What Environmental Factors Influence the Concentration of Fecal Indicator Bacteria in Groundwater? Insights from Explanatory Modeling in Uganda and Bangladesh

Abstract

Information about microbial water quality is critical for managing water safety and protecting public health. In low-income countries, monitoring all drinking water supplies is impractical because financial resources and capacity are insufficient. Data sets derived from satellite imagery, census, and hydrological models provide an opportunity to examine relationships between a suite of environmental risk factors and microbial water quality over large geographical scales. We investigated the relationships between groundwater fecal contamination and different environmental parameters in Uganda and Bangladesh. In Uganda, groundwater contamination was associated with high population density (p < 0.001; OR = 1.27), high cropland coverage (p < 0.001; OR = 1.47), high average monthly precipitation (p < 0.001; OR = 1.14), and high surface runoff (p < 0.001; OR = 1.37), while low groundwater contamination was more likely in areas further from cities (p < 0.001; OR = 0.66) and with higher forest coverage (p < 0.001; OR = 0.70). In Bangladesh, contamination was associated with higher weekly precipitation (p < 0.001; OR = 1.44) and higher livestock density (p = 0.05; OR = 1.11), while low contamination was associated with low forest coverage (p < 0.001; OR = 1.23) and high cropland coverage (p < 0.001; OR = 0.80). We developed a groundwater contamination index for each country to help decision-makers identify areas where groundwater is most prone to fecal contamination and prioritize monitoring activities. Our approach demonstrates how to harness satellite-derived data to guide water safety management.

Risk Factors Affecting the Bacterial Contamination in Water of Thailand’s Upper South 2020 - 2022

“…This was considered one of the reasons for the increased bacterial contamination. These results were congruent with the findings of Poulin et al [42], who discovered that strong rains could carry sewage from the neighborhood or agricultural runoff into water sources; bacterial contamination, therefore, rises.…”

Monitoring Drinking Water Quality in Nationally Representative Household Surveys in Low- and Middle-Income Countries: Cross-Sectional Analysis of 27 Multiple Indicator Cluster Surveys 2014–2020

“…The cross-sectional nature of the MICS water quality data, and the predominance of samples from the dry season may understate the importance of some risk factors. Geolocation of household survey clusters would also enable a wider range of environmental risk factors to be considered ( Poulin et al. 2020 ).…”

A global perspective on assessing groundwater quality

“…Satellite-based earth observations (EO) can produce proxies for groundwater contamination processes. Poulin et al (2020) showed that EO on population density, road density, precipitation, temperature and landcover in Uganda and Bangladesh were strongly correlated with microbial contamination levels in shallow groundwater. Earth observations can provide variables for use in prediction modelling-for example, EO-derived information on anthropogenic activities such as landcover or population density can be used to predict nitrate, herbicide concentrations and salinity in groundwater (Anning et al 2012;Stackelberg et al 2012).…”