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Applying spatial regression to evaluate risk factors for microbiological contamination of urban groundwater sources in Juba, South Sudan
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Land and Water Resources Engineering. KTH, School of Architecture and the Built Environment (ABE), Transport Science. (Environmental Management and Assessment)ORCID iD: 0000-0002-5290-5704
KTH, School of Architecture and the Built Environment (ABE), Transport Science.ORCID iD: 0000-0001-5290-6101
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Land and Water Resources Engineering. (Environmental Management and Assessment)ORCID iD: 0000-0002-1640-8946
2017 (English)In: Hydrogeology Journal, ISSN 1431-2174, E-ISSN 1435-0157, Vol. 25, 1077-1091 p.Article in journal (Refereed) Published
Abstract [en]

This study developed methodology for statistically assessing groundwater contamination mechanisms. It focused on microbial water pollution in low-income regions. Risk factors for faecal contamination of groundwater-fed drinking-water sources were evaluated in a case study in Juba, South Sudan. The study was based on counts of thermotolerant coliforms in water samples from 129 sources, collected by the humanitarian aid organisation M,decins Sans FrontiSres in 2010. The factors included hydrogeological settings, land use and socio-economic characteristics. The results showed that the residuals of a conventional probit regression model had a significant positive spatial autocorrelation (Moran's I = 3.05, I-stat = 9.28); therefore, a spatial model was developed that had better goodness-of-fit to the observations. The most significant factor in this model (p-value 0.005) was the distance from a water source to the nearest Tukul area, an area with informal settlements that lack sanitation services. It is thus recommended that future remediation and monitoring efforts in the city be concentrated in such low-income regions. The spatial model differed from the conventional approach: in contrast with the latter case, lowland topography was not significant at the 5% level, as the p-value was 0.074 in the spatial model and 0.040 in the traditional model. This study showed that statistical risk-factor assessments of groundwater contamination need to consider spatial interactions when the water sources are located close to each other. Future studies might further investigate the cut-off distance that reflects spatial autocorrelation. Particularly, these results advise research on urban groundwater quality.

Place, publisher, year, edition, pages
Springer, 2017. Vol. 25, 1077-1091 p.
National Category
Environmental Engineering
Research subject
Land and Water Resources Engineering
Identifiers
URN: urn:nbn:se:kth:diva-168241DOI: 10.1007/s10040-016-1504-xISI: 000401787800015OAI: oai:DiVA.org:kth-168241DiVA: diva2:815113
Note

QC 20170614

Available from: 2015-05-29 Created: 2015-05-29 Last updated: 2017-06-14Bibliographically approved
In thesis
1. Predicting the transport of Escherichia coli to groundwater
Open this publication in new window or tab >>Predicting the transport of Escherichia coli to groundwater
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Groundwater contamination with pathogens poses a health risk worldwide. Predictive modeling could provide decision support for risk analysis in this context. This study therefore aimed to improve predictive modeling of the transport of Escherichia coli (E. coli) to groundwater. Primarily, it included a review of the state-of-the-art of the underlying process, influencing factors and modeling approaches that relate to E. coli transport in the unsaturated zone. Subsequently, two recently developed models were innovatively applied to the context of microbial contamination. The Active Region Model was evaluated as an alternative to the traditional, uniform flow model (Richard’s equation) to describe bacterial transport in a wastewater treatment facility. It resulted in removal rates that were two orders of magnitude smaller than the traditional approach, more consistently with observations. The study moreover assessed the relevance of a spatial probit model to estimate the probability of groundwater source contamination with thermotolerant coliforms in a case study in Juba, South Sudan. A conventional probit regression model resulted in spatially auto-correlated residuals, pointing to that the spatial model was more accurate. The results of this approach indicated that the local topography and the near presence of areas with informal settlements (Tukul zones) were associated with contamination. Statistical analyses moreover suggested that the depth of cumulative, long-term antecedent rainfall and on-site hygiene were significant risk factors. The findings indicated that the contributing groundwater was contaminated in Juba, and that contamination could be both local and regional in extent. They are relevant for environments with similar climatic, hydrogeological and socioeconomic characteristics, which are common in Sub-Saharan Africa. The results indicated that it is important to consider spatial interactions in this subject area. There is a need for studies that assess the distance within which such interactions can occur, using both mechanistic and statistical methods. Lastly, the results in this study consistently emphasized the importance of flow patterns for E. coli transport. It is thus recommended that future studies evaluate how models of preferential flow and transport can incorporate microbial fate. The multidisciplinary nature of the subject calls for a systems approach and collaboration between disciplines.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. x, 34 p.
Series
TRITA-LWR. PHD, ISSN 1650-8602 ; 2015:04
National Category
Environmental Engineering
Identifiers
urn:nbn:se:kth:diva-168242 (URN)978-91-7595-618-3 (ISBN)
Public defence
2015-06-15, Kollegiesalen, Brinellvägen 8, KTH, Stockholm, 14:00 (English)
Opponent
Supervisors
Note

QC 20150529

Available from: 2015-05-29 Created: 2015-05-29 Last updated: 2015-05-29Bibliographically approved

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Engström, Emma

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