Exploratory use of a Bayesian network process for translating stakeholder perceptions of water quality problems in a catchment in South Africa

Abstract

Water resource management is complex, and should ideally be a co-operative, stakeholder-driven problem-solving process. Bayesian networks (BNs) are one participatory tool being increasingly used to facilitate this process. The upper Mgeni catchment in the province of KwaZulu-Natal, South Africa, is a key water resource area with looming water quality problems. The high number of stakeholders involved in a catchment management forum provided an environment for testing the development of a BN showing relationships between water quality problems and stakeholders in this area. Through engagement with stakeholders at quarterly meetings during 2011, and collation and analysis of water quality time-series, qualitative and quantitative data were successfully translated into a BN for water quality improvement in the study area. The model demonstrated that certain water quality variables (for example, compliance of wastewater treatment works; increase in housing developments) were more likely to be the cause of problems than others (such as discharges from farm dams or accidental spills). The value of involving stakeholders in a co-operative process is highlighted, and it is argued that the robustness of such a model would be enhanced further if applied within a formal participatory approach using conditional probability values endorsed by all stakeholders.

Applications of Bayesian Networks as Decision Support Tools for Water Resource Management under Climate Change and Socio-Economic Stressors: A Critical Appraisal

“…The ability of BNs to combine these different types of data is particularly useful for informing decisions under high levels of uncertainty, where the state of a variable or decision outcome is uncertain. This is because BNs are well suited to facilitate stakeholder involvement to identify potential intervention options and incorporate stakeholder expertise to assess the likely consequences of each option even where detailed quantitative data on outcomes is incomplete [1].…”

“…Optimization-based approaches were encountered much less frequently, only appearing in 18% of the reviewed applications. Only seven (e.g., [1,45,106]) of these optimization-based studies actually incorporated decision nodes, cost node(s) and utility node(s) into their BNs to optimize selection of water-related management options. Other studies (e.g., [17,18]) coupled BNs with external economic valuations to optimize the selection of water management measures.…”

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

“…Stakeholders are essential for water management, especially in determining the values placed on water resources to achieve the balance between sustainable use and protection of this vital resource. It is critical that community stakeholders are adequately equipped with the knowledge to play a meaningful role in managing water resources (Rivers‐Moore, 2016 ). A clear understanding of the intentions behind management objectives should be made explicit from the onset of community engagement in any process.…”

“…3 (Chen & Pollino, 2012 ). Rivers‐Moore ( 2016 ) highlighted the value of using BNs as a participatory tool to engage stakeholders in seeking solutions to complex environmental management problems. However, we must be mindful of the significant impact of language.…”