Water quality modelling and quantitative microbial risk assessment for uMsunduzi River in South Africa
dc.contributor.author | Ngubane, Zesizwe | en_US |
dc.contributor.author | Bergion, Viktor | en_US |
dc.contributor.author | Dzwairo, Bloodless | en_US |
dc.contributor.author | Troell, Karin | en_US |
dc.contributor.author | Amoah, Isaac Dennis | en_US |
dc.contributor.author | Stenstrom, Thor Axel | en_US |
dc.contributor.author | Sokolova, Ekaterina | en_US |
dc.date.accessioned | 2022-05-16T13:09:14Z | |
dc.date.available | 2022-05-16T13:09:14Z | |
dc.date.issued | 2022-04 | |
dc.date.updated | 2022-05-12T13:55:08Z | |
dc.description.abstract | 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 R<sup>2</sup> 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. | en_US |
dc.format.extent | 16 p. | en_US |
dc.format.medium | ||
dc.identifier.citation | Ngubane, Z. et al. 2022. Water quality modelling and quantitative microbial risk assessment for uMsunduzi River in South Africa. Journal of Water and Health. 20(4): 641-656. doi:10.2166/wh.2022.266 | en_US |
dc.identifier.doi | 10.2166/wh.2022.266 | |
dc.identifier.issn | 1477-8920 | |
dc.identifier.issn | 1996-7829 (Online) | |
dc.identifier.other | isidoc: 0V3JI | |
dc.identifier.other | pubmed: 35482381 | |
dc.identifier.uri | https://hdl.handle.net/10321/3965 | |
dc.language.iso | en | en_US |
dc.publisher | IWA Publishing | en_US |
dc.relation.ispartof | Journal of Water and Health; Vol. 20, Issue 4 | en_US |
dc.subject | Cryptosporidium | en_US |
dc.subject | Escherichia coli (E. coli) | en_US |
dc.subject | QMRA | en_US |
dc.subject | SWAT | en_US |
dc.subject | uMsunduzi River | en_US |
dc.subject | water quality modelling | en_US |
dc.subject | Microbiology | en_US |
dc.subject.mesh | Humans | |
dc.subject.mesh | Cryptosporidium | |
dc.subject.mesh | Escherichia coli | |
dc.subject.mesh | Cryptosporidiosis | |
dc.subject.mesh | Risk Assessment | |
dc.subject.mesh | Rivers | |
dc.subject.mesh | South Africa | |
dc.subject.mesh | Water Quality | |
dc.subject.mesh | Cryptosporidiosis | |
dc.subject.mesh | Cryptosporidium | |
dc.subject.mesh | Escherichia coli | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Risk Assessment | |
dc.subject.mesh | Rivers | |
dc.subject.mesh | South Africa | |
dc.subject.mesh | Water Quality | |
dc.title | Water quality modelling and quantitative microbial risk assessment for uMsunduzi River in South Africa | en_US |
dc.type | Article | en_US |
local.sdg | SDG06 |
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