A decision analysis framework for stakeholder involvement and learning in groundwater management
- 1Thule Institute, University of Oulu, P.O. Box 7300, University of Oulu, 90014 Oulu, Finland
- 2University of Oulu, Department of Process and Environmental Engineering, Water Resources and Environmental Engineering Laboratory, P.O. Box 4300, University of Oulu, 90014 Oulu, Finland
- 3Pöyry Finland Oy, Tutkijantie 2A–D, 90590 Oulu, Finland
- 4Research Institute of Water and Environmental Engineering, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
- 5Department of Systems Analysis, Integrated Assessment and Modeling, Swiss Federal Institute for Aquatic Science and Technology, Ueberlandstrasse, 133, 8600 Duebendorf, Switzerland
- 6Department of Environmental Science, University of Basel, Petersplatz 1, 4003, Basel, Switzerland
Abstract. Multi-criteria decision analysis (MCDA) methods are increasingly used to facilitate both rigorous analysis and stakeholder involvement in natural and water resource planning. Decision-making in that context is often complex and multi-faceted with numerous trade-offs between social, environmental and economic impacts. However, practical applications of decision-support methods are often too technically oriented and hard to use, understand or interpret for all participants. The learning of participants in these processes is seldom examined, even though successful deliberation depends on learning. This paper analyzes the potential of an interactive MCDA framework, the decision analysis interview (DAI) approach, for facilitating stakeholder involvement and learning in groundwater management. It evaluates the results of the MCDA process in assessing land-use management alternatives in a Finnish esker aquifer area where conflicting land uses affect the groundwater body and dependent ecosystems. In the assessment process, emphasis was placed on the interactive role of the MCDA tool in facilitating stakeholder participation and learning. The results confirmed that the structured decision analysis framework can foster learning and collaboration in a process where disputes and diverse interests are represented. Computer-aided interviews helped the participants to see how their preferences affected the desirability and ranking of alternatives. During the process, the participants' knowledge and preferences evolved as they assessed their initial knowledge with the help of fresh scientific information. The decision analysis process led to the opening of a dialogue, showing the overall picture of the problem context and the critical issues for the further process.