure. Journal of Pipeline Systems Engineering and Practice, 7(4), 04016010. doi:10.1061/(ASCE)PS.1949-1204.0000245
   Web of Science ®Google Scholar
• Elsawah, H., Guerrero, M., & Moselhi, O. (2014). Decision support model for integrated intervention plans of municipal infrastructure. ICSI 2014: Creating Infrastructure for a Sustainable World - Proceedings of the 2014 International Conference on Sustainable Infrastructure (pp. 1039–1050). doi:10.1061/9780784478745.098
   Google Scholar
• Fani, A., Golroo, A., Ali Mirhassani, S., & Gandomi, A. H. (2022). Pavement maintenance and rehabilitation planning optimisation under budget and pavement deterioration uncertainty. International Journal of Pavement Engineering, 23(2), 414–424. doi:10.1080/10298436.2020.1748628
   Web of Science ®Google Scholar
• Flintsch, G. W., & McGhee, K. K. (2009). NCHRP Synthesis 401: Quality management of pavement condition data collection. Washington, DC: Transportation Research Board of the National Academies.
   Google Scholar
• García-Segura, T., Montalbán-Domingo, L., Llopis-Castelló, D., Lepech, M. D., Sanz, M. A., & Pellicer, E. (2022). Incorporating pavement deterioration uncertainty into pavement management optimization. International Journal of Pavement Engineering, 23(6), 2062–2073. doi:10.1080/10298436.2020.1837827
   Web of Science ®Google Scholar
• Garramone, M., Moretti, N., Scaioni, M., Ellul, C., Re Cecconi, F., & Dejaco, M. C. (2020). BIM and GIS integration for infrastructure asset management: A bibliometric analysis. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, VI-4/W1-2020(4/W1), 77–84. doi:10.5194/isprs-annals-VI-4-W1-2020-77-2020
   Google Scholar
• Gillette, J., Fisher, R., Peerenboom, J., & Whitfield, R. (2002). Analyzing water/wastewater infrastructure interdependencies. Analyzing water/wastewater infrastructure interdependencies (No. ANL/DIS/CP-107254). Lemont, IL: Argonne National Lab. www.ipd.anl.gov/anlpubs/2002/03/42598.pdf.
   Google Scholar
• Guy, S., Marvin, S., & Moss, T. (2001). Urban infrastructure in transition: Networks, buildings plans. London: Earthscan.
   Google Scholar
• Haas, R., Hudson, W. R., & Falls, L. C. (2015). Pavement asset management. Beverly, MA: Scrivener Publishing LLC.
   Google Scholar
• Hafskjold, L. S. (2010). SIP - Future rehabilitation strategies for physical infrastructure: Coordination of rehabilitation planning and measures - co-infrastructure interactions. SINTEF (Report No. SBF IN A10316). doi:10.1080/02508068008685878
   Google Scholar
• Halfawy, M. R. (2008). Integration of municipal infrastructure asset management processes: Challenges and solutions. Journal of Computing in Civil Engineering, 22(3), 216–229. doi:10.1061/(ASCE)0887-3801(2008)22:3(216)
   Web of Science ®Google Scholar
• Halfawy, M. R. (2010). Municipal information models and federated software architecture for implementing integrated infrastructure management environments. Automation in Construction, 19(4), 433–446. doi:10.1016/j.autcon.2009.11.013
   Web of Science ®Google Scholar
• Han, D., & Lee, S. H. (2016). Stochastic fo recasting of life expectancies considering multi-maintenance criteria and localized uncertainties in the pavement-deterioration process. Journal of Testing and Evaluation, 44(1), 20140246–20140140. doi:10.1520/JTE20140246
   Web of Science ®Google Scholar
• Haugen, H. J. (2018). Rørinspeksjon av hovedledninger for vann og avløp 234/2018 [Interior inspection of main pipes for water and wastewater]. Hamar, Norway: Norsk Vann BA.
