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The Metric

Aug 18, 2014

The challenge of measuring global water quality

Figure 1. Global distribution of monitoring sites used for the 2010 EPI's Water Quality Index measure is uneven. (Source: CIESIN, Columbia University)

Despite the paramount importance of water to all human and ecosystem life, there still lacks any good measure to compare how countries perform on water quality. Poor data quality and coverage are largely to blame, but there also exist problematic framing issues, which undermine global indexing efforts. In this piece, we discuss some of the challenges in creating comparable water quality indicators and what is needed in the future.

“Will the Prime Minister confirm that the Yale University report, which he used to justify his claim that our water quality is second only to Iceland, has in fact been widely ridiculed by leading freshwater scientists and environmentalists, including former National Party candidate Guy Salmon, who says it is “totally flawed”?”

This question was posed by Opposition Labour Party representative Brendon Burns at a 2011 Parliamentary Hearing on New Zealand’s water quality, after Prime Minister John Key asserted that the country boasted the “world’s second best water quality.” That claim was based on New Zealand’s second-place ranking on a water quality measure (WATQI) in the 2010 Environmental Performance Index (EPI).

The WATQI was based on the UN Global Environmental Monitoring systems (UN GEMS), the only globally available database of national-level water quality parameters. However, as UN GEMS is a self-reported database, scientists within New Zealand question the selection of sites included, which they felt largely overlooked other more polluted bodies of water. Due to the overall sparseness and lack of spatial representation for many other countries, the EPI team imputed the WATQI for many countries (see Srebotnjak et al. (2010) for the methodology used).

We ultimately dropped the WATQI in subsequent editions of the EPI because of these challenges of gaps in country data. Since then, we have struggled to develop alternative measures of water quality. With advances in data collection and monitoring for other high-priority environmental issues, why do gaps still persist for measuring water quality? What are the challenges, and what can and cannot be done to address them?

Problems of Defining Water Quality

While there is little dispute within the international expert community that water quality is essential for human health and the vitality of ecosystems, developing a standard approach to measuring it has proved much more cumbersome. To properly measure and benchmark water quality, it is important first to define it. Water quality definitions vary widely depending on the source, location, and intended use of the water. As a result, no single or right definition of water quality exists. For example, it can be defined in terms of “quality for life” (e.g., drinking water); “quality for food production (e.g., to sustain agricultural activities), or the “quality for nature” (e.g., to support ecosystems or flora and fauna in a region).

How water quality performance indicators provide a policy signal is an even more challenging question. Water quality is influenced by context-specific factors such as background pollution, flow and volume of a water body, as well as precipitation rate, making it difficult to direct policy solutions because these are factors for which governments have no control. Additionally, a lack of uniformity and agreement over definition, measurement approaches, and parameters necessarily complicates target- setting. As Srebotnjak et al. (2012) write, “Ecological water quality targets differ according to the ecological uses of water resources, natural background conditions of the water systems, and what is considered as ‘ideal’ for different parts of the world”.

A single goal or target for water quality therefore may not even be possible or desirable to define.

Why the data gaps?

Owing perhaps to the difficulties regarding water quality definition and measurement, there is a lack of an international, coordinated effort to mobilize the scientific and policy communities to collaborate on measuring and recording data in a consistent and timely fashion. The UN GEMs dataset was voluntary, self-reported, and outdated (from 1990). Additionally, monitoring station density varied considerably by country, calling into question the representativeness of the data points. Figure 1 shows a map of the location of monitoring stations available in the UN GEMS database and the European Environment Agency that were used for the WATQI in the 2010 EPI. It is clear that the majority of data points are predominantly located in Europe, while major gaps exist in Central Asia, East Asia, and the entire African continent.

These data gaps and lack of standardization for definitions and measurement have experts estimating some time before a meaningful global indicator for water quality can be developed. For ecosystem freshwater, for example, water quality is entirely dependent upon a landscape’s ability to collect and purify water. Attempting to scale or aggregate these landscape-level dynamics, then, may not help with understanding the actual underlying drivers of quality. The future of the UN GEMS database is uncertain; funding from Environment Canada recently ended and the program is undergoing transition as the German and Irish governments take ownership.

Towards an ‘ideal’ water quality metric

What ideally, should an indicator of water quality be able to do? In developing the WATQI for the 2010 EPI, Srebotnjak et al. (2012) defined an “ideal” water quality metric capable of being defined at multiple levels (e.g., watershed/basin, river, community or national level) that can deliver information and context for decision-makers (e.g., water resource managers, public/private water utilities, policymakers) to:

•identify water quality problems in time and space,

•determine priority areas in water quality and resource management, e.g., the reduction of eutrophication-causing effluents from agriculture into surface water,

•compare water quality at different locations and/or points in time,

• allocate funds and resources more effectively and efficiently to ensure water quality satisfies the requirements dictated by its designated uses,

• enforce water quality standards and regulations,

• inform the public about the status and trends in water quality,

•predict if and how changes in water management are likely to affect water quality, e.g., as a result of land use changes,

•formulate efficient and effective water resource management strategies, and

•supply input to scientific research into the determinants of water quality.

Unfortunately, no clear definition, framework, or set of indicators meets all of these criteria, let alone is there data available to gauge them.

In an ideal world, the EPI’s measures of water – both in the Environmental Health and Ecosystem Vitality objectives – would include indicators of outputs, such as pollutant levels. However, due to the challenges of developing a water quality indicator, in the interim we’ve settled for second-best input measures that assess drivers of water quality, including the 2014 EPI’s indicator of wastewater treatment. The wastewater treatment indicator assesses the percentage of wastewater treated, normalized by the percentage of a country’s population that is connected to treatment. While not a perfect proxy for water quality, the indicator is being considered in the United Nations Sustainable Development Goal (SDG) for Water, to “ensure availability and sustainable management of water for all,” suggesting the importance policymakers are placing on wastewater treatment as a key factor.