Background
This visual furthers SDG 6: Clean Water and Sanitation by helping decision makers decide how much capital to invest in the region to ensure a standard of access to drinking water. Our visual displays the distance women and girls in Rwanda must travel to gain access to clean water (water points). We have included data that shows the condition of these water points (functional, non-functional, and functional but needs repair). The visualization calculates the distance to the closest water point for Rwanda’s women and girls and compares it to the cost of repair to help decision makers see the impact of investing in water sources.
Approach
Our visualization uses satellite population data as well as a dataset from the Water Point Data Exchange to evaluate how far women in Rwanda are from potable water points. We created the visualization in Python with packages such as Plotly, GeoPandas, Rasterio, and Shapely. To process the data in Python we loaded in the satellite population data and restricted it to women, since they are the most impacted by needing to travel to access water. The water point and population data were in the WGS84 (latitude and longitude), so the initial distance calculation was made in degrees to find the nearest water point for each population point. Once the nearest water point was identified in degrees, the distance to just the single nearest water point was calculated in kilometers using GeoPy. We created a 3D representation of the distance women are from freshwater points with the Plotly library. Then we removed water points listed as non-functional or with fecal coliform present as this indicates that the water is unsafe for drinking. The distance to the water points if they are all operational and cleared of fecal coliform can be compared to the distance without these water points using this interactive visualization.
Rwanda Population
Motivation
We were motivated to address water stress in Africa by both the disproportionate effect it has on women and girls, and the future of this issue which is only projected to worsen. UNICEF has estimated that women and girls spend altogether 200 million hours retrieving water every day. For women, gathering water significantly affects the time spent on childcare, other household tasks, or even leisure activities. For girls, water collection can take time away from their valuable education and therefore future prospects. When water needs to be retrieved, women and girls are paying with their time and missed opportunities, and it’s a lifetime burden. Additionally, access to clean water will be exacerbated by population growth and the effects of climate change in the future. By 2050 global water demand is estimated to climb by 20% to 25% due to population growth, and an additional 1 billion people are expected to live with extremely high water stress even if rising temperatures are regulated. With these additional motivating factors in mind our group decided to focus on water stress in Africa for our visualization.
Rwanda Population with Water Points
Access to water is critical
To learn more about the issue our group researched articles, literature, and stories that offered a more well-rounded view of the topic. The articles and literature with water stress statistics were important for understanding the overarching effects and global status of water stress, such as a publication from Nature Communications and this article from the World Resource Institute. While other articles had more of a narrative focus, showing a different view of the implications of water stress in Rwanda. One of the stories we found compelling was the article from World Vision about the “Pond of Misery” in Rwanda. In addition to articles and literature the group looked at videos from communities in Rwanda to better understand the living conditions of the area we were choosing to focus on. One example is a video detailing the story of two children’s struggle to provide their family with clean water. Perhaps the most important finding was articles on how this issue is impacting women and girls disproportionately, such as this link from UNICEF. This finding allowed us to narrow our topic to looking at distance to clean water and shape our analysis to focus on women and girls.
Distance to water 2D
As you can see in this 2D image, the distance to water is relatively low in the center of the country. But the distance to water grows significantly the more rural the population is on the outskirts of the country, especially in the south.
Data Ethics
We considered biased or incomplete data – data for the region can be scarce and reported census data from the Rwandan government might not always be completely reliable. To mitigate these issues, we prioritized impartial, quantitative data from 3rd party sources and tried to display visualizations at the highest demographic levels – urban vs rural populations. Rural populations will generally have to travel further to access clean water and this tool will help visualize that struggle so that decision makers can make more positive impacts.
Interactive Visualization
Our interactive 3D visualization of the distance to water for women in Rwanda is below.