   Google Scholar
• Hawari, A., Alkadour, F., Elmasry, M., & Zayed, T. (2020). A state of the art review on condition assessment models developed for sewer pipelines. Engineering Applications of Artificial Intelligence, 93, 103721. doi:10.1016/j.engappai.2020.103721
   Web of Science ®Google Scholar
• InfraGuide. (2003a). An Integrated approach to assessment and evaluation of municipal road, sewer and water networks. Federation of Canadian Municipalities and National Research Council, National Guide to Sustainable Municipal Infrastructure, Ottawa.
   Google Scholar
• InfraGuide. (2003b). Coordinating infrastructure works: A best practice by the national guide to sustainable municipal infrastructure. In Federation of Canadian Municipalities and National Research Council, National Guide to Sustainable Municipal Infrastructure, Ottawa.
   Google Scholar
• Islam, T., & Moselhi, O. (2012). Modeling geospatial interdependence for integrated municipal infrastructure. Journal of Infrastructure Systems, 18(2), 68–74. doi:10.1061/(ASCE)IS.1943-555X.0000065
   Web of Science ®Google Scholar
• ISO 55000:2014 (2014). Asset management - overview, principles and terminology. Geneva, Switzerland: International Organization for Standardization.
   Google Scholar
• Johansson, J., & Hassel, H. (2010). An approach for modelling interdependent infrastructures in the context of vulnerability analysis. Reliability Engineering & System Safety, 95(12), 1335–1344. doi:10.1016/j.ress.2010.06.010
   Web of Science ®Google Scholar
• Kabir, G., Tesfamariam, S., Loeppky, J., & Sadiq, R. (2015). Integrating Bayesian linear regression with ordered weighted averaging: Uncertainty analysis for predicting water main failures. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 1(3), 04015007. doi:10.1061/AJRUA6.0000820
   Google Scholar
• Kammouh, O., Nogal, M., Binnekamp, R., & Wolfert, A. R. M. R. (2021). Multi-system intervention optimization for interdependent infrastructure. Automation in Construction, 127, 103698. doi:10.1016/j.autcon.2021.103698
   Web of Science ®Google Scholar
• Khameneh, A. P., Lavasani, M. S. M., Nodehi, N. R., & Arjmandi, R. (2020). Water distribution network failure analysis under uncertainty. International Journal of Environmental Science and Technology, 17(1), 421–432. doi:10.1007/s13762-019-02362-y
   Web of Science ®Google Scholar
• Kielhauser, C. (2018). A method for determining optimal intervention programs for interrelated infrastructure networks (Doctoral dissertation). Zürich, Switzerland: ETH Zurich. doi:10.3929/ethz-b-000269313
   Google Scholar
• Kielhauser, C., Adey, B. T., & Lethanh, N. (2017). Investigation of a static and a dynamic neighbourhood methodology to develop work programs for multiple close municipal infrastructure networks. Structure and Infrastructure Engineering, 13(3), 361–389. doi:10.1080/15732479.2016.1162818
   Web of Science ®Google Scholar
• Kırbaş, U., & Karaşahin, M. (2016). Performance models for hot mix asphalt pavements in urban roads. Construction and Building Materials, 116, 281–288. doi:10.1016/j.conbuildmat.2016.04.118
   Web of Science ®Google Scholar
• Kleiner, Y., Nafi, A., & Rajani, B. (2010). Planning renewal of water mains while considering deterioration, economies of scale and adjacent infrastructure. Water Supply, 10(6), 897–906. doi:10.2166/ws.2010.571
   Google Scholar
• Kleiner, Y., & Rajani, B. (2001). Comprehensive review of structural deterioration of water mains: Statistical models Rajani, B.B.; Kleiner, Y. NRCC-43722. Urban Water, 3(3), 131–150. www.elsevier.com/locate/urbwat. doi:10.1016/S1462-0758(01)00032-2
   Google Scholar
• Kumar, S. S., Abraham, D. M., Jahanshahi, M. R., Iseley, T., & Starr, J. (2018). Automated defect classification in sewer closed circuit television inspections using deep convolutional neural networks. Automation in Construction, 91, 273–283. doi:10.1016/j.autcon.2018.03.028
   Web of Science ®Google Scholar
• Le Gat, Y. (2008). Modelling the deterioration process of drainage pipelines. Urban Water Journal, 5(2), 97–106. doi:10.1080/15730620801939398
   Web of Science ®Google Scholar
• Li, J., Yang, X., & Sitzenfrei, R. (2020). Rethinking the Framework of Smart Water System. Review Water, 12(2), 412. doi:10.3390/w12020412
   Web of Science ®Google Scholar
• Liu, X., Wang, X., Wright, G., Cheng, J. C. P., Li, X., & Liu, R. (2017). A state-of-the-art review on the integration of Building Information Modeling (BIM) and Geographic Information System (GIS). ISPRS International Journal of Geo-Information, 6(2), 53–21. doi:10.3390/ijgi6020053
   Web of Science ®Google Scholar
• Lu, Q., Xie, X., Heaton, J., Parlikad, A. K., & Schooling, J. (2020). From BIM towards digital twin: Strategy and future development for smart asset management. Studies in Computational Intelligence, 853, 392–404. doi:10.1007/978-3-030-27477-1_30
   Google Scholar
• Mair, M., Zischg, J., Rauch, W., & Sitzenfrei, R. (2017). Where to find water pipes and sewers?-On the correlation of infrastructure networks in the urban environment. Water (Switzerland), 9(2), 146. doi:10.3390/w9020146
   Google Scholar
• Makropoulos, C., & Savic, D. A. (2019). Urban hydroinformatics: Past, present and future. Water, 11(10), 1959. doi:10.3390/w11101959
   Web of Science ®Google Scholar
• Marlow, D., Davis, P., Trans, D., Beale, D., Burn, S., & Urquhart, A. (2009). Remaining asset life: A state of the art review. Water environment research foundation. London: IWA Publishing. doi:10.2166/9781780403427
   Google Scholar
• Marlow, D., Pearson, L., MacDonald, D. H., Whitten, S., & Burn, S. (2011). A framework for considering externalities in urban water asset management. Water Science and Technology, 64(11), 2199–2206. doi:10.2166/wst.2011.789
   PubMed Web of Science ®Google Scholar
• Marzouk, M., & Osama, A. (2015). Fuzzy approach for optimum replacement time of mixed infrastructures. Civil Engineering and Environmental Systems, 32(3), 269–280. doi:10.1080/10286608.2014.1002715
   Web of Science ®Google Scholar
• Meijer, D., Scholten, L., Clemens, F., & Knobbe, A. (2019). A defect classification methodology for sewer image sets with convolutional neural networks. Automation in Construction, 104, 281–298. doi:10.1016/j.autcon.2019.04.013
   Web of Science ®Google Scholar
• Menendez, J. R., & Gharaibeh, N. G. (2017). Incorporating risk and uncertainty into infrastructure asset management plans for pavement networks. Journal of Infrastructure Systems, 23(4), 04017019. doi:10.1061/(ASCE)IS.1943-555X.0000379
   Web of Science ®Google Scholar
• Metayer, G., Torres-Machi, C., & Bastias, A. (2020). A proposed framework for the integrated management of municipal infrastructure. Construction Research Congress, 2020, 846–855. 10.1061/9780784482865%0Ahttps://trid.trb.org/view/1760497.
   Google Scholar
• Michaud, D., & Apostolakis, G. E. (2006). Methodology for ranking the elements of water-supply networks. Journal of Infrastructure Systems, 12(4), 230–242. doi:10.1061/(ASCE)1076-0342(2006)12:4(230)
   Web of Science ®Google Scholar
• Mohammadi, M. M., Najafi, M., Kaushal, V., Serajiantehrani, R., Salehabadi, N., & Ashoori, T. (2019). Sewer pipes condition prediction models: A state-of-the-art review. Infrastructures, 4(4), 64–16. doi:10.3390/infrastructures4040064
   Google Scholar
• Myrans, J., Everson, R., & Kapelan, Z. (2018). Automated detection of faults in sewers using CCTV image sequences. Automation in Construction, 95, 64–71. doi:10.1016/j.autcon.2018.08.005
   Web of Science ®Google Scholar
• Nafi, A., & Kleiner, Y. (2010). Scheduling renewal of water pipes while considering adjacency of infrastructure works and economies of scale. Journal of Water Resources Planning and Management, 136(5), 519–530. doi:10.1061/(ASCE)WR.1943-5452.0000062
   Web of Science ®Google Scholar
• Nakamura, E., & Sakai, H. (2020). Does vertical integration facilitate coordination between infrastructure management and train operating units in the rail sector? Implications for Japanese railways. Utilities Policy, 66, 101099. doi:10.1016/j.jup.2020.101099
   Web of Science ®Google Scholar
• NSW SOCC. (2018). Guide to codes and practices for streets opening. NSW, Australia: NSW SOCC.
   Google Scholar
• NYC DOT. (2019). Highway rules, title 34, Chapter 2: Rules of the city of New York. New York, NY: Department of Transportation.
   Google Scholar
• Okuda, T., Suzuki, K., & Kohtake, N. (2018). Non-parametric prediction interval estimate for uncertainty quantification of the prediction of road pavement deterioration. IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, 2018-Novem, 824–830. doi:10.1109/ITSC.2018.8569337
   Google Scholar
• Okwori, E., Pericault, Y., Ugarelli, R., Viklander, M., & Hedström, A. (2021). Data-driven asset management in urban water pipe networks: A proposed conceptual framework. Journal of Hydroinformatics, 23(5), 1014–1029. doi:10.2166/hydro.2021.068
   Web of Science ®Google Scholar
• Ong, G. P., Noureldin, S., & Sinha, K. C. (2010). Automated pavement condition data collection quality control, quality assurance and reliability. Report FHWA/IN/JTRP-2009/17. West Lafayette, IN: Purdue University.
   Google Scholar
• Osman, H. (2016). Coordination of urban infrastructure reconstruction projects. Structure and Infrastructure Engineering, 12(1), 108–121. doi:10.1080/15732479.2014.995677
   Web of Science ®Google Scholar
• Ouyang, M. (2014). Review on modeling and simulation of interdependent critical infrastructure systems. Reliability Engineering & System Safety, 121, 43–60. doi:10.1016/j.ress.2013.06.040
   Web of Science ®Google Scholar
• Ouyang, M., Hong, L., Mao, Z. J., Yu, M. H., & Qi, F. (2009). A methodological approach to analyze vulnerability of interdependent infrastructures. Simulation Modelling Practice and Theory, 17(5), 817–828. doi:10.1016/j.simpat.2009.02.001
   Web of Science ®Google Scholar
• Papageorgiou, G. (2019). Appraisal of road pavement evaluation methods. Journal of Engineering Science and Technology Review, 12(6), 158–166. doi:10.25103/jestr.126.20
   Google Scholar
• Parlikad, K., & Jafari, M. (2016). Challenges in infrastructure asset management. IFAC-Papers Online, 49(28), 185–190. doi:10.1016/j.ifacol.2016.11.032
   Google Scholar
• Peraka, N. S. P., & Biligiri, K. P. (2020). Pavement asset management systems and technologies: A review. Automation in Construction, 119, 103336. doi:10.1016/j.autcon.2020.103336
   Web of Science ®Google Scholar
• Pierce, L. M., McGovern, G., & Zimmerman, K. A. (2013). Practical guide for quality management of pavement condition data collection. Practical guide for quality management of pavement condition data collection. https://www.fhwa.dot.gov/pavement/management/qm/data_qm_guide.pdf.
