Eutropia: Integrated Valuation of Lake Eutrophication Abatement Decisions Using a Bayesian Belief Network

• Main Authors: Barton, David N, Andersen, Tom, Bergland, Olvar, Engebretsen, Alexander, Moe, S. Jannicke, Orderud, Geir I, Tominaga, Koji, Romstad, Eirik, Vogt, Rolf D
• Format: Book
• Language: English

The term “integrated valuation” is defined and its relevance is discussed in terms of bridging the gap between cost-effectiveness analysis and economic valuation in the implementation of the European Union Water Framework Directive. We demonstrate how to integrate benefit valuation with the ecosystem services cascade framework using an Object-Oriented Bayesian Network (OOBN). The OOBN is then used to assess the benefits of nutrient abatement measures across a cascade of submodels of the driver-pressure-state-impact-response (DPSIR) chain for the Vanemfjord lake in Morsa catchment in south-eastern Norway. The lake is part of a complex lake system in a semi-urbanized catchment dominated by forest and agriculture. The catchment has highly variable seasonal climatic conditions affecting nutrient run-off and algal blooms. It has been one of the most eutrophic lakes in Norway with periodic cyanobacteria blooms, but continues to attract a large recreational user population, despite the large variations in water quality. The “DPSIR-OOBN” model is used as a case study of “integrated valuation” and evaluated for its applicability for decision support in nutrient abatement. We find that the DPSIR-OOBN model meets seven of the nine criteria we propose for “integrated valuation”. The model struggles to meet the criteria that ecological, social and economic values should be defined consistently in relation to impacts on lake quality. While the DPSIR-OOBN integrates from valuation methods across an ecosystem cascade to management alternatives, it is neither a full benefit-cost analysis, nor a multi-criteria analysis. However, we demonstrate how the DPSIR-OOBN can be used to explore issues of consistency in scaling and weighting of different ecological, social and economic values in the catchment system. Bayesian belief networks offer a consistent approach to analysing how management implementation probability may determine economic valuation. We discuss the implication of our integrated valuation not being able to account for farmer responses, in particular the incentive effects of the model not being able to predict abatement effectiveness and value. The resolution of the nutrient monitoring data and modeling technologies that were at our disposal are probably better in the Morsa catchment than for any other catchment of this size in Norway. We therefore conclude that using our integrated valuation model for assessing benefits of eutrophication abatement measures as par