Environmental Risk Assessment of Wetland Ecosystems Using Bayesian Belief Networks
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. Diffe...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Hydrology |
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| Online Access: | https://www.mdpi.com/2306-5338/10/1/16 |
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| author | Bahram Malekmohammadi Cintia Bertacchi Uvo Negar Tayebzadeh Moghadam Roohollah Noori Soroush Abolfathi |
| author_facet | Bahram Malekmohammadi Cintia Bertacchi Uvo Negar Tayebzadeh Moghadam Roohollah Noori Soroush Abolfathi |
| author_sort | Bahram Malekmohammadi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T12:28:45Z |
| format | Article |
| id | doaj.art-77c80d1c7b4a4d048b42bbf72be68c2d |
| institution | Directory Open Access Journal |
| issn | 2306-5338 |
| language | English |
| last_indexed | 2024-03-09T12:28:45Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Hydrology |
| spelling | doaj.art-77c80d1c7b4a4d048b42bbf72be68c2d2023-11-30T22:31:32ZengMDPI AGHydrology2306-53382023-01-011011610.3390/hydrology10010016Environmental Risk Assessment of Wetland Ecosystems Using Bayesian Belief NetworksBahram Malekmohammadi0Cintia Bertacchi Uvo1Negar Tayebzadeh Moghadam2Roohollah Noori3Soroush Abolfathi4Graduate Faculty of Environment, University of Tehran, Tehran 1417853111, IranFinish Environment Institute, 00790 Helsinki, FinlandGraduate Faculty of Environment, University of Tehran, Tehran 1417853111, IranGraduate Faculty of Environment, University of Tehran, Tehran 1417853111, IranSchool of Engineering, University of Warwick, Coventry CV4 7AL, UKWetlands 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.https://www.mdpi.com/2306-5338/10/1/16Bayesian belief network (BBN)environmental riskrisk managementShadegan International Wetland (SIWs)wetlandsRamsar wetlands |
| spellingShingle | Bahram Malekmohammadi Cintia Bertacchi Uvo Negar Tayebzadeh Moghadam Roohollah Noori Soroush Abolfathi Environmental Risk Assessment of Wetland Ecosystems Using Bayesian Belief Networks Hydrology Bayesian belief network (BBN) environmental risk risk management Shadegan International Wetland (SIWs) wetlands Ramsar wetlands |
| title | Environmental Risk Assessment of Wetland Ecosystems Using Bayesian Belief Networks |
| title_full | Environmental Risk Assessment of Wetland Ecosystems Using Bayesian Belief Networks |
| title_fullStr | Environmental Risk Assessment of Wetland Ecosystems Using Bayesian Belief Networks |
| title_full_unstemmed | Environmental Risk Assessment of Wetland Ecosystems Using Bayesian Belief Networks |
| title_short | Environmental Risk Assessment of Wetland Ecosystems Using Bayesian Belief Networks |
| title_sort | environmental risk assessment of wetland ecosystems using bayesian belief networks |
| topic | Bayesian belief network (BBN) environmental risk risk management Shadegan International Wetland (SIWs) wetlands Ramsar wetlands |
| url | https://www.mdpi.com/2306-5338/10/1/16 |
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