by Lisa Scholten, Judit Lienert, Max Maurer
Our centralized water supply systems are aging. Especially small utilities (altogether servicing more than half the Swiss population; SVGW, 2009) often lack the institutional, financial, and personnel means to anticipate the long-term performance of the system and to proactively plan their water supply systems into an uncertain future. The aim of this sub-project thus is the development of approaches for
- the prediction of the future condition of centralized pipe systems,
- strategic rehabilitation planning, and
- water infrastructure decision analysis that acknowledge uncertainties of predictions, future development, and stakeholder preferences.
Lifetime and failure prediction of water supply pipe networks
To assess the future condition of water supply networks, predictive pipe failure and pipe lifetime models are needed. The basis for these is the knowledge about expected pipe lifetimes and failure occurrence. In practice, failure and replacement data are often either absent or only cover short time windows, e.g. recording of the last few years. In addition, the amount of data available in small water networks does usually not suffice to robustly calibrate prediction models. This challenge is overcome in two ways:
- Development of prediction models which take into account the absence of failure and replacement data (i.e. left censoring, right truncation, selective survival)
- Combination of prior knowledge with locally available data to calibrate the models (Bayesian parameter inference).
The prior knowledge can be obtained from different sources. In this work, an approach to elicit pipe service life estimates from experts and its use for the calibration of pipe survival models was developed. This is presented in detail in Scholten et al. (2013a). Experts proved to be a useful source of knowledge which allowed to obtain differentiated estimates of the survival curves for different pipe groups (e.g. by material and vintage). The incorporation of in-between experts’ variance permitted to acknowledge different environmental and operational framework conditions, an important aspect in pipe survival modeling.
In another study, prior knowledge was obtained from recorded data of three mid-size to large water networks in Switzerland. This was combined with local data (by Bayesian parameter estimation) to calibrate a novel pipe failure model for a small water utility, see Scholten et al. (2013b). The model is presented in Scheidegger et al. (2013) where its ability to deal with the common data situation is also demonstrated. Similar modeling approaches were developed for sewerage Systems (Sub-project 2)
Strategic pipe rehabilitation planning
In light of pipe aging and high replacement values, pipe failure models are increasingly used to support water asset management decisions. Besides costs, different fundamental objectives play a role in these decisions. In this sub-project, the fundamental objectives of costs, reliability, and intergenerational equity were considered and traded against each other using multi-criteria decision analysis (MCDA) to define most desirable long-term rehabilitation strategies. This desirability depends on the long-term performance of a strategy and the preference of the decision maker(s) regarding these objectives.
Thereto, the failure model was combined with an existing strategic asset management software to model the outcomes of 18 rehabilitation strategies under four future scenarios for a small water utility. Model parameter uncertainty was propagated to the model outcomes and considered during evaluation. Different preferences were assumed to compare these alternatives. The analysis for a single case study utility revealed that, in this case, the common purely reactive rehabilitation strategy is not recommendable and that an annual replacement rate of 1–2% of the network by pipe condition could be a good long-term strategy. The ranking of alternatives differed the most under a development scenario with massive population and socio-economic growth (“Boom scenario”) as compared to the Status Quo or less extreme growth/ recession scenarios. For more details please see Scholten et al. (2013b).
Multi-criteria decision analysis under uncertainty – Good water supply infrastructure for the “Mönchaltorfer Aa”
To achieve a “good water supply infrastructure” in the long term, not only the technical pipe condition and pipe rehabilitation play a role. Together with stakeholders, 30 lower-level fundamental objectives for drinking water supply were identified by Lienert et al. (2014). These are quantified by 30 attributes. In addition, eleven water supply alternatives characterized by different organizational forms, geographical extent, management strategy, and technical configuration were developed and evaluated. Thereto, the outcomes of all alternatives regarding these attributes were predicted under four future scenarios to account for uncertainties about the future development. Based on a stakeholder and social network Analysis (, ten stakeholders were selected for individual MCDA interviews (Lienert et al., 2013). Their preferences were elicited and modeled using an approach which includes the imprecision of the stated preferences as well as uncertainties of preference parameters which were not elicited (the aggregation model, marginal value functions, risk attitude, and scaling factors). This finally resulted in obtaining probability distributions of the ranking of alternatives for each single stakeholder. Future dynamics and uncertainties could be incorporated by combining decision making and modeling with scenario planning, besides the quantitative consideration of uncertainties in making predictions, and evaluating the results. The results are currently prepared for publication. Sub-project 1)
Research on different preference elicitation formats is being conducted in another MCDA for identifying good wastewater infrastructures (sub-project 4)
References and more information
- Lienert, J., Schnetzer, F., Ingold, K. 2013. Stakeholder analysis combined with social network analysis provides fine-grained insights into water infrastructure planning processes. Journal of Environmental Management 125: 134–148. Postprint / Publisher's version
- Lienert, J., Scholten, L., Egger, C., Maurer, M. (2014) Structured decision making for sustainable water infrastructure planning and four future scenarios. EURO Journal on Decision Processes, special issue on Environmental Decision Making. Publisher's version
- SVGW, 2009. Statistische Erhebungen der Wasserversorgungen in der Schweiz Betriebsjahr 2008. Zürich, Schweizer Verein des Gas- und Wasserfaches. Link
- Scholten, L., Scheidegger, A., Reichert, P., Maurer, M., 2013a. Combining expert knowledge and local data for improved service life modeling of water supply networks. Environmental Modelling & Software 42 1-16. Postprint / Publisher's version
- Scholten, L., Scheidegger, A., Reichert, P., Maurer, M., Lienert, J., 2013b. Strategic rehabilitation planning of piped water networks using multi-criteria decision analysis. Water Research 49: 124-143. Postprint / Publisher's version
- Scheidegger, A., Scholten, L., Maurer, M., Reichert, P., 2013. Extension of pipe failure models to consider the absence of data from replaced pipes. Water Research 47(11) 3696-3705. Postprint / Publisher's version
- Scholten, L., Schuwirth. N., Reichert, P., Lienert, J. Tackling uncertainties in multi-criteria decision analysis - An application to water supply infrastructure planning. European Journal of Operational Research. In press. View at publisher | Postprint.