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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.

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