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Application of Bayesian networks for sustainability assessment in catchment modeling and management (Case study: The Hablehrood river catchment)

•We assess water quality problems in a semi-arid catchment in Iran using Bayesian networks.•Modeling will help to integrate catchment management and scenario analysis to improve water quality.•Modeling will show how, in a dryland ecosystem, riparian vegetation has the greatest influence on water qua...

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Bibliographic Details
Published in:Ecological modelling 2013-10, Vol.268, p.48-54
Main Authors: Keshtkar, A.R., Salajegheh, A., Sadoddin, A., Allan, M.G.
Format: Article
Language:English
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Summary:•We assess water quality problems in a semi-arid catchment in Iran using Bayesian networks.•Modeling will help to integrate catchment management and scenario analysis to improve water quality.•Modeling will show how, in a dryland ecosystem, riparian vegetation has the greatest influence on water quality improvement. Catchment management is a process which increases the sustainable development and management of all catchment resources in order to maximize the balance among socioeconomic welfare and the sustainability of vital ecosystems. The increase of anthropogenic activities within river catchments causes degradation and serious problems for stakeholders and managers, particularly in arid and semi-arid regions. Although there are many techniques for solving these problems, it is not easy for catchment managers to apply them. An integrated Bayesian network model framework was applied to evaluate the sustainability of a semi-arid river catchment located in the Iranian Central Plateau river basin encompassing 32.6km2 area on the Hablehrood river catchment, located in the northern part of the Iranian Central Plateau river basin. The research illustrated the assessment of the relevant management problems, the model framework, and the techniques applied to extract input data. Results for the study area implementation and a suggestion for management are described and discussed.
ISSN:0304-3800
1872-7026
DOI:10.1016/j.ecolmodel.2013.08.003