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The Metric

Oct 15, 2015

EPI’s foray into crowdsourcing wastewater data: How did it go?

EPI polled experts from around the world to help update and improve its wastewater treatment indicator. This crowdsourcing effort yielded valuable information that will be included in the 2016 EPI report. Yet wastewater treatment data quality remains generally inconsistent. New methods are needed to collect comprehensive wastewater data and ultimately enhance wastewater treatment.
Screen capture from EPI's interactive wastewater map built by Yale College student Diego Torres-Quintanilla (

Discharging untreated wastewater into the environment has profound impacts on freshwater quality and human health.  Scientists have linked the discharge of untreated wastewater to increased child mortality and ecosystem degradation. Yet, until a team of Environmental Performance Index (EPI) researchers created a wastewater treatment indicator in 2014, no global database reported on wastewater treatment. The EPI indicator is an important first step to measuring this vital issue, but more research is needed to improve data coverage and quality.  

Information on water, where it exists, is inconsistent and especially difficult to coalesce into a meaningful indicator. As we developed the 2016 EPI methodology, we decided to employ a cost-effective, collaborative approach to enhance our wastewater indicator: crowdsourcing.   

We created an interactive map showing available wastewater treatment data, and asked experts and members of the public to weigh in. Is our data consistent with on-the-ground observations? Are our sources reliable or problematic? What other sources should we be using?

Click here to download a full-sized, pdf version of this infographic.

People from all over the world responded to our request, providing useful feedback and insights that would otherwise be near impossible to come by. A World Bank staff member based in Mozambique, for example, provided this helpful information:

“You have listed Mozambique as 5% connected and 50% treated.  Both numbers are optimistic. The Government’s urban water and sanitation strategic plan, drafted in 2009, estimated that 1.1% of the national population had sewerage connections… There has been little expansion of sewerage since then, and there has been significant urban growth, so the 1.1% estimate is unlikely to have increased.”

Sub-saharan Africa has particularly poor data coverage, meaning the insider’s assessment of Mozambique’s treatment capabilities -- from which I’ve excerpted -- contributes invaluable knowledge to a nearly barren information field.

Field work on one of the wastewater management training schemes run by Train-Sea-Coast GPA - a UN inter-agency collaboration (Image courtesy of GPA/UNDP).

In Austria, where wastewater information is easier to find, the Ministry of Agriculture, Forestry, Environment and Water Management pointed to a flaw in our scoring, describing how the country’s alpine geography makes the goal of 100% sewage connectivity impractical.  As of 2012, about 95% of Austria’s population was connected to sewer lines and the remaining 5%, the expert assured us, have their own, specialized solutions:

“[A]ll of the Austrian wastewater in urban as well as rural areas is adequately treated in centralised treatment plants or small individual solutions or collected in cesspits and regularly transported to treatment plants by trucks.”

These details give useful context to coarse wastewater treatment numbers, providing a clearer picture than the raw data can of how nations cope with geographical challenges.

Our call for input has enticed experts to come forward with information that complements and qualifies existing data, while others have shed light on untapped data sources.  A Yale School of Forestry & Environmental Studies alumnus from Chile had us take a closer look at our numbers, pointing us to a new data source:

“I think the percentage of water treated in Chile is higher than you have. I have the information from SISS ( the national water Chilean authority. The information from SISS is only for urban areas, so maybe that is the reason why the percentage is higher than you have.”

Some contributors have pointed out glaring data gaps in official records.  A water resource consultant from Puerto Rico, for instance, describes a key discrepancy in the data:

“The figure shown in the map for Puerto Rico (100% wastewater treated) reflects only the treatment to the wastewaters collected by the PR Aqueduct and Sewer Authority (PRASA). But the actual number of houses connected to the PRASA wastewater collection and treatment system is only 57% of the households. The balance represent about 650,000 septic tanks that discharge untreated or minimally treated wastewaters to the environment.”

The distinction between rates of wastewater treated and sewerage system connection rates is an important one. In Puerto Rico, wastewater that makes it to treatment plants is treated adequately, but many communities are not connected to treatment plants. This type of pattern is why we chose to include sewerage connection rates in our wastewater indicator. Ultimately, these suggestions improve the accuracy of our data, and also link us with a global community of experts interested in better understanding and improving wastewater treatment.

The crowdsourcing effort has produced encouraging results, but we still have a long way to go to fill a legion of data gaps. We have received no feedback from many countries. This silence may be due to the fact that it is very difficult to summarize an entire country’s treatment capabilities. Perhaps a national-level interactive map is not the best way to garner responses. We’re learning from this experience. Crowdsourcing initiatives won’t solve all of our data problems, but these efforts are a relatively inexpensive way of expanding data coverage. When well-designed, these methods can enhance data quality as well.

Improving wastewater treatment is a priority for the UN’s Sustainable Development Goal 6. The proposed target -- halving the proportion of untreated wastewater worldwide by 2030 -- is ambitious. If we are serious about making progress towards this goal, baseline treatment statistics need to be established, which require better data. The SDG's water targets have attracted a lot of attention and resources, but their success is anything but certain. Are we up to the tasks of improving wastewater treatment, making drinking water safe to consume, and restoring aquatic ecosystems? Accomplishing these goals must start from knowing where we currently stand with wastewater treatment. And in the absence of clear records, there is no better way to find out than to ask.

(United Nations Sustainable Development Goal 6: