Bayesian Network Applications for Sustainable Holistic Water Resources Management: Modeling Opportunities for South Africa

Abstract

Anthropogenic transformation of land globally is threatening water resources in terms of quality and availability. Managing water resources to ensure sustainable utilization is important for a semiarid country such as South Africa. Bayesian networks (BNs) are probabilistic graphical models that have been applied globally to a range of water resources management studies; however, there has been very limited application of BNs to similar studies in South Africa. This article explores the benefits and challenges of BN application in the context of water resources management, specifically in relation to South Africa. A brief overview describes BNs, followed by details of some of the possible opportunities for BNs to benefit water resources management. These include the ability to use quantitative and qualitative information, data, and expert knowledge. BN models can be integrated into geographic information systems and predict impact of ecosystem services and sustainability indicators. With additional data and information, BNs can be updated, allowing for integration into an adaptive management process. Challenges in the application of BNs include oversimplification of complex systems, constraints of BNs with categorical nodes for continuous variables, unclear use of expert knowledge, and treatment of uncertainty. BNs have tremendous potential to guide decision making by providing a holistic approach to water resources management.

Multi-Scenario Simulation to Predict Ecological Risk Posed by Urban Sprawl with Spontaneous Growth: A Case Study of Quanzhou

“…Ecological risk research focuses on analyzing the probability that threats outside the ecosystem will lead to irreversible damage to the structure and function of the ecosystem [ 1 , 2 , 3 ]. At the lower level, ecological risk assessments have focused more on the adverse effects of a single physical or chemical stress on an individual organism or a small group of representative species [ 4 , 5 ].…”

Water quality prediction based on Naïve Bayes algorithm

“…(Kragt 2009;Chen & Pollino 2012). BNs are also widely used in the field of water management (Drury et al 2017;Phan et al 2019;Guzmán-Fierro 2020;Govender et al 2021).…”

Bayesian networks for risk analysis and decision support

“…IBRAM has helped to evaluate the efficacy of pathway management to mitigate the risk of these pests' establishment in the country. Govender et al (2021) offer a perspective paper on the potential of applying BNs for sustainable and holistic management of water resources in South Africa. The authors undertake a literature review and discuss the benefits and challenges of BNs in the context of future sustainable water resources management.They conclude that BNs have significant potential to guide decision making to achieve a sustainable balance between the use and protection of resources.…”

“…Finally, there is significant opportunity to explore the use of BNs across more fields, disciplines, and application areas. Undertaking more reviews such as the one presented by Govender et al (2021) would be very useful in pushing the disciplinary uses and potential contributions of BNs.…”

“…Undertaking more reviews such as the one presented by Govender et al. (2021) would be very useful in pushing the disciplinary uses and potential contributions of BNs.…”