Dynamic Bayesian Networks to Assess Anthropogenic and Climatic Drivers of Saltwater Intrusion: A Decision Support Tool Toward Improved Management

Integrating climate model projections into environmental risk assessment: A probabilistic modeling approach

The Society of Environmental Toxicology and Chemistry (SETAC) convened a Pellston workshop in 2022 to examine how information on climate change could be better incorporated into the ecological risk assessment (ERA) process for chemicals as well as other environmental stressors. A major impetus for this workshop is that climate change can affect components of ecological risks in multiple direct and indirect ways, including the use patterns and environmental exposure pathways of chemical stressors such as pesticides, the toxicity of chemicals in receiving environments, and the vulnerability of species of concern related to habitat quality and use. This article explores a modeling approach for integrating climate model projections into the assessment of near- and long-term ecological risks, developed in collaboration with climate scientists. State-of-the-art global climate modeling and downscaling techniques may enable climate projections at scales appropriate for the study area. It is, however, also important to realize the limitations of individual global climate models and make use of climate model ensembles represented by statistical properties. Here, we present a probabilistic modeling approach aiming to combine projected climatic variables as well as the associated uncertainties from climate model ensembles in conjunction with ERA pathways. We draw upon three examples of ERA that utilized Bayesian networks for this purpose and that also represent methodological advancements for better prediction of future risks to ecosystems. We envision that the modeling approach developed from this international collaboration will contribute to better assessment and management of risks from chemical stressors in a changing climate. Integr Environ Assess Manag 2024;20:367-383. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Assessment of groundwater sustainable development considering geo-environment stability and ecological environment: a case study in the Pearl River Delta, China

Groundwater resources have an important impact on the geo-environment and ecological environment. The exploitation of groundwater resources may induce geo-environmental issues and has a negative impact on the ecological environment. The assessment of groundwater sustainable development can provide reasonable suggestions for the management of groundwater resources in coastal cities. In this study, an assessment method for groundwater sustainable development based on the resource supply function, geo-environment stability function, and ecological environment function was provided. Considering the groundwater quantity and quality; the vulnerability of karst collapse, land subsidence, and seawater intrusion; and the distribution of groundwater-dependent ecosystems (GDEs) and soil erosion, the groundwater in the Pearl River Delta was divided into concentrated groundwater supply area (21.97%) and decentralized groundwater supply area (48.22%), ecological protection area (20.77%), vulnerable geo-environment area (8.94%), and unsuitable to exploit groundwater area (0.10%). ROC curve and single-indicator sensitivity analysis were applied in the assessment of geo-environment vulnerability, and the results showed that the VW-AHP model effectively adjusted the weights of the indicators so that the assessment results were more in line with the actual situation in the Pearl River Delta, and the accuracy of the VW-AHP model was higher than that of the AHP model. This study provides a scientific basis for groundwater management in the Pearl River Delta and an example for the assessment of groundwater sustainable development in coastal cities.

Review of Seawater Intrusion in Western Coastal Regions of South Korea

Groundwater salinization in coastal aquifers because of seawater intrusion has raised serious concerns worldwide since it deteriorates the quality of drinking water and thereby threatens sustainable economic development. In particular, this problem has been a cause of growing concern in the western coastal regions of South Korea. In this paper, we review studies of seawater intrusion in western coastal regions of South Korea conducted over the past 20 years, particularly focusing on studies reported in international journals. We summarize the study locations, methods used, and major findings from individual and regional-scale studies. General methods used to identify and interpret seawater intrusion and subsequent geochemical processes are also presented. On the basis of insights gleaned from the previous studies, future research needs are discussed.

Increased Use of Bayesian Network Models Has Improved Environmental Risk Assessments

Environmental and ecological risk assessments are defined as the process for evaluating the likelihood that the environment may be impacted as a result of exposure to stressors. Although this definition implies the calculation of probabilities, risk assessments traditionally rely on nonprobabilistic methods such as calculation of a risk quotient. Bayesian network (BN) models are a tool for probabilistic and causal modeling, increasingly used in many fields of environmental science. Bayesian networks are defined as directed acyclic graphs where the causal relationships and the associated uncertainty are quantified in conditional probability tables. Bayesian networks inherently incorporate uncertainty and can integrate a variety of information types, including expert elicitation. During the last 2 decades, there has been a steady increase in reports on BN applications in environmental risk assessment and management. At recent annual meetings of the Society of Environmental Toxicology and Chemistry (SETAC) North America and SETAC Europe, a number of applications of BN models were presented along with new theoretical developments. Likewise, recent meetings of the European Geosciences Union (EGU) have dedicated sessions to Bayesian modeling in relation to water quality. This special series contains 10 articles based on presentations in these sessions, reflecting a range of BN applications to systems, ranging from cells and populations to watersheds and national scale. The articles report on recent progress in many topics, including climate and management scenarios, ecological and socioeconomic endpoints, machine learning, diagnostic inference, and model evaluation. They demonstrate that BNs can be adapted to established conceptual frameworks used to support environmental risk assessments, such as adverse outcome pathways and the relative risk model. The contributions from EGU demonstrate recent advancements in areas such as spatial (geographic information system [GIS]-based) and temporal (dynamic) BN modeling. In conclusion, this special series supports the prediction that increased use of Bayesian network models will improve environmental risk assessments. Integr Environ Assess Manag 2021;17:53-61. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).