Inputs zur gesellschaftlichen Entscheidungsfindung

Switzerland plans to restore 4000 km of rivers by 2090. Despite the immense investment costs, river restoration benefits have not been valued in monetary terms, and a cost-benefit analysis (CBA) does not exist for any river restoration project in Switzerland. We apply stated preference methods to elicit public preferences and willingness to pay for restoring two specific but representative river sites. The benefits of restoration are compared with its costs. Upscaling the results to the national level shows that the government budget allocated for river restoration (CHF 1200/m) is insufficient to cover the costs of local restoration projects. However, the surveyed local populations are willing to pay substantially more for restoring rivers in their area of residence than they are legally obliged to do. The CBA results demonstrate that the benefits outweigh the costs in the two case studies, and hence that restoration efforts are justified from an economic point of view. A sensitivity analysis shows that the main results and conclusions do not change when we change some of the key assumptions underlying the CBA.

Environmental monitoring covers many different management domains. They range from biodiversity conservationto water protection, natural hazard prevention, impact assessment, resource use, or environmentalrestoration. The need for clear objectives has long been emphasized in the management literature, but has oftenreceived only little attention in monitoring design. This is partly due to the lack of systematic approaches forsetting objectives. In this paper, we present a formal approach based on Multi-Criteria Decision Analysis(MCDA), namely relevancy analysis, to prioritize management objectives. We demonstrate its use for a riverrestoration monitoring program in Switzerland comprising 35 physical and biological objectives. The relevancyof an objective is based on two main components, the general importance of the objective, and the problemspecificimpact range. The general importance of an objective is used to identify the most important managementobjectives from a hierarchy within the national program (i.e. objectives to be monitored). The impact range isused to understand which management objectives are more important to monitor for different river restorationmeasures (i.e. sub-selection of the objectives specifically for the restoration measure). The general importance ofa management objective was determined based on the frequency an objective is mentioned in selected policydocuments, and the legislative power and temporal persistency of each document. The impact ranges wereidentified from a questionnaire involving 15 Swiss river restoration professionals. Hereby, we assumed that theimpact range increases as the anticipated impact of the restoration measure on a specific management objectiveincreases, and as the uncertainty to anticipate this impact increases. For simplicity, we applied the approach onlyto one restoration measure, namely river widening. Six management objectives scored high in relevancy in termsof both impact range and general importance – channel structure and diversity, structure and diversity of thebanks and floodplains, sediment dynamics, longitudinal connectivity, lateral connectivity, and vertical connectivity.Hence, these objectives are both important national objectives for river monitoring (according to thelegislation) and are objectives that are potentially highly impacted by a river widening project. We performedsensitivity analyses related to the calculation of the general importance, the impact range, and the relevancy ofthe objectives. The practice-oriented approach can be transferred to a broad diversity of decision situationswhere there is a need for systematic evaluation of the importance of objectives. It could be a useful tool for sociallearning and finding group consensus about the priority of the objectives.

Transitioning economic sectors towards more sustainable futures is a major global challenge, in particular for non-OECD countries. Policymakers in these countries are confronted with a double challenge: how to implement cleaner technologies and infrastructures while at the same time promoting rapid industrial development. In catch-up studies, this trade-off has been increasingly interpreted as providing windows of opportunity for gaining strong leadership in new generations of cleantech industries. In this paper, we maintain that in order to specify how these windows of opportunity can be endogenized, a deeper understanding is needed about whether, how and by whom the directionality of innovation systems can be influenced. For this purpose, we propose an analytical approach that draws on the technological innovation system framework extending the current understanding of directionality in two ways: first, we complement the prevalent top-down perspective with a bottom-up view exemplified by the institutional entrepreneurship literature. Second, we posit that the focus has to be shifted from the manufacturing of single technologies to the transformation of entire socio-technical systems. The presented framework is validated by a case study on recent shifts in the dominant technology in China's urban water management sector. Major changes in the country's sectoral selection environment led membrane bioreactor technology to become the dominant design in urban water management - a development that is unmatched in any other country in the world. Owing to these transformations, China's technology firms outcompete multinational players and therefore they show strong potentials for industrial leapfrogging. However, although the promise to solve environmental problems played a decisive role in the shaping of the selection environment, it remains unclear whether the observed transformation leads the way to a more sustainable sector structure in the longer run. The case, however, still enables us to specify how windows of opportunity can be endogenized through the interplay of different actors trying to shape different layers of the selection environment in a specific sector.

Theories of policymaking often focus on subsystems within a larger, overarching governance system. However, subsystem identification is complicated by the complexity of governance systems, characterized by multiple, interrelated issues, multi‐level interactions, and a diverse set of organizations. This study suggests an empirical, bottom‐up methodology to identify subsystems. Subsystems are identified based on bundles of similar observed organizational activity. The study further suggests a set of three elementary criteria to classify individual subsystems. In order to prove the value of the methodology, subsystems are identified through cluster analysis, and subsequently classified in a study of Swiss water governance. Results suggest that Swiss water governance can be understood as a network of overlapping subsystems connected by boundary penetrating organizations, with high‐conflict and quiet politics subgroups. The study shows that a principled analysis of subsystems as the interconnected, constituent parts of complex governance systems offers insights into important contextual factors shaping outcomes. Such insights are prerequisite knowledge in order to understand and navigate complex systems for researchers and practitioners alike.

In densely populated areas, surface waters are affected by many sources of pollution. Besides classical pollutants like nutrients and organic matter that lead to eutrophication, micropollutants from various point- and non-point sources are getting more attention by water quality managers. For cost-effective management an integrated assessment is needed that takes into account all relevant pollutants and all sources of pollution within a catchment. Due to the difficulty of identifying and quantifying sources of pollution and the need for considering long-term changes in boundary conditions, typically substantial uncertainty exists about the consequences of potential management alternatives to improve surface water quality. We therefore need integrated assessment methods that are able to deal with multiple objectives and account for various sources of uncertainty.
This paper aims to contribute to integrated, prospective water management by combining a) multi-criteria decision support methods to structure the decision process and quantify preferences, b) integrated water quality modelling to predict consequences of management alternatives accounting for uncertainty, and c) scenario planning to consider uncertainty from potential future climate and socio-economic developments, to evaluate the future cost-effectiveness of water quality management alternatives at the catchment scale. It aims to demonstrate the usefulness of multi-attribute value functions for water quality assessment to i) propagate uncertainties throughout the entire assessment procedure, ii) facilitate the aggregation of multiple objectives while avoiding discretization errors when using categories for sub-objectives, iii) transparently communicate the results. We show how to use such multi-attribute value functions for model-based decision support in water quality management.
We showcase the procedure for the Mönchaltorfer Aa catchment on the Swiss Plateau. We evaluate ten different water quality management alternatives, including current practice, that tackle macro- and micropollutants from a wide spectrum of agricultural and urban sources. We evaluate costs and water quality effects of the alternatives under four different socio-economic scenarios for the horizon 2050 under present and future climate projections and visualize their uncertainty. While the performance of alternatives is catchment specific, the methods can be transferred to other places and other management situations. Results confirm the need for cross-sectoral coordination of different management actions and interdisciplinary collaboration to support the development of prospective strategies to improve water quality.