Baseline surveys

Ekiti State, Nigeria
World Bank Group Innovation Fund
Community-based 'crowd seeds' learned how to perform surveys and water quality tests using the mWater kit in a 3-day training. They also learned how to conduct household surveys and how to use mWater to map water sources and record the water test results.
Community-based 'crowd seeds' learned how to perform surveys and water quality tests using the mWater kit in a 3-day training. They also learned how to conduct household surveys and how to use mWater to map water sources and record the water test results.

Summary

In advance of a major water sector investment, The World Bank asked mWater to design a baseline evaluation tool that collected gender-disaggregated data on water access, water quality test results, and the distance that women walked for water, using GPS sensors. mWater trained 10 male and 10 female enumerators who live in this neighborhood. This dashboard tells the story of the data they collected over the course of three weeks in June 2014.

Water choices

mWater included the Progress out of Poverty assessment in the household survey questionnaire. This tool estimates a household's likelihood of being impoverished using 10 simple questions, such as "does this household have a television?" Ekiti residents showed surprisingly low levels of poverty. Most residents had TVs, almost all residents had graduated high school, and a majority had some college experience.

Given this, it was surprising that the overwhelming majority of residents chose shallow wells as their main source of drinking water. These hand-dug, unprotected shallow wells are among the most unsafe water sources.

mWater concluded from these results that in regions like Ekiti, where measures of income rose very sharply within one generation, a cultural legacy of unsafe water choices persists. The usual signs of a population relying on unsafe water sources, like stunting and poor health, are veiled by the region's wealth and easy access to primary healthcare such as antibiotics.

Gender differences

Household questionnaires asked each head of household male and head of household female (n=1,013) questions that assessed their perceptions of the amount of water stress their household experiences.

Predictably, men's estimation of the amount of water needed for the household was far less than women's. Also, men perceived water collection to be less of a burden on their household than women.

While men reported that they were as likely as women to collect water for the household, women disagreed, saying that they were twice as likely to collect water.

Men and women answer differently about who collects water and the burden involved
Men and women answer differently about who collects water and the burden involved

GPS sensors on water containers

In studies, there has been little correlation between self-assessed walk for water time and distance and actual, unobserved time and distance. To achieve an accurate baseline of access to water in the community, mWater worked with Sparx Engineering to develop GPS sensors to passively monitor the time and distance needed to gather water. The sensors which averaged $200/each were waterproof, lightweight, and could go 3 weeks without battery replacement or charge. Each sensor was fixed onto jerry cans and water buckets of Ekiti households over the three-week enumeration. The maps created of the households' walks to water sources were overlaid with the community water point mapping data, which included water quality of water sources. The end result was a rugged view of regions of the community where residents had few safe water choices, had few near choices, or both conditions. Infrastructure targets were strongly advised for community regions where both cases were true.
GPS sensor mounted on a bucket to measure walk distance and time
GPS sensor mounted on a bucket to measure walk distance and time
Map of the path walked by water bearers measured via a GPS sensor attached to their bucket
Map of the path walked by water bearers measured via a GPS sensor attached to their bucket

GPS Data Analysis

Sensors tracked the movement of water containers for 2 weeks at each household. mWater built software to analyze the GPS track data on the server to determine the locations of the home and water points, based on how long the sensor stopped in each place. Then key indicators were calculated, including number of trips per day and round trip time and distance to gather water.

Water quality

Water sources in the target neighborhoods were mapped and tested for contamination. mWater trained the crowdseeds to use the mWater test kit, which evaluates safety at the WHO and EPA standard for safe drinking water and for safe wash water. The majority of household water sources (shallow, open wells) were unsafe at both levels.