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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.

Abstract. Complete understanding of the hydrological functioning of large-scale intertropical watersheds such as the Lake Chad basin is becoming a high priority in the context of climate change in the near future and increasing demographic pressure. This requires integrated studies of all surface water and groundwater bodies and of their quite-complex interconnections. We present here a simple method for estimating the annual mean water balance of sub-Sahelian lakes subject to high seasonal contrast and located in isolated regions with no road access during the rainy season, a situation which precludes continuous monitoring of in situ hydrological data. Our study focuses for the first time on two lakes, Iro and Fitri, located in the eastern basin of Lake Chad. We also test the approach on Lake Ihotry in Madagascar, used as a benchmark site that has previously been extensively studied by our group. We combine the δ18O and δ2H data that we measured during the dry season with altimetry data from the SARAL satellite mission in order to model the seasonal variation of lake volume and isotopic composition. The annual water budget is then estimated from mass balance equations using the Craig–Gordon model for evaporation. We first show that the closed-system behavior of Lake Ihotry (i.e., precipitation equal to evaporation) is well simulated by the model. For lakes Iro and Fitri, we calculate evaporation to influx ratios (E∕I) of 0.6±0.3 and 0.4±0.2, respectively. In the case of the endorheic Lake Fitri, the estimated output flux corresponds to the infiltration of surface water toward the surface aquifer that regulates the chemistry of the lake. These results constitute a first-order assessment of the water budget of these lakes, in regions where direct hydrological and meteorological observations are very scarce or altogether lacking. Finally, we discuss the implications of our data on the hydro-climatic budget at the scale of the catchment basins. We observe that the local evaporation lines (LELs) obtained on both lake and aquifer systems are slightly offset from the average rainfall isotopic composition monitored by IAEA at N'Djamena (Chad), and we show that this difference may reflect the impact of vegetation transpiration on the basin water budget. Based on the discussion of the mass balance budget we conclude that, while being broadly consistent with the idea that transpiration is on the same order of magnitude as evaporation in those basins, we cannot derive a more precise estimate of the partition between these two fluxes, owing to the large uncertainties of the different end-members in the budget equations.

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