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

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 functi...

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Published in:Environmental Modelling & Software
Main Authors: Barton, David Nicholas, Sundt, Håkon, Adeva Bustos, Ana, Fjeldstad, Hans-Petter, Hedger, Richard David, Forseth, Torbjørn, Köhler, Berit, Aas, Øystein, Alfredsen, Knut, Madsen, Anders L.
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2019
Subjects:
Online Access:http://hdl.handle.net/11250/2634689
https://doi.org/10.1016/j.envsoft.2019.104604
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spelling ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/2634689 2023-05-15T15:32:14+02:00 Multi-criteria decision analysis in Bayesian networks - diagnosing ecosystem service trade-offs in a hydropower regulated river Barton, David Nicholas Sundt, Håkon Adeva Bustos, Ana Fjeldstad, Hans-Petter Hedger, Richard David Forseth, Torbjørn Köhler, Berit Aas, Øystein Alfredsen, Knut Madsen, Anders L. 2019 http://hdl.handle.net/11250/2634689 https://doi.org/10.1016/j.envsoft.2019.104604 eng eng Elsevier Norges forskningsråd: 215934 Environmental Modelling & Software. 2020,124 . urn:issn:1364-8152 http://hdl.handle.net/11250/2634689 https://doi.org/10.1016/j.envsoft.2019.104604 cristin:1760716 Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no CC-BY 12 124 Environmental Modelling & Software Journal article Peer reviewed 2019 ftntnutrondheimi https://doi.org/10.1016/j.envsoft.2019.104604 2020-01-08T23:32:26Z 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 publishedVersion This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Article in Journal/Newspaper Atlantic salmon NTNU Open Archive (Norwegian University of Science and Technology) Norway Environmental Modelling & Software 124 104604
institution Open Polar
collection NTNU Open Archive (Norwegian University of Science and Technology)
op_collection_id ftntnutrondheimi
language English
description 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 publishedVersion This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
format Article in Journal/Newspaper
author Barton, David Nicholas
Sundt, Håkon
Adeva Bustos, Ana
Fjeldstad, Hans-Petter
Hedger, Richard David
Forseth, Torbjørn
Köhler, Berit
Aas, Øystein
Alfredsen, Knut
Madsen, Anders L.
spellingShingle Barton, David Nicholas
Sundt, Håkon
Adeva Bustos, Ana
Fjeldstad, Hans-Petter
Hedger, Richard David
Forseth, Torbjørn
Köhler, Berit
Aas, Øystein
Alfredsen, Knut
Madsen, Anders L.
Multi-criteria decision analysis in Bayesian networks - diagnosing ecosystem service trade-offs in a hydropower regulated river
author_facet Barton, David Nicholas
Sundt, Håkon
Adeva Bustos, Ana
Fjeldstad, Hans-Petter
Hedger, Richard David
Forseth, Torbjørn
Köhler, Berit
Aas, Øystein
Alfredsen, Knut
Madsen, Anders L.
author_sort Barton, David Nicholas
title Multi-criteria decision analysis in Bayesian networks - diagnosing ecosystem service trade-offs in a hydropower regulated river
title_short Multi-criteria decision analysis in Bayesian networks - diagnosing ecosystem service trade-offs in a hydropower regulated river
title_full Multi-criteria decision analysis in Bayesian networks - diagnosing ecosystem service trade-offs in a hydropower regulated river
title_fullStr Multi-criteria decision analysis in Bayesian networks - diagnosing ecosystem service trade-offs in a hydropower regulated river
title_full_unstemmed Multi-criteria decision analysis in Bayesian networks - diagnosing ecosystem service trade-offs in a hydropower regulated river
title_sort multi-criteria decision analysis in bayesian networks - diagnosing ecosystem service trade-offs in a hydropower regulated river
publisher Elsevier
publishDate 2019
url http://hdl.handle.net/11250/2634689
https://doi.org/10.1016/j.envsoft.2019.104604
geographic Norway
geographic_facet Norway
genre Atlantic salmon
genre_facet Atlantic salmon
op_source 12
124
Environmental Modelling & Software
op_relation Norges forskningsråd: 215934
Environmental Modelling & Software. 2020,124 .
urn:issn:1364-8152
http://hdl.handle.net/11250/2634689
https://doi.org/10.1016/j.envsoft.2019.104604
cristin:1760716
op_rights Navngivelse 4.0 Internasjonal
http://creativecommons.org/licenses/by/4.0/deed.no
op_rightsnorm CC-BY
op_doi https://doi.org/10.1016/j.envsoft.2019.104604
container_title Environmental Modelling & Software
container_volume 124
container_start_page 104604
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