ArticleScientific reports2024
Multi-criteria decision analysis framework for engaging stakeholders in river pollution risk management.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Integrating machine learning and multi-criteria decision analysis for health risk management in water distribution networks.Scientific reports · 2026Article
- Industrial Assessment Tools of Risks Associated with Wastewater and Water Technologies.ACS ES&T water · 2025Article
- A Comprehensive Dataset of Surface Water Quality Spanning 1940-2023 for Empirical and ML Adopted Research.Scientific data · 2025Article
- Distance and similarity measures on belief and plausibility under q-rung orthopair fuzzy sets with applications.Scientific reports · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.