Applying spatial regression to evaluate risk factors for microbiological contamination of urban groundwater sources in Juba, South Sudan
Artikel i vetenskaplig tidskrift, 2017

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.

Microbial processes

Statistical modeling

Health

Urban groundwater

Sub-Saharan Africa

Författare

E. Engstrom

Kungliga Tekniska Högskolan (KTH)

U. Mortberg

Kungliga Tekniska Högskolan (KTH)

A. Karlstrom

Kungliga Tekniska Högskolan (KTH)

Mikael Mangold

Chalmers, Bygg- och miljöteknik, Vatten Miljö Teknik

Läkare utan gränser (MSF)

Hydrogeology Journal

1431-2174 (ISSN)

Vol. 25 4 1077-1091

Drivkrafter

Hållbar utveckling

Ämneskategorier

Vattenteknik

Mikrobiologi

Oceanografi, hydrologi, vattenresurser

Styrkeområden

Livsvetenskaper och teknik

DOI

10.1007/s10040-016-1504-x