Development of a multi-criteria decision-support tool for improving water quality to assist with engineering infrastructure and catchment management

Abstract

Research combining water quality modelling, quantitative chemical/microbial risk assessment, and stakeholder engagement to prioritise catchment areas facing water pollution problems to devise effective pollution mitigation strategies are limited. This research therefore aimed to address this gap by providing a practical and comprehensive framework that supports wellinformed decision-making processes in water pollution alleviation. By integrating multiple criteria and catchment aspects, this framework can assist infrastructure, operational, and ecological managers within a catchment in prioritising best management practices (BMPs) to reduce pollution and mitigate against potential resultant impacts. Given this context, uMsunduzi catchment, in KwaZulu-Natal, South Africa was chosen as a study site. UMsunduzi River is a major tributary of uMngeni River that is used for water supply to the cities of Pietermaritzburg and Durban. The study begins with the data synthesis from diverse sources of scientific data to identify chemical and microbial hazards, utilising a water quality modelling tool to map point and nonpoint source pollution in the catchment. The assessment encompasses the presence of pathogens such as Cryptosporidium and Escherichia coli (E. coli) in the catchment, with rural areas showing a greater contribution from animal sources, while urban areas are affected by impaired wastewater infrastructure. Quantitative microbial risk assessment (QMRA) was conducted, assuming no water treatment within the catchment. The investigation considered multiple exposure routes, including domestic drinking and recreational activities for both adults and children. The results indicate that the probability of infection from Cryptosporidium and E. coli exceeds acceptable levels set by South African water quality guidelines and the World Health Organization. The assessment further included a chemical risk assessment on various chemical groups, including organochlorinated pesticides (OCPs), pharmaceuticals and personal care products (PPCPs), heavy metals, nitrates, and phosphates. Elevated carcinogenic risks were observed for most OCPs, while noncarcinogenic pesticide effects pose long-term risks. Heavy metals and PPCPs are within sub-risk levels, but phosphates have notable ecological and health impacts, particularly in Inanda Dam, a key source of potable water for Durban. In this study, a unique contribution is made by incorporating both chemical and microbial risk assessment. Furthermore, the risk assessment methodology not only encompasses various chemical pollutants and exposure pathways but addresses the nuanced issue of water consumption variability between children and adults. To address these identified risks, a multi-criteria decision analysis methodology is employed to engage stakeholders in the risk management process. Affected, involved, and interested stakeholders, along with economic, environmental, and social criteria, contribute to the selection of Best Management Practices (BMPs). The Simple Multi-Attribute Rating Technique for Enhanced Stakeholder Take-up (SMARTEST) is utilised to identify suitable interventions. The study culminates in the recommendation of BMPs that aim to change behaviour, including public education on livestock grazing management, safe medication disposal, and responsible fertilizer and pesticide use. Pollution management measures, such as solid waste control and river cleanup, are suggested, along with infrastructure management improvements, like sewer system maintenance. This research strived to bridge the gap in water pollution alleviation by presenting a practical and comprehensive framework designed to support well-informed decision-making processes. This framework, with its integration of multiple criteria and considerations, stands poised to aid infrastructure, operational, and ecological managers within a catchment in prioritising BMPs aimed at reducing pollution and mitigating resultant health impacts.