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Multi-criteria decision analysis in Bayesian networks - diagnosing ecosystem service trade-offs in a hydropower regulated river

Abstract

The paper demonstrates the use of Bayesian networks in multicriteria decision analysis (MCDA) of environmental design alternatives for environmental flows (eflows) and physical habitat remediation measures in the Mandalselva River in Norway. We demonstrate how MCDA using multi-attribute value functions can be implemented in a Bayesian network with decision and utility nodes. An object-oriented Bayesian network is used to integrate impacts computed in quantitative sub-models of hydropower revenues and Atlantic salmon smolt production and qualitative judgement models of mesohabitat fishability and riverscape aesthetics. We show how conditional probability tables are useful for modelling uncertainty in value scaling functions, and variance in criteria weights due to different stakeholder preferences. While the paper demonstrates the technical feasibility of MCDA in a BN, we also discuss the challenges
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Category

Academic article

Language

English

Author(s)

  • David Nicholas Barton
  • Håkon Sundt
  • Ana Adeva Bustos
  • Hans-Petter Fjeldstad
  • Richard David Hedger
  • Torbjørn Forseth
  • Berit Köhler
  • Øystein Aas
  • Knut Alfredsen
  • Anders L. Madsen

Affiliation

  • SINTEF Energy Research / Energisystemer
  • Denmark
  • Aalborg University
  • Norwegian University of Science and Technology
  • Norwegian Institute for Nature Research

Year

2019

Published in

Environmental Modelling & Software

ISSN

1364-8152

Volume

124

View this publication at Norwegian Research Information Repository