Bayesian network integration of nutrient loading and lake eutrophication models in cost-effectiveness analysis of abatement measures

One of the major problems of water quality in Norway is eutrophication, which tends to occur in low-lying areas, particularly near urban areas and agricultural land. Due to the gravity of the situation, authorities and the local population demand effectiv e countermeasures, which in turn require a comprehensive analysis of the particular situation and an assessment of potential abatement measures. The EutroBayes project aims to contribute to enhancing the quality of these assessments, specifically in the t wo case study river basins, Vansjø-Hobøl and Steinsfjorden, having documented and topical eutrophication problems. Uncertainty analysis forms the basis for risk analysis that often precedes decision-making, e.g. between the alternative nutrient abatemen t measures. The main aim of the EutroBayes project is to carry out such holistic uncertainty assessment for the case study river basins by (1) applying models of nutrient (phosphorus) abatement costs and effects, as well as models of lake P and eutrophica tion dynamics, and by (2) integrating these models and their results by using probabilistic Bayesian network techniques. Bayesian network methodology provides a powerful, intuitively and visually appealing tool for combining (uncertain) information from d ifferent sources into a common framework and for analysing this particular system's functioning and characteristics. The EutroBayes project will deliver a fully functioning Bayesian network integrated model for exploring the probable (and improbable) out comes and uncertainties of (i) the eutrophication problem and (ii) the cost-effectiveness analysis of the corresponding abatement measures in Vansjø-Hobøl and Steinsfjorden river basins. In addition the project outcome includes scientific publications as well as a list of the key uncertainties and gaps in our knowledge, that play a major role in the eutrophication problem and the cost-effectiveness evaluation of the possible abatement measures.