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.

Procedural and behavioural biases have received little attention in recent Multi-Criteria Decision Analysis (MCDA) research. Our literature review shows that most research on biases was done 15–30 years ago. This study focuses on biases that are introduced at an early stage of MCDA when building objectives hierarchies and their effect on the weights. The main objective is to investigate whether prior findings regarding such biases, which were mostly based on laboratory experiments, can be found in real-world applications. We conducted a meta-analysis of the objectives hierarchies and weight elicitation procedures in 61 environmental and energy MCDA cases. Relationships between the structural characteristics of the objectives hierarchy and assigned objectives’ weights were analysed with statistical tests. Our main research questions were: (i) How does hierarchy size and structure affect the objectives’ weights? (ii) How are weights distributed across economic, social and environmental objectives? (iii) Is there support for the equalising bias? Our findings are mostly aligned with earlier research and suggest that the hierarchy structure and content can substantially influence weight distributions. For example, hierarchical weighting seems to be sensitive to the asymmetry bias, which can occur when a hierarchy has branches that differ in the number of sub-objectives. We found no evidence for the equalising bias. We highlight issues deserving more attention when developing objectives hierarchies and eliciting weights. The research demonstrates the potential to use meta-analysis, which has not previously been used in this way in the MCDA field, to learn from a collection of applications.

Structuring problems for Multi-Criteria Decision Analysis (MCDA) has attracted increasing attention over the past 20 years from both a conceptual and a practical perspective. This is reflected in a significant growth in the number of published applications which use a formal approach to problem structuring in combination with an analytic method for multi-criteria analysis. The problem structuring approaches (PSMs) include general methodologies such as Checkland's Soft Systems Method (SSM), Eden and Ackermann's Strategic Options Design and Analysis (SODA) and other methods that focus on a particular aspect. We carried out a literature review that covers eight PSMs (Cognitive and Causal Maps, DPSIR, Scenario Planning, SSM, Stakeholder Analysis, Strategic Choice Approach, SODA and SWOT) and seven MCDA methods (AHP, ANP, ELECTRE, MAUT, MAVT, PROMETHEE and TOPSIS). We first identified and analysed 333 articles published during 2000-2015, then selected 68 articles covering all PSM-MCDA combinations, which were studied in detail to understand the associated processes, benefits and challenges. The three PSMs most commonly combined with MCDA are SWOT, Scenario Planning and DPSIR. AHP was by far the most commonly applied MCDA method. Combining PSMs with MCDA produces a richer view of the decision situation and enables more effective support for different phases of the decision-making process. Some limitations and challenges in combining PSMs and MCDA are also identified, most importantly relating to building a value tree and assigning criteria weights.

River rehabilitation aims at alleviating negative effects of human impacts such as loss of biodiversity and reduction of ecosystem services. Such interventions entail difficult trade-offs between different ecological and often socio-economic objectives. Multi-Criteria Decision Analysis (MCDA) is a very suitable approach that helps assessing the current ecological state and prioritizing river rehabilitation measures in a standardized way, based on stakeholder or expert preferences. Applications of MCDA in river rehabilitation projects are often simplified, i.e. using a limited number of objectives and indicators, assuming linear value functions, aggregating individual indicator assessments additively, and/or assuming risk neutrality of experts. Here, we demonstrate an implementation of MCDA expert preference assessments to river rehabilitation and provide ample material for other applications. To test whether the above simplifications reflect common expert opinion, we carried out very detailed interviews with five river ecologists and a hydraulic engineer. We defined essential objectives and measurable quality indicators (attributes), elicited the experts´ preferences for objectives on a standardized scale (value functions) and their risk attitude, and identified suitable aggregation methods. The experts recommended an extensive objectives hierarchy including between 54 and 93 essential objectives and between 37 to 61 essential attributes. For 81% of these, they defined non-linear value functions and in 76% recommended multiplicative aggregation. The experts were risk averse or risk prone (but never risk neutral), depending on the current ecological state of the river, and the experts´ personal importance of objectives. We conclude that the four commonly applied simplifications clearly do not reflect the opinion of river rehabilitation experts. The optimal level of model complexity, however, remains highly case-study specific depending on data and resource availability, the context, and the complexity of the decision problem.

