Infrastructure alone cannot ensure resilience to weather events in drinking water supplies.

Climate resilient water supplies are those that provide access to drinking water that is sustained through seasons and through extreme events, and where good water quality is also sustained. While surface and groundwater quality are widely understood to vary with rainfall, there is a gap in the evidence on the impact of weather and extremes in rainfall and temperature on drinking water quality, and the role of changes in water system management. A three-country (Bangladesh, Nepal and Tanzania) observational field study tracked 2353 households clustered around 685 water sources across seven different geographies over 14 months. Water quality (E. coli) data was modelled using GEE to account for clustering effects and repeated measures at households. All types of infrastructure were vulnerable to changes in weather, with differences varying between geographies; protected boreholes provided the greatest protection at the point of collection (PoC). Water quality at the point of use (PoU) was vulnerable to changes in weather, through changes in PoC water quality as well as changes in management behaviours, such as safe storage, treatment and cleaning. This is the first study to demonstrate the impact of rainfall and temperature extremes on water quality at the PoC, and the role that weather has on PoU water quality via management behaviours. Climate resilience for water supplies needs to consider the infrastructure as well as the management decisions that are taking place at a community and household level.

Modelling the influence of short-term climate variability on drinking water quality in tropical developing countries: A case study in Tanzania.

Climate change is expected to increase the prevalence of water-borne diseases especially in developing countries. Climate-resilient drinking water supplies are critical to protect communities from faecal contamination and thus against increasing disease risks. However, no quantitative assessment exists for the impacts of short-term climate variability on faecal contamination at different drinking water sources in developing countries, while existing understanding remains largely conceptual. This critical gap limits the ability to predict drinking water quality under climate change or to recommend climate-resilient water sources for vulnerable communities. This study aims to provide such quantitative understanding by investigating the relationships between faecal contamination and short-term climate variability across different types of water sources. We collected a novel dataset with over 20 months' monitoring of weather, Escherichia coli (E. coli) and total coliforms, at 233 different water sources in three climatically different regions in Tanzania. We then took a rigorous statistical analysis with Bayesian hierarchical models, to relate both contamination occurrence and amount to climate variability. The model results explained the temporal variability in drinking water faecal contamination using climate predictors, and also revealed the climate sensitivity of faecal contamination for individual water sources. We found that: a) short-term climate variability and baseline contamination levels can explain about half the observed variability in faecal contamination (R2 ≥ 0.44); b) increased contamination was most consistently related to recent heavy rainfall and high temperature across different water sources; c) unimproved water sources such as the unprotected dug wells have substantially higher climate sensitivity. Based on these results, we can expect substantial increases in drinking water contamination risks across tropical Sub-Saharan Africa and South-East Asian developing countries under a warmer climate, which highlight the urgent need of protecting vulnerable communities from the severe climate impacts.

Understanding the Impacts of Short-Term Climate Variability on Drinking Water Source Quality: Observations From Three Distinct Climatic Regions in Tanzania.

Climate change is expected to increase waterborne diseases especially in developing countries. However, we lack understanding of how different types of water sources (both improved and unimproved) are affected by climate change, and thus, where to prioritize future investments and improvements to maximize health outcomes. This is due to limited knowledge of the relationships between source water quality and the observed variability in climate conditions. To address this gap, a 20-month observational study was conducted in Tanzania, aiming to understand how water quality changes at various types of sources due to short-term climate variability. Nine rounds of microbiological water quality sampling were conducted for Escherichia coli and total coliforms, at three study sites within different climatic regions. Each round included approximately 233 samples from water sources and 632 samples from households. To identify relationships between water quality and short-term climate variability, Bayesian hierarchical modeling was adopted, allowing these relationships to vary with source types and sampling regions to account for potentially different physical processes. Across water sources, increases in E. coli/total coliform levels were most closely related to increases in recent heavy rainfall. Our key recommendations to future longitudinal studies are (a) demonstrated value of high sampling frequency and temporal coverage (a minimum of 3 years) especially during wet seasons; (b) utility of the Bayesian hierarchical models to pool data from multiple sites while allowing for variations across space and water sources; and (c) importance of a multidisciplinary team approach with consistent commitment and sharing of knowledge.