   Google Scholar
• Rajani, B., & Kleiner, Y. (2001). Comprehensive review of structural deterioration of water mains: Physically based models. Urban Water, 3(3), 151–164. doi:10.1016/S1462-0758(01)00032-2
   Google Scholar
• Ramos, C., Muñuzuri, J., Aparicio-Ruiz, P., & Onieva, L. (2021). A decision support system to design water supply and sewer pipes replacement intervention programs. Reliability Engineering & System Safety, 216, 107967. doi:10.1016/j.ress.2021.107967
   Web of Science ®Google Scholar
• Rinaldi, S. M., Peerenboom, J. P., & Kelly, T. K. (2001). Identifying, understanding, and analyzing critical infrastructure interdependencies. IEEE Control Systems Magazine, 21(6), 11–25. doi:10.1109/37.969131
   Web of Science ®Google Scholar
• Rogers, C. D. F., Hao, T., Costello, S. B., Burrow, M. P. N., Metje, N., Chapman, D. N., … Saul, A. J. (2012). Condition assessment of the surface and buried infrastructure - A proposal for integration. Tunnelling and Underground Space Technology, 28(1), 202–211. doi:10.1016/j.tust.2011.10.012
   Google Scholar
• Rokstad, M. M., & Ugarelli, R. M. (2015). Evaluating the role of deterioration models for condition assessment of sewers. Journal of Hydroinformatics, 17(5), 789–804. doi:10.2166/hydro.2015.122
   Web of Science ®Google Scholar
• Rokstad, M. M., & Ugarelli, R. M. (2016). Improving the benefits of sewer condition deterioration modelling through information content analysis. Water Science and Technology: A Journal of the International Association on Water Pollution Research, 74(10), 2270–2279. 10.2166/wst.2016.419.
   PubMed Web of Science ®Google Scholar
• Rose, S., Mathew, B. S., Isaac, K. P., Abhaya, A. S., Rose, S., Mathew, B. S., … Abhaya, A. S. (2018). Risk based probabilistic pavement deterioration prediction models for low volume roads. International Journal of Pavement Engineering, 19(1), 88–97. doi:10.1080/10298436.2016.1162308
   Web of Science ®Google Scholar
• Saad, D. A., & Hegazy, T. (2017). Economic optimization for the rehabilitation of co-located mixed assets. Canadian Journal of Civil Engineering, 44(10), 820–828. doi:10.1139/cjce-2016-0509
   Web of Science ®Google Scholar
• Saha, P., & Ksaibati, K. (2016). A risk-based optimisation methodology for pavement management system of county roads. International Journal of Pavement Engineering, 17(10), 913–923. doi:10.1080/10298436.2015.1065992
   Web of Science ®Google Scholar
• Salman, B., & Salem, O. (2012). Risk assessment of wastewater collection lines using failure models and criticality ratings. Journal of Pipeline Systems Engineering and Practice, 3(3), 68–76. doi:10.1061/(ASCE)PS.1949-1204.0000100
   Web of Science ®Google Scholar
• Shah, Y. U., Jain, S. S., Tiwari, D., & Jain, M. K. (2013). Development of overall pavement condition index for urban road network. Procedia - Social and Behavioral Sciences, 104, 332–341. doi:10.1016/j.sbspro.2013.11.126
   Google Scholar
• Shahata, K., & Zayed, T. (2010). Integrated decision-support framework for municipal infrastructure asset. Pipelines 2010: Climbing New Peaks to Infrastructure Reliability - Renew, Rehab, and Reinvest - Proceedings of the Pipelines 2010 Conference (Vol. 386, pp. 1492–1502). January 2018. doi:10.1061/41138(386)145
   Google Scholar
• Shahata, K., & Zayed, T. (2016). Integrated risk-assessment framework for municipal infrastructure. Journal of Construction Engineering and Management, 142(1), 04015052. doi:10.1061/(ASCE)CO.1943-7862.0001028
   Web of Science ®Google Scholar
• Silva, B. N., Khan, M., & Han, K. (2018). Towards sustainable smart cities: A review of trends, architectures, components, and open challenges in smart cities. Sustainable Cities and Society, 38, 697–713. doi:10.1016/j.scs.2018.01.053
   Web of Science ®Google Scholar
• Torbaghan, E. M., Curioni, G., Hayati, F., Royal, A. C., Chapman, D. N., Atkins, P. R., & Rogers, C. D. (2020). Investigating the relationship between trenching practice and road deterioration. Infrastructure Asset Management, 7(4), 282–296. doi:10.1680/jinam.19.00052
   Web of Science ®Google Scholar
• Tscheikner-Gratl, F. (2016). (Integrated approach for multi-utility rehabilitation planning of urban water infrastructure: Focus on small and medium sized municipalities). (Doctoral Dissertation, University of Innsbruck). https://www.uibk.ac.at/umwelttechnik/teaching/phd/dissertation_ftg_ohne_papers.pdf.
