We compare the use of multi-criteria decision analysis (MCDA)–or more precisely, models used in multi-attribute value theory (MAVT)–to integrated assessment (IA) models for supporting long-term water supply planning in a small town case study in Switzerland. They are used to evaluate thirteen system scale water supply alternatives in four future scenarios regarding forty-four objectives, covering technical, social, environmental, and economic aspects. The alternatives encompass both conventional and unconventional solutions and differ regarding technical, spatial and organizational characteristics. This paper focuses on the impact assessment and final evaluation step of the structured MCDA decision support process. We analyze the performance of the alternatives for ten stakeholders. We demonstrate the implications of model assumptions by comparing two IA and three MAVT evaluation model layouts of different complexity. For this comparison, we focus on the validity (ranking stability), desirability (value), and distinguishability (value range) of the alternatives given the five model layouts. These layouts exclude or include stakeholder preferences and uncertainties. Even though all five led us to identify the same best alternatives, they did not produce identical rankings. We found that the MAVT-type models provide higher distinguishability and a more robust basis for discussion than the IA-type models. The needed complexity of the model, however, should be determined based on the intended use of the model within the decision support process. The best-performing alternatives had consistently strong performance for all stakeholders and future scenarios, whereas the current water supply system was outperformed in all evaluation layouts. The best-performing alternatives comprise proactive pipe rehabilitation, adapted firefighting provisions, and decentralized water storage and/or treatment. We present recommendations for possible ways of improving water supply planning in the case study and beyond.@en

A new approach for tackling uncertainties in preference elicitation and predictive modeling of complex MCDA/MAUT problems and its application to water infrastructure planning in Switzerland will be presented. To this end, a two-step procedure for preference elicitation is combined with uncertainty and global sensitivity analyses (UA, GSA). This covers uncertainty of the preference components (marginal value and utility functions, hierarchical aggregation functions, aggregation parameters) and the attribute predictions. Context uncertainties about future socio-economic developments are captured by combining MAUT with scenario planning. We perform a global sensitivity analysis (GSA) to assess the contribution of single uncertain preference parameters to the uncertainty of the ranking of alternatives. This is done taking into account the implications of five different GSA designs regarding the choice of the feasible sample space. We will show the usefulness of UA and GSA to explore the importance and contribution of often ignored uncertainties and to focus on those crucial for discriminating alternatives. Based on these results, we will furthermore demonstrate that a priori assumptions such as linear value functions or additive aggregation can result in misleading recommendations, unless thoroughly checked during preference elicitation and modeling. This work has been recently published (Scholten et al. 2015). We now strive to adapt this work such that GSA can be used to inform the decision analysis process about the most sensitive parameters before detailed preference assessment and attribute prediction is undertaken. We will present an outlook on work in progress and some challenges faced in further developing the framework. This framework will be beneficial for water infrastructure planning and other complex planning situations, as it allows to identify which components of the overall MCDA it is worth to focus efforts on, and under which conditions. Reference: Scholten, L., Reichert, P., Schuwirth, N., Lienert, J., 2015. Tackling uncertainty in multi-criteria decision analysis- An application to water supply infrastructure planning. European Journal of Operational Research 242(1) 243-260. @en

To overcome the difficulties of strategic asset management of water distribution networks, a pipe failure and a rehabilitation model are combined to predict the long-term performance of rehabilitation strategies. Bayesian parameter estimation is performed to calibrate the failure and replacement model based on a prior distribution inferred from three large water utilities in Switzerland. Multi-criteria decision analysis (MCDA) and scenario planning build the framework for evaluating 18 strategic rehabilitation alternatives under future uncertainty. Outcomes for three fundamental objectives (low costs, high reliability, and high intergenerational equity) are assessed. Exploitation of stochastic dominance concepts helps to identify twelve non-dominated alternatives and local sensitivity analysis of stakeholder preferences is used to rank them under four scenarios. Strategies with annual replacement of 1.5-2% of the network perform reasonably well under all scenarios. In contrast, the commonly used reactive replacement is not recommendable unless cost is the only relevant objective. Exemplified for a small Swiss water utility, this approach can readily be adapted to support strategic asset management for any utility size and based on objectives and preferences that matter to the respective decision makers.

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