Department Urban Water Management

Sustainable Water Infrastructure Planning (SWIP)

Goal is an improved planning procedure for sustainable water supply and wastewater infrastructure management that links into the existing Swiss governance structures. A special focus is given to dealing with limited data, the uncertainty of future developments, and ensuring high acceptance of the decision-making process by stakeholders.

SWIP is based on three main pillars: (i) Quantitatively considering the goals of the involved stakeholders by the means of Multi-Criteria Decision analysis (MCDA); (ii) extrapolating the consequence of rehabilitation strategies into the future by providing novel deterioration models for sewer and water distribution networks, and (iii) explicitly including all known uncertainties, including climate change and socio economic development, into the results.

The approach was tested in one case study and showed some surprising results. The overall methodology is sound, but needs more practical experience and tweaking to be rolled out on a large scale.

Background

Water infrastructures such as water supply pipes, sewers, and treatment plants are vital to our society. They provide us with water for various purposes at all times. They also ensure the hygienically safe and environmentally friendly disposal of wastewater, and they protect us from floodings. However, with lifetimes of 100 and more years, water infrastructures are very long-lived. They are expensive and in many industrialized countries the ageing water infrastructures need to be repaired or replaced in the next years.

Infrastructure planning is complex. Usually, the past activities are projected into the future, without systematic integration of the previous experience or changed future conditions, and without active participation of different actors. Existing planning tools are unsuitable to deal with an increasingly dynamic and uncertain future. Effects of climate change such as water scarcity and heavy rainfall, as well as the demographic and socio-economic development are uncertain, but strongly affect the services expected from water infrastructures. In Switzerland, the water sector is highly fragmented, which additionally causes organizational deficits.

Current Swiss planning procedures (mainly GEP, Generelle Entwässerungsplanung  and GWP, Generelle Wasserversorgungsplanung) do not consider the future systematically. Due to socio-economic and climate change and the large uncertainty about the status of the current infrastructure, this gap needs to be bridged with new tools and methodologies.

Aim

Main goal of SWIP is an improved procedure for water supply and wastewater infrastructure planning. It explicitly considers sustainability aspects, by balancing economy (predicting costs of decisions), with ecology (ecosystem effects), and social aspects (integrating stakeholder values). Special attention is given to the fact that many (small) communities have only limited data concerning their infrastructures and that future developments cannot be predicted with certainty.

SWIP complements existing governance tools such as GEP and GWP. The SWIP-approach can be adapted to a variety of real-world decision situations with many stakeholders involved.

The project combined engineering with decision sciences in four sub-projects (Link). Tools and methods to improve the long-term planning process for water infrastructures were developed. These instruments support changing from the current problem-based repairs to a proactive and long-term maintenance and rehabilitation concept. The approach was developed with active participation of local actors in a case study region near Zürich (Greifensee), being very typical for Switzerland and consisting of several smaller communities.

SWIP is characterized by a consistent transdisciplinary approach. The experience, knowledge, and preferences of important stakeholders were integrated during different phases of the scientific research. A new framework based on Multi-Criteria Decision analysis (MCDA) allows to synthesize all available information and data – quantitative and qualitative – and to structure the participation of stakeholders throughout the planning process.

Another important characteristic of SWIP is the explicit consideration of uncertainty in all sub-projects. This includes adequate dealing with small data sets and missing information, the uncertainty of models that predict the performance and deterioration of infrastructures, the uncertainty about the future climate or socio-economic development, as well as the uncertainty about the preferences of stakeholders.

 

Sub-projects

Sub-Project 1 - Stakeholder and social network analysis

by Judit Lienert, with Florian Schnetzer and Karin Ingold 

Aim

Primary aim of this sub-project was to characterize the stakeholders that are directly involved in the planning of the water supply and wastewater infrastructures, as well as those that are connected to these processes. Additional aim was to find out how well these actors are integrated into decision making, and which interests they follow. We also aimed at testing several hypotheses, namely that there is a strong fragmentation between different sectors and decision levels in the water sector.

Methods

We combined a classical stakeholder analysis with a social network analysis. Stakeholder analysis is a rather qualitative, but very popular approach, which helps to identify actors with high influence as well as those with less power, but who might be affected by decisions. We carried out 27 semi-structured face to face interviews, which allowed characterizing these stakeholders in some detail, along with their role in the water sector and the interests that they follow.

In the second part of the stakeholder analysis we included open questions for a more holistic assessment of the stakeholder’s perceptions of current water infrastructure planning. Hereby, we asked the interview partners to identify elements of “ideal planning processes”, barriers to the current system, and drivers used to overcome the perceived deficiencies.

The social network analysis is a more-quantitative approach, which allowed us to identify the relationships and ties between different actors and how well these actors are integrated into the planning processes.

Main results

A very high number of stakeholders – namely 66 – were mentioned to play a role in water infrastructure planning. The hypothesis of strong fragmentation in the water sector was clearly confirmed. It is generally known that there is little collaboration between the water supply and wastewater sector – in Switzerland as well as in other countries. However, to our knowledge this has not been demonstrated in such a systematic way as in our social network analysis. On the other hand, it was possible to identify some actors that interact with many others and are able to connect between different sectors. They are thus very central to the network of stakeholders and have a highly influential role as intermediaries.


There is also only little collaboration between actors of different decisional levels. Local engineers and community authorities have a very important role in current water infrastructure planning, while many other stakeholders have little influence on planning processes. Not surprisingly, many of the actors have strong interests in economic revenue, the water infrastructure technology itself, and in receiving the services related to the technology, water supply and wastewater infrastructures.

Many of the interview partners clearly perceived the shortcomings of the current system. They were well aware that main actors follow shorter-term interests, while longer-term strategic objectives such as regionalization and integrated catchment planning are difficult to pursue under the existing planning procedures. Many also mentioned that the water sector urgently requires better collaboration to overcome the drawbacks of fragmentation and to increase efficiency. They pointed out, that integrated catchment planning is needed to address longer-term sustainability challenges. They also criticized that current water infrastructure planning is too closely coupled with local politics, again increasing the difficulty of addressing longer-term strategic and sustainability objectives.

The methodological approach of combining the open questions of the stakeholder analysis with the closed format of the social network analysis was highly effective, helping to better understand the social system of water infrastructure planning.

Based on the results of the case study, we can clearly conclude that it is no longer adequate to delegate water infrastructure planning to engineers alone. We must think about new solutions to meet the upcoming future challenges. This can only be achieved by a more profound discussion about sustainability goals in the water sector. We need to find out which regulations and governance forms are best suited to achieve these goals. In collaboration with practitioners, we need to link our research and political discussions with implementation in the real world.

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

Sub-project 2 - Dissertation by Christoph Egger:
Determining the performance and condition of future wastewater systems

by Christoph Egger and Max Maurer

Predictions of the structural condition of urban drainage networks enables us to estimate future investment costs under various rehabilitation strategies. This facilitates proactive, far-sighted sewer asset management, which, in turn, contributes to a better balance between expenses and system performance. The latter is related to, among other things, the system’s ability to drain large quantities of stormwater under extreme precipitation with as little damage as possible. The design of system adaptions must therefore incorporate additional information on potential future urban land use as well as the changing precipitation regime.

Deterioration modelling of urban drainage networks

Successful calibration of sewer deterioration models is often hindered by the following factors,:

  • Limited information content of the data, as in case of small sample sizes
  • If sewer pipes have been renovated, repaired or replaced by new ones corresponding condition ratings prior the rehabilitation measure are often overwritten or discarded. In this case the remaining data distort the observed deterioration process. 

Detailed information on methods to overcome these issues can be found under the following link. See also (Egger et al., 2013).

http://apollo.emp-eaw.ch:9999/forschung/sww/gruppen/swip/eng_wastewater/2nd_revision_open_source_egger

Uncertainties as a result of climate change and variability

Hydraulic sewer system design under conditions of an changing climate is challenging due to the following reasons:

  • Some climate projections suggest that the probability of heavy precipitation events will increase. However, the spacial and temporal resolution of these projections are too coarse to be directly used as input data for sewer system design.
  • The currently used rain data series are too short and therefore not representative enough.

Current design practice relies on historical precipitation data. Even though observation periods cover usually several decades these data are not representative with respect to precipitation extremes. Stochastic models for rainfall simulation and disaggregation are appropriate tools to overcome these issues which enables us to take account of uncertainties resulting from climate change and variability. Further information on this can be found here. An investigation is currently underway that highlights the significance of these uncertainties – also with regard to additional investment costs for the deliberate incorporation of safety precautions into the systems.

Outlook


The methods described above are currently being applied to concrete cases under a variety of socio-economic scenarios. Thereby, we investigate the following issues:

  • The predicted future investment costs depend strongly on the size and quality of the available condition data. Low data availability increases the significance of the prior knowledge and increase uncertainty. In these cases great care is needed to identify adequate prior information. This also highlights the importance of keeping historic data.
  • How significant are the individual factors (i) the need for system adaptions in order to assure their serviceability in the future, (ii) sewer deterioration and (iii) urban development with regard to future investment needs? And in considering these, what are the uncertainties do we have to deal with?

Further information

  • Aqua Urbanica
  • Egger, C., Scheidegger, A., Reichert, P. and Maurer, M., 2013. Sewer deterioration modeling with condition data lacking historical records. Water Research 47 (17), 6762-6779. Postprint Publisher's Version

Sub-project 3 - Dissertation by Lisa Scholten:
Multi-criteria decision analysis for water supply infrastructure planning under uncertainty

 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

  1. the prediction of the future condition of centralized pipe systems,
  2. strategic rehabilitation planning, and
  3. 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:

  1. Development of prediction models which take into account the absence of failure and replacement data (i.e. left censoring, right truncation, selective survival)
  2. 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.

Sub-project 4 - Postdoctorate by Jun Zheng:
Incorporating stakeholders’ preferences into wastewater infrastructure planning with multi-criteria decision Analysis(MCDA)

by Jun Zheng, Judit Lienert

The importance of incorporating stakeholders in public and environmental decisions is increasingly recognized. Involving stakeholders allows them to see the broader picture of the decision problem and move beyond single-interest concerns, which ultimately helps to reduce potential conflicts. The transparency of the process enhances the acceptance of the final recommendation, thus resulting in more willingness to implement it.

With help of the stakeholder and social network analysis (Sub-project1, Lienert et al., 2013), ten stakeholders were identified, who are influential on wastewater infrastructure planning or who might be affected by the decision. These stakeholders were deeply involved in the whole decision analysis process, from the initial problem structuring phase to the final recommendation. The focus of this sub-project is to quantify the stakeholders’ preferences which are to be integrated in a Multi-Attribute Utility model by its preferential parameters.

 

Aim

The aim of this sub-project was to elicit each stakeholder’s preferences in a quantitative way. A preference elicitation process consists of a sequence of questions and answers in which stakeholders progressively express their preferences. Preference elicitation is a rather challenging task of MCDA. There are various reasons for these difficulties:

  1. The decision problem is relevant to the stakeholders, but they do not necessarily have adequate knowledge to understand the objectives and attributes. In some cases, especially the attributes (= indicators, performance measures) are inevitably technical. Often, stakeholders may only have expertise concerning a specific field (e.g. cost of wastewater infrastructure or management aspects), but do not know much about other topics (e.g. removal of micropollutants in wastewater).
  2. The trade-offs themselves can be very difficult, as they may invoke moral, inner conflicts. Trade-offs have to be made if not all objectives can be reached at the same time. For instance, it may not be possible to remove all micropollutants from wastewater and to achieve the lowest-possible costs as well. In the preference elicitation process, decision makers are explicitly asked to make such difficult trade-offs.
  3. Quantifying the preferences is per se not easy. Many people find it difficult to clearly express their preferences, especially if they have not been able to think about them thoroughly so far. If the preferences are not clear to a person, they are constructed during the elicitation process, in a numeric way.
  4. We aimed at designing a structured elicitation procedure which enables the stakeholders to express their preferences with as much support as possible (Figure 1). At the same time we aimed at applying a methodologically correct and meaningful procedure from an MCDA point of view. We are also interested in the potential influence of different elicitation methods on the elicitation process.

 

Methods

Generally speaking, there are two paradigms of elicitation methods (Figure 2). Direct elicitation approaches directly ask the stakeholders for the preferential parameters so that a (mathematical) preference model can be constructed. On the other hand, indirect elicitation approaches deduce an aggregation model from a subset of alternatives, or in the language of artificial intelligence, to learn a preference model on the basis of a learning set.

The two different elicitation methods may trigger different activities in people’s mind, and ultimately reveal various aspects of preference information. We employed both approaches to elicit preferences from the same stakeholders, in order to test their possible influences on the elicitation results. We were also interested in investigating the stability of the stakeholders’ preferences.

 

Direct elicitation of preferential parameters was implemented by an online questionnaire and face-to-face interviews. The weights of objectives and attributes, the value functions, risk attitude, and aggregation methods were elicited from individual stakeholders. Uncertainties were dealt with by explicitly allowing stakeholders to answer the questions with a range rather than a precise number, or by requesting them to state an uncertainty level. We were also concerned about the common biases known from the literature, such as the “splitting bias” and “goal-directed bias”, and developed corresponding remedies to avoid them as much as possible.

The indirect elicitation approach was also realized by face-to-face interviews. The questions asked comprised pairwise comparisons of some hypothetical alternatives, the strength of preferences, and trade-off questions. Imprecise preference models are inferred from all this information by solving linear program problems.

In both methods, the stakeholders were encouraged to “think aloud” in the interviews, i.e. they were asked to explain the rationale when they made judgments. Furthermore, when changes of answers were detected between the interviews, a discussion followed to understand whether the change was caused by the different elicitation method, or by a real change of preferences.

Main results

As the project is still ongoing there are no final results yet.

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 Decison Making: in press.
  • Zheng, J., Egger, C., Lienert, J. (2014a) Multi-criteria decision analysis for wastewater infrastructure planning incorporating stakeholders’ preferences (working title, in preparation).
  • Zheng, J., Lienert, J. (2014b) Stakeholder preference elicitation and modeling for wastewater infrastructure planning: a comparative evaluation of two elicitation methods (working title, in preparation).

More information

Media (TV, Radio, Newspaper)

  • Maurer, M. (2014) Radio interview: Im Untergrund drohen Wasserlecks (in German) (There is a threat of underground water leakages). Radio SRF 2 Wissenschaftsmagazin, Anita Vonmont, 22.02.2014, 12.40. Switzerland.
  • Maurer, M., Lienert, J. (2014) Im Untergrund drohen Wasserlecks (in German) (There is a threat of underground water leakages). Technik – Wissen, Schweizer Radio und Fernsehen, Online-Artikel Anita Vonmong, 24.02.2014. Switzerland.

Products and literature