Water pollution presents a substantial environmental challenge with extensive implications for water resources, ecosystem sustainability, and human health. Using a South African catchment, this study aimed to provide watershed managers with a framework for selecting best management practices (BMPs) to reduce pollution and the related risk to river users, while also including the perspectives of key catchment stakeholders. The framework encompassed the identification of and consultation with key stakeholders within the catchment. A Multi-Criteria Decision Analysis (MCDA) methodology using the Simple Multi-Attribute Rating Technique for Enhanced Stakeholder Take-up (SMARTEST) was used to identify and prioritise suitable BMPs in a case study. Decision alternatives and assessment criteria as well as their weights were derived based on stakeholder responses to a two-stage survey. Stakeholders included those utilising the river for domestic and recreational purposes, municipal representatives, scientists, NGOs, and engineers. The assessment of decision alternatives considered environmental, economic, and social criteria. The aggregated scores for decision alternatives highlighted the significance of involving stakeholders throughout the decision process. This study recommends the pairing of structural and non-structural BMPs. The findings provide valuable insights for catchment managers, policymakers, and environmental stakeholders seeking inclusive and effective pollution mitigation strategies in a catchment.

South African rivers generally receive waste from inadequate wastewater infrastructure, mines, and farming activities, among others. The uMsunduzi River in KwaZulu-Natal, South Africa, is among these recipients with recorded poor to very poor water quality. To identify parts of the uMsunduzi River that are polluted by Cryptosporidium and Escherichia coli (E. coli), this study mapped out pollutants emanating from point and non-point sources using the Soil and Water Assessment Tool (SWAT). Streamflow calibration in the upper and lower reaches of the catchment showed good performance with R2 of 0.64 and 0.58, respectively. SWAT water quality output data were combined with a Quantitative Microbial Risk Assessment (QMRA) to understand the microbial health implications for people using river water for drinking, recreational swimming, and non-competitive canoeing. QMRA results for Cryptosporidium and pathogenic E. coli showed that the probability of infection for most users exceeds the acceptable level for drinking and recreation as outlined in the South African water quality guidelines, and by the World Health Organization (WHO). The results of this study can be used as a baseline to assess the economic and health implications of different management plans, resulting in better-informed, cost-effective, and impactful decision-making.

Reliable and safe drinking water supply requires adequate risk management. Decision support models can aid decisionmakers to effectively evaluate risk mitigation measures and allocate societal resources. Here, a Swedish case study illustrates how the installation of ultrafiltration membranes can be evaluated by combining risk assessment and cost-benefit analysis. Quantitative microbial risk assessment was used to assess several contamination sources and estimate the achieved risk reduction from waterborne pathogens using Campylobacter, Norovirus, and Cryptosporidium as reference pathogens. The societal value of the improved water quality was estimated in the cost-benefit analysis by monetising the gained quality adjusted life years and aesthetic water quality improvements. The calculated net present value (mean of 7 MEUR) indicated that the installation of the ultrafiltration membranes was a sound investment from a societal economic perspective. The ultrafiltration membranes reduced the annual probability of infection from 3 × 10⁻² to 10⁻⁷, well below the U.S. EPA’s acceptable level, as well as improving the aesthetic quality of the drinking water. The results provide a novel example of the importance for water distributors to consider not only health-related metrics when evaluating treatment options or monitoring the drinking water quality, but to also consider the aesthetic quality of the drinking water.

Unexpected risk events in drinking water systems, such as heavy rain or manure spill accidents, can cause waterborne outbreaks of gastrointestinal disease. Using a scenario-based approach, these unexpected risk events were included in a risk-based decision model aimed at evaluating risk reduction alternatives. The decision model combined quantitative microbial risk assessment and cost–benefit analysis and investigated four risk reduction alternatives. Two drinking water systems were compared using the same set of risk reduction alternatives to illustrate the effect of unexpected risk events. The first drinking water system had a high pathogen base load and a high pathogen log₁₀ reduction in the treatment plant, whereas the second drinking water system had a low pathogen base load and a low pathogen Log₁₀ reduction in the treatment plant. Four risk reduction alternatives were evaluated on their social profitability: (A1) installation of pumps and back-up power supply, to remove combined sewer overflows; (A2) installation of UV treatment in the drinking water treatment plant; (A3) connection of 25% of the OWTSs in the catchment area to the WWTP; and (A4) a combination of A1–A3. Including the unexpected risk events changed the probability of a positive net present value for the analysed alternatives in the decision model and the alternative that is likely to have the highest net present value. The magnitude of the effect of unexpected risk events is dependent on the local preconditions in the drinking water system. For the first drinking water system, the unexpected risk events increase risk to a lesser extent compared to the second drinking water system. The main conclusion was that it is important to include unexpected risk events in decision models for evaluating microbial risk reduction, especially in a drinking water system with a low base load and a low pathogen log₁₀ reduction in the drinking water treatment plant.