Malekmohammadi, Bahram, Uvo, Cintia Bertacchi, Moghadam, Negar Tayebzadeh, Noori, Roohollah and Abolfathi, Soroush (2023) Environmental risk assessment of wetland ecosystems using Bayesian belief networks. Hydrology, 10 (1). 16. doi:10.3390/hydrology10010016 ISSN 2306-5338.

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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 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.

Item Type:	Journal Article
Subjects:	G Geography. Anthropology. Recreation > GB Physical geography G Geography. Anthropology. Recreation > GE Environmental Sciences Q Science > QH Natural history T Technology > TA Engineering (General). Civil engineering (General) T Technology > TC Hydraulic engineering. Ocean engineering T Technology > TD Environmental technology. Sanitary engineering
Divisions:	Faculty of Science, Engineering and Medicine > Engineering > Engineering
Library of Congress Subject Headings (LCSH):	Bayesian statistical decision theory, Environmental risk assessment, Wetlands, Ecosystem health
Journal or Publication Title:	Hydrology
Publisher:	MDPI Publishing
ISSN:	2306-5338
Official Date:	7 January 2023
Dates:	Date Event 7 January 2023 Published 4 January 2023 Accepted
Volume:	10
Number:	1
Article Number:	16
DOI:	10.3390/hydrology10010016
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access (Creative Commons)
Date of first compliant deposit:	9 January 2023
Date of first compliant Open Access:	9 January 2023
Related URLs:	Publisher

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