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.

This study investigates how land use and climate changes affect water yield ecosystem service (ES) in the Sirvan River basin, located in Iran’s Kurdistan and Kermanshah provinces. By detecting land-use and climatic parameter changes in the past, their future evolution were modeled by scenario making. For this purpose, we developed two land-use scenarios (low and high urbanization) and two climatic scenarios (Representative Concentration Pathway 2.6 and RCP 8.5). The implemented scenarios showed how the amount of water yield in the basin and sub-basins changes in the future based on climate and land-use changes. The results showed that, concerning land use, the forest has decreased from 2013 to 2019, and built-up areas have increased. Also, the results showed that precipitation has been declining in the long term, and the temperature has been rising. Finally, the Water yield in 2019 was higher than in 2013 and lower in the future based on forecast scenarios. This trend will continue until 2040. In addition, it was found that the t effects of these factors on water yield ES are a complex process, and based on the results, the impact of climatic factors is more significant than the one of land-use change. We could conclude that this region will face more environmental problems in the future.