Robust water quality information is critical
Understanding water quality trends in rivers, lakes and aquifers presents a significant challenge that many countries are unable to meet. Facing and addressing this challenge presents an opportunity that could help build climate change resilience on multiple fronts. This is especially relevant in those countries that are predicted to be most impacted by climate change, where currently the greatest water quality knowledge gaps exist.i
Differentiating between natural and anthropogenic water quality changes is essential