   Google Scholar
• Tscheikner-Gratl, F., Caradot, N., Cherqui, F., Leitão, J. P., Ahmadi, M., Langeveld, J. G., … Clemens, F. (2019). Sewer asset management–state of the art and research needs. Urban Water Journal, 16(9), 662–675. doi:10.1080/1573062X.2020.1713382
   Web of Science ®Google Scholar
• Tscheikner-Gratl, F., Egger, P., Rauch, W., & Kleidorfer, M. (2017). Comparison of multi-criteria decision support methods for integrated rehabilitation prioritization. Water, 9(2), 68. doi:10.3390/w9020068
   Web of Science ®Google Scholar
• Tscheikner-Gratl, F., Hammerer, M., Rauch, W., Mikovits, C., & Kleidorfer, M. (2013). Integrated Rehabilitation management for different infrastructure sectors, gwf-Wasser-Abwasser, Special (1/2013), 50–56. https://www.gwf-wasser.de/produkte/2013-integrated-rehabilitation-management-for-different-infrastructure-sectors-1/.
   Google Scholar
• Tscheikner-Gratl, F., Sitzenfrei, R., Rauch, W., & Kleidorfer, M. (2016a). Enhancement of limited water supply network data for deterioration modelling and determination of rehabilitation rate. Structure and Infrastructure Engineering, 12(3), 366–380. doi:10.1080/15732479.2015.1017730
   Web of Science ®Google Scholar
• Tscheikner-Gratl, F., Sitzenfrei, R., Rauch, W., & Kleidorfer, M. (2016b). Integrated rehabilitation planning of urban infrastructure systems using a street section priority model. Urban Water Journal, 13(1), 28–40. doi:10.1080/1573062X.2015.1057174
   Web of Science ®Google Scholar
• Tscheikner-Gratl, F., Sitzenfrei, R., Stibernitz, C., Rauch, W., & Kleidorfer, M. (2015). Integrated rehabilitation management by prioritization of rehabilitation areas for small and medium sized municipalities. World Environmental and Water Resources Congress 2015, 2045–2057. doi:10.1061/9780784479162.201
   Google Scholar
• Ugarelli, R. (2008). Asset management of wastewater networks (Doctoral dissertation). Bologna, Italy: Alma Mater Studiorum - Università di Bologna. http://amsdottorato.unibo.it/878/.
   Google Scholar
• Urich, C., & Rauch, W. (2014). Exploring critical pathways for urban water management to identify robust strategies under deep uncertainties. Water Research, 66, 374–389. doi:10.1016/j.watres.2014.08.020.
