Clean drinking water is hard to find in Mayange, Rwanda.

That's why a group of university students and two professors from the University of Redlands (U of R) in Redlands, California, traveled to this African region. Using the GIS technology and GPS equipment they brought along, they mapped the area's water sources and collected water use information. Their survey is helping improve access to clean drinking water in the community and in similar communities across sub-Saharan Africa.

This map shows building density and estimated housing expansion areas in the Mayange sector.

The maps are useful in providing local sustainable development programs with accurate locations of where people get their water. For example, the data can be used to identify areas where water sources are contaminated and support decisions about improving water quality, such as how to protect an open pit water source or where to dig a new water source. Ultimately, this field collection and mapping model may be used for mapping other water networks in Rwanda and other parts of Africa and to contribute to the implementation of sustainable practices in impoverished nations.

"Anything that we can do to improve water quality is going to have a major impact on the population," says Maxwell Baber, Ph.D., associate professor in the Master of Science in Geographic Information Science program at U of R. Baber and Katherine Noble-Goodman, a visiting lecturer in environmental studies at the university, led U of R undergraduate environmental studies students to the rural Mayange sector in 2008 and 2009.

In the bigger picture, the project contributes to an ambitious plan—the Millennium Development Goals (MDG)—that pledges to eliminate extreme poverty worldwide by 2015. Representatives from 192 United Nations (UN) member states signed on to the UN's MDG commitment to reduce poverty by improving health, education, agriculture, and infrastructure. Access to clean drinking water plays an important part in supporting these goals. MDG aims to reduce by half the proportion of people without sustainable access to safe drinking water.

Some progress has been made in advancing MDG goals, but in sub-Saharan Africa, improvements have advanced more slowly than in other parts of the world. As a result, the Millennium Villages Project (MVP) was established to create a successful model in Africa for alleviating poverty using a set of integrated, community-driven activities.

Mayange, with a sector population of 25,000, is one of 80 MVP participants spread across 10 African countries. Located in one of the poorest regions in Rwanda, the area is almost completely deforested and receives 800 millimeters (about 31.5 inches) of intermittent annual rainfall. As in many other rural African areas, Mayange villagers spend hours each day retrieving water their families need to survive. Often, the water source is contaminated, which can cause health problems. The time-consuming retrieval process also diverts efforts from activities crucial to sustainable development, such as education and farming.

"Clean, reliable sources of water for drinking, cooking, and other basic human needs are a necessary condition for the elimination of poverty and the success of sustainable development," says Noble-Goodman. In Rwanda, more than 25 percent of the population lacks access to clean water.

Using Garmin GPS equipment and ArcGIS (through their Esri University Site License), the teams spent a total of 15 days in May 2008 and 2009 in the field mapping and classifying water access points, such as wells, lakes, and cisterns. With help from local village leaders and guides and personnel from Rwanda National University and MVP, the students built a database of water sources by collecting GPS points and classifying each site as a shallow well, open pit, lake, deep borehole, water tap, or cistern.

The teams also collected survey data by talking with individuals who arrived at the sites to fill their water cans. The survey provided information on water use, household location and size, distance to the water source, and the seasonal availability of water. The survey's purpose was to help MVP participants prioritize areas in most need of improving the quality and quantity of water sources. "One goal of MVP is to have water within one kilometer of every household. This is very ambitious and will take a while," notes Molly Moore, a U of R student who participated in the project.

The data is being held by Didace Kayiranga, MVP science coordinator in Mayange. "It gives us tools for planning and to evaluate our indicators, such as distance from a household to a clean water source," says Kayiranga. "This indicator cannot be easily measured without overlaying the different household and water point layers."

The fieldwork gave students hands-on experience in learning how GIS technology can support projects that study the relationship between humans and the environment.

"And for a few days in May," adds Noble-Goodman, "students had the opportunity to help improve the community's access to clean, safe water."

U of R faculty and students continue to edit and revise the project data in graduate GIS classroom studies as a way to explore the spatial dimensions of public health issues. They are running analyses and creating spatial models to predict relative likelihood of productivity for new borehole well site locations. The most commonly employed model inputs are derived from household density (as analog for population density, to incorporate proximity to population concentrations) and relative terrain situation (valley or ridge, for relative proximity to groundwater).

More Information

For this project, U of R collaborated with Loma Linda University School of Public Health (www.llu.edu/llu/sph), the Millennium Villages Project (www.millenniumvillages.org), and National University of Rwanda Geographic Information Systems and Remote Sensing Centre (www.cgisnur.org). Grant money was provided by the Southern California Metropolitan Water District. Note: Maxwell Baber now holds the position of director of academic programs, U.S. Geospatial Intelligence Foundation.