This example is taken from (Barton et al, 2008).
A Bayesian network approach is used to conduct decision analysis of nutrient abatement measures in the Morsa catchment, South Eastern Norway. The paper demonstrates the use of Bayesian networks as a meta-modelling tool in integrated river basin management (IRBM) for structuring and combining the probabilistic information available in existing costeffectiveness studies, eutrophication models and data, non-market valuation studies and expert opinion. The Bayesian belief network is used to evaluate eutrophication mitigation costs relative to benefits, as part of the economic analysis under the EU Water Framework Directive (WFD). Pros and cons of Bayesian networks as reported in the literature are reviewed in light of the results from our Morsa catchment model. The reported advantages of Bayesian networks in promoting integrated, inter-disciplinary evaluation of uncertainty in IRBM, as well as the apparent advantages for risk communication with stakeholders, are offset in our case by the cost of obtaining reliable probabilistic data and meta-model validation procedures.
Cost individal ww
Total cost vegetation zone(kr/yr)
Total ploughing cost (kr./yr)
D.N. Barton, T. Saloranta, S.J. Moe, H.O. Eggestad, S. Kuikka, Bayesian belief networks as a meta-modelling tool in integrated river basin management - Pros and cons in evaluating nutrient abatement decisions under uncertainty in a Norwegian river basin, Ecological Economics, Volume 66, Issue 1, 15 May 2008, Pages 91-104, ISSN 0921-8009, dx.doi.org/10.1016/j.ecolecon.2008.02.012.
David N. Barton, Norwegian Institute for Nature Research. david.barton_at_nina.no