   PubMed Web of Science ®Google Scholar
• van den Boomen, M., Spaan, M. T. J., Shang, Y., & Wolfert, A. R. M. (2020). Infrastructure maintenance and replacement optimization under multiple uncertainties and managerial flexibility. Construction Management and Economics, 38(1), 91–107. doi:10.1080/01446193.2019.1674450
   Web of Science ®Google Scholar
• Van Dijk, D., & Hendrix, E. M. T. (2016). Pipe replacement in a water supply network: Coordinated versus uncoordinated replacement and budget effects. Informatica, 27(2), 387–403. doi:10.15388/Informatica.2016.91
   Web of Science ®Google Scholar
• van Riel, W., Langeveld, J., Herder, P., & Clemens, F. (2017). The influence of information quality on decision-making for networked infrastructure management. Structure and Infrastructure Engineering, 13(6), 696–708. doi:10.1080/15732479.2016.1187633
   Web of Science ®Google Scholar
• van Riel, W., Post, J., Langeveld, J., Herder, P., & Clemens, F. (2017). A gaming approach to networked infrastructure management. Structure and Infrastructure Engineering, 13(7), 855–868. doi:10.1080/15732479.2016.1212902
   Web of Science ®Google Scholar
• Walker, W. E., Harremoes, P., Rotmans, J., Van Der Sluijs, J. P., Van Asselt, M. B. A., Janssen, P., & Krayer Von Krauss, M. P. (2003). Defining uncertainty. Integrated Assessment, 4(1), 5–17. https://www.narcis.nl/publication/RecordID/oai:tudelft.nl:uuid:fdc0105c-e601-402a-8f16-ca97e9963592. doi:10.1076/iaij.4.1.5.16466
   Google Scholar
• Wei, L., Du, H., Mahesar, Q. a., Al Ammari, K., Magee, D. R., Clarke, B., … Cohn, A. G. (2020). A decision support system for urban infrastructure inter-asset management employing domain ontologies and qualitative uncertainty-based reasoning. Expert Systems with Applications, 158, 113461. doi:10.1016/j.eswa.2020.113461
   Web of Science ®Google Scholar
• Xu, Q., Qiang, Z., Chen, Q., Liu, K., & Cao, N. (2018). A superposed model for the pipe failure assessment of water distribution networks and uncertainty analysis: A case study. Water Resources Management, 32(5), 1713–1723. doi:10.1007/s11269-017-1899-8
   Web of Science ®Google Scholar
• Yang, Y., Ng, S. T., Xu, F. J., & Skitmore, M. (2018). Towards sustainable and resilient high density cities through better integration of infrastructure networks. Sustainable Cities and Society, 42, 407–422. doi:10.1016/j.scs.2018.07.013
   Web of Science ®Google Scholar
• Yilema, M. G., & Gianoli, A. (2018). Infrastructure governance: Causes for the poor sectoral coordination among infrastructure sectors of Addis Ababa. Cities, 83, 165–172. doi:10.1016/j.cities.2018.06.019
   Web of Science ®Google Scholar
• Young, O. R., Agrawal, A., King, L. A., & Sand, P. H. (1999). Institutional dimensions of global environmental change. Public Administration and Public Policy, 2(1999), 100.
   Google Scholar
• Yuan, X. (2017). Principles and guidelines of deterioration modelling for water and waste water assets. Infrastructure Asset Management, 4(1), 19–35. doi:10.1680/jinam.16.00017
   Web of Science ®Google Scholar
• Zhang, J., & Yuan, X. (2021). Stochastic modelling of maintenance flexibility in Value for Money assessment of PPP road projects stochastic modelling of maintenance flexibility in value for money. Construction Management and Economics, 39(2), 173–191. doi:10.1080/01446193.2020.1855666
   Web of Science ®Google Scholar
• Zuluaga, S., & Sánchez-silva, M. (2020). The value of flexibility and sequential decision-making in maintenance strategies of infrastructure systems. Structural Safety, 84, 101916. doi:10.1016/j.strusafe.2019.101916
   Web of Science ®Google Scholar