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Environmental Risk Assessment of Wetland Ecosystems Using Bayesian Belief Networks

Malekmohammadi, Bahram LU ; Uvo, Cintia Bertacchi LU orcid ; Moghadam, Negar Tayebzadeh ; Noori, Roohollah LU and Abolfathi, Soroush (2023) In Hydrology 10(1).
Abstract

Wetlands are valuable natural capital and sensitive ecosystems facing significant risks from anthropogenic and climatic stressors. An assessment of the environmental risk levels for wetlands’ dynamic ecosystems can provide a better understanding of their current ecosystem health and functions. Different levels of environmental risk are defined by considering the categories of risk and the probability and severity of each in the environment. Determining environmental risk levels provides a general overview of ecosystem function. This mechanism increases the visibility of risk levels and their values in three distinct states (i.e., low, moderate, and high) associated with ecosystem function. The Bayesian belief network (BBN) is a novel... (More)

Wetlands are valuable natural capital and sensitive ecosystems facing significant risks from anthropogenic and climatic stressors. An assessment of the environmental risk levels for wetlands’ dynamic ecosystems can provide a better understanding of their current ecosystem health and functions. Different levels of environmental risk are defined by considering the categories of risk and the probability and severity of each in the environment. Determining environmental risk levels provides a general overview of ecosystem function. This mechanism increases the visibility of risk levels and their values in three distinct states (i.e., low, moderate, and high) associated with ecosystem function. The Bayesian belief network (BBN) is a novel tool for determining environmental risk levels and monitoring the effectiveness of environmental planning and management measures in reducing the levels of risk. This study develops a robust methodological framework for determining the overall level of risks based on a combination of varied environmental risk factors using the BBN model. The proposed model is adopted for a case study of Shadegan International Wetlands (SIWs), which consist of a series of Ramsar wetlands in the southwest of Iran with international ecological significance. A comprehensive list of parameters and variables contributing to the environmental risk for the wetlands and their relationships were identified through a review of literature and expert judgment to develop an influence diagram. The BBN model is adopted for the case study location by determining the states of variables in the network and filling the probability distribution tables. The environmental risk levels for the SIWs are determined based on the results obtained at the output node of the BBN. A sensitivity analysis is performed for the BBN model. We proposed model-informed management strategies for wetland risk control. According to the BBN model results, the SIWs ecosystems are under threat from a high level of environmental risk. Prolonged drought has been identified as the primary contributor to the SIWs’ environmental risk levels.

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Please use this url to cite or link to this publication:
author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Bayesian belief network (BBN), ecosystem function, ecosystem health, environmental risk, Ramsar wetlands, risk management, Shadegan International Wetland (SIWs), wetlands
in
Hydrology
volume
10
issue
1
article number
16
publisher
MDPI AG
external identifiers
  • scopus:85146736752
ISSN
2306-5338
DOI
10.3390/hydrology10010016
language
English
LU publication?
yes
additional info
Funding Information: The first author would like to express his gratitude to the Islamic Development Bank (IDB) for providing a fellowship through the Merit Scholarship Program, which facilitated research visit and collaboration with Lund University. CBU would like to acknowledge partial funding by the Academy of Finland under the HYDRO-RI and GreenDigiBasin projects that are part of the Freshwater Competence Centre. Publisher Copyright: © 2023 by the authors.
id
3fc9a0ec-4cd4-4a9b-a8fb-b8c5229ea89b
date added to LUP
2023-02-06 14:23:01
date last changed
2023-10-05 08:41:49
@article{3fc9a0ec-4cd4-4a9b-a8fb-b8c5229ea89b,
  abstract     = {{<p>Wetlands are valuable natural capital and sensitive ecosystems facing significant risks from anthropogenic and climatic stressors. An assessment of the environmental risk levels for wetlands’ dynamic ecosystems can provide a better understanding of their current ecosystem health and functions. Different levels of environmental risk are defined by considering the categories of risk and the probability and severity of each in the environment. Determining environmental risk levels provides a general overview of ecosystem function. This mechanism increases the visibility of risk levels and their values in three distinct states (i.e., low, moderate, and high) associated with ecosystem function. The Bayesian belief network (BBN) is a novel tool for determining environmental risk levels and monitoring the effectiveness of environmental planning and management measures in reducing the levels of risk. This study develops a robust methodological framework for determining the overall level of risks based on a combination of varied environmental risk factors using the BBN model. The proposed model is adopted for a case study of Shadegan International Wetlands (SIWs), which consist of a series of Ramsar wetlands in the southwest of Iran with international ecological significance. A comprehensive list of parameters and variables contributing to the environmental risk for the wetlands and their relationships were identified through a review of literature and expert judgment to develop an influence diagram. The BBN model is adopted for the case study location by determining the states of variables in the network and filling the probability distribution tables. The environmental risk levels for the SIWs are determined based on the results obtained at the output node of the BBN. A sensitivity analysis is performed for the BBN model. We proposed model-informed management strategies for wetland risk control. According to the BBN model results, the SIWs ecosystems are under threat from a high level of environmental risk. Prolonged drought has been identified as the primary contributor to the SIWs’ environmental risk levels.</p>}},
  author       = {{Malekmohammadi, Bahram and Uvo, Cintia Bertacchi and Moghadam, Negar Tayebzadeh and Noori, Roohollah and Abolfathi, Soroush}},
  issn         = {{2306-5338}},
  keywords     = {{Bayesian belief network (BBN); ecosystem function; ecosystem health; environmental risk; Ramsar wetlands; risk management; Shadegan International Wetland (SIWs); wetlands}},
  language     = {{eng}},
  number       = {{1}},
  publisher    = {{MDPI AG}},
  series       = {{Hydrology}},
  title        = {{Environmental Risk Assessment of Wetland Ecosystems Using Bayesian Belief Networks}},
  url          = {{http://dx.doi.org/10.3390/hydrology10010016}},
  doi          = {{10.3390/hydrology10010016}},
  volume       = {{10}},
  year         = {{2023}},
}