Studies indicate the world is off track to achieve water and clean sanitation for all by 2030.
Accurately mapping and monitoring geographic factors that influence access to water, sanitation, and hygiene can help ensure SDG 6 truly is "for all".
World Vision is employing machine learning, high resolution satellite imagery, and geographic information systems to map water access, with tangible policy results in Rwanda and Zambia.
Achieving Sustainable Development Goal (SDG) 6: Clean water and sanitation for all by 2030 will require a major course correction according to studies that indicate the world is far off-track.
To provide a detailed picture, a SDG6 Progress Report by UN-Water Integrated Monitoring Initiative for SDG 6 (IMI-SDG6) reports 2 billion people globally still lack access to safely managed drinking water and 3.6 billion people, or roughly 46% of the world’s population, are without access to safely managed sanitation services.
Determining the geography of water’s availability will play a key factor in ensuring water and sanitation is available for all by 2030. The “for all” caveat involves touching the most remote communities that may be missed or “invisible” on official population maps, which disadvantages communities from receiving the consideration and benefits of many policy initiatives. Therefore, monitoring and planning approaches in the water, sanitation, and hygiene (WASH) sector are critical towards securing availability and sustainably managed water for all.
World Vision is addressing this issue with the application of evolving technologies, specifically, high resolution population maps to better monitor progress and understand the geography of “water for all.” To ensure no one is left behind in terms of access to safe water, their team is working to fill relevant data gaps with the use of machine learning; high resolution satellite imagery; and geographic information systems. Focusing on Rwanda and Zambia, the three sources of high-resolution population data are visualized in maps that feature building locations, estimations of populations, development indicators, population distribution, topography, land cover, and other statistics.
To achieve their goals, World Vision engaged in several external collaborations. Fruitful partnerships with governments helped draw attention to the degree to which communities could exploit water supply facilities and the levels of water service coverage levels in a particular area. Even the use of OpenStreetMap enabled the World Vision team to employ volunteers to physically map locations, essentially guaranteeing an exceptional level of detail in the maps.
In Gasaka and Kamegeri, Rwanda, their work revealed about 60% of the population lived within the government’s prescribed distance of a water collection point. This data indirectly highlighted other groups without access and prompted further investigation and correction. In Zambia, their work also highlighted the population density around a water supply point, showing 77% of the population lived beyond the prescribed distance to an improved water point. Broadly, the total results of this project detected communities whose lack of water would have otherwise gone unregistered.
The results of this initiative are bringing the needs of the most distant communities into the spotlight, but ongoing work is needed to ensure truly achieving SDG 6 by 2030. For more information on the work of World Vision’s WASH monitoring approaches, visit The Geography of Clean Water for All (arcgis.com).
This article was written with support from the UN World Data Forum Secretariat. Read additional SDG Knowledge Hub stories about the UN World Data Forum, data impact, and news.