We used a multi-method and repeated elicitation approach across different stakeholder groups to explore possible differences in the outcome of an environmental decision. We compared different preference elicitation procedures based on Multi Criteria Decision Analysis (MCDA) over time for a water infrastructure decision in Switzerland. We implemented the SWING and SMART/SWING weight elicitation methods and also compared results with earlier stakeholder interviews. In all procedures, the weights for environmental protection and well-functioning (waste-)water systems were higher than for cost reduction. The SMART/SWING variant produced statistically significantly different weights than SWING. Weights changed over time with both elicitation methods. Weights were more stable with the SWING method, which was also perceived as slightly more difficult than the SMART/SWING variant. We checked whether the difference in weights produced by the two elicitation methods and the difference in their stability affects the ranking of six alternatives. Overall an unconventional decentralized alternative ranked first or second in 92 percent of all elicitation procedures, which were the online surveys or interviews. For practical decision-making, using multiple methods across different stakeholder groups and repeating elicitation can increase our confidence that the results reflect the true opinions of the decision makers and stakeholders.

Water supply and wastewater infrastructures are vital for human well-being and environmental protection; they adhere to the highest standards, are expensive and long-lived. Because they are also aging, substantial planning is required. Climate and socio-economic change create large planning uncertainties and simple projections of past developments are no longer adequate. This paper presents the initial phases of a structured decision-making (SDM) procedure which is designed to increase the sustainability of water infrastructure planning and includes various stakeholders in an exemplary Swiss case study. We evaluate the SDM approach critically based on stakeholder feedback, give general recommendations and provide ample material to make it applicable to other settings. We carried out 27 interviews and two stakeholder workshops. We identified important objectives for water infrastructure planning, including all three sustainability pillars and their respective attributes (indicators, benchmarks) to measure how well the objectives are achieved. We then created strategic decision alternatives, including "business-as-usual" upgrades of the central water supply and wastewater system as well as semi- to fully decentralized alternatives. To tackle future uncertainty, we developed four socio-demographic scenarios. We used these to test the robustness of decision alternatives in a later Multi-Attribute Utility Theory analysis. Additionally, we contribute to the topical discussion of combining scenario planning with multi-criteria decision analysis and demonstrate how various scenarios can stimulate creativity when generating decision alternatives. Their internal consistency is ensured by rigorously specifying them using a strategy generation table. Our SDM procedure can be adapted to inform decisions about sustainable water infrastructures in other contexts.

We present a novel approach for practically tackling uncertainty in preference elicitation and predictive modeling to support complex multi-criteria decisions based on multi-attribute utility theory (MAUT). A simplified two-step elicitation procedure consisting of an online survey and face-to-face interviews is followed by an extensive uncertainty analysis. 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 exemplified for sustainable water infrastructure planning in a case study in Switzerland. We compare 11 water supply alternatives ranging from conventional water supply systems to novel technologies and management schemes regarding 44 objectives. Their performance is assessed for four future scenarios and 10 stakeholders from different backgrounds and decision-making levels. Despite uncertainty in the ranking of alternatives, potential best and worst solutions could be identified. We 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. We suggest GSA to focus elicitation on most sensitive preference parameters. Our GSA results indicate that output uncertainty can be considerably reduced by additional elicitation of few parameters, e.g. the overall risk attitude and aggregation functions at higher-level nodes. Here, rough value function elicitation was sufficient, thereby substantially reducing elicitation time.

Environmental policy and decision-making are characterized by complex interactions between different actors and sectors. As a rule, a stakeholder analysis is performed to understand those involved, but it has been criticized for lacking quality and consistency. This lack is remedied here by a formal social network analysis that investigates collaborative and multi-level governance settings in a rigorous way. We examine the added value of combining both elements. Our case study examines infrastructure planning in the Swiss water sector. Water supply and wastewater infrastructures are planned far into the future, usually on the basis of projections of past boundary conditions. They affect many actors, including the population, and are expensive. In view of increasing future dynamics and climate change, a more participatory and long-term planning approach is required. Our specific aims are to investigate fragmentation in water infrastructure planning, to understand how actors from different decision levels and sectors are represented, and which interests they follow. We conducted 27 semi-structured interviews with local stakeholders, but also cantonal and national actors. The network analysis confirmed our hypothesis of strong fragmentation: we found little collaboration between the water supply and wastewater sector (confirming horizontal fragmentation), and few ties between local, cantonal, and national actors (confirming vertical fragmentation). Infrastructure planning is clearly dominated by engineers and local authorities. Little importance is placed on longer-term strategic objectives and integrated catchment planning, but this was perceived as more important in a second analysis going beyond typical questions of stakeholder analysis. We conclude that linking a stakeholder analysis, comprising rarely asked questions, with a rigorous social network analysis is very fruitful and generates complementary results. This combination gave us deeper insight into the socio-political-engineering world of water infrastructure planning that is of vital importance to our well-being.

Point-source measures have been suggested to decrease pharmaceuticals in water bodies. We analyzed 68 and 50 alternatives, respectively, for a typical Swiss general and psychiatric hospital to decrease pharmaceutical discharge. Technical alternatives included reverse osmosis, ozonation, and activated carbon; organizational alternatives included urine separation. To handle this complex decision, we used Multiple-Criteria Decision Analysis (MCDA) and combined expert predictions (e.g., costs, pharmaceutical mass flows, ecotoxicological risk, pathogen removal) with subjective preference-valuations from 26 stakeholders (authorities, hospital-internal actors, experts). The general hospital contributed ca. 38% to the total pharmaceutical load at the wastewater treatment plant, the psychiatry contributed 5%. For the general hospital, alternatives removing all pharmaceuticals (especially reverse osmosis, or vacuum-toilets and incineration), performed systematically better than the status quo or urine separation, despite higher costs. They now require closer scrutiny. To remove X-ray contrast agents, introducing roadbags is promising. For the psychiatry with a lower pharmaceutical load, costs were more critical. Stakeholder feedback concerning MCDA was very positive, especially because the results were robust across different stakeholder-types. Our MCDA results provide insight into an important water protection issue: implementing measures to decrease pharmaceuticals will likely meet acceptance. Hospital point-sources merit consideration if the trade-off between costs and pharmaceutical removal is reasonable.

Urine source separation (NoMix-technology) is a promising innovation aiming at a resource-oriented, decentralized approach in urban water management. However, NoMix-technology has a sensitive end-point: people’s bathrooms. NoMix-technology is increasingly applied in European pilot projects, but the success from a user point-of-view has rarely been systematically monitored. We aim at closing this gap. We review surveys on acceptance, including reuse of human urine as fertilizer, from 38 NoMix-projects in 7 Northern and Central European countries with 2700 respondents. Additionally, we identify explanatory variables with logistic regression of a representative Swiss library survey. NoMix-technology is well accepted; around 80% of users liked the idea, 75−85% were satisfied with design, hygiene, smell, and seating comfort of NoMix-toilets, 85% regarded urine-fertilizers as good idea (50% of farmers), and 70% would purchase such food. However, 60% of users encountered problems; NoMix-toilets need further development. We found few differences among countries, but systematic differences between public and private settings, where people seem more critical. Information was positively correlated with acceptance, and, e.g., a good mood or environmentally friendly behavior. For future success of NoMix-projects, we recommend authorities follow an integral strategy. Lay people will then find the NoMix-concept appealing and support this promising bathroom innovation.

We assessed the ecotoxicological hazard potential of 42 pharmaceuticals from 22 therapeutic groups, including metabolites formed in humans. We treated each parent drug and its metabolites as a mixture of similarly acting compounds. If physicochemical or effect literature data were missing, we estimated these with quantitative structure-activity relationships (QSAR). Additionally, we estimated micropollutant removal efficiency of urine source separation using pharmaceutical information. On average, 50% of a parent drug was metabolized, and 70% was excreted with urine, albeit with large variations among drugs. Metabolism reduced the toxic potential of all but eight drugs. The subsequently modeled risk quotient was mostly below the threshold of one. However, ibuprofen and its metabolites in a mixture could pose an ecotoxicologal risk; and possibly also acetylsalicylic acid, bezafibrate, carbamazepine, diclofenac, fenofibrate, and paracetamol. Lipophilicity and sale quantities of parent drugs alone were insufficient to estimate their ecotoxicological risk. Urine separation could decrease the ecotoxicological risk of some, but not all drugs. The estimated risk quotients were equal in urine and feces, again with large variations among compounds. Because of scientific limitations of the model and inconsistent literature data the results are somewhat uncertain. However, this new approach allows first tier screening of single drugs, thus supporting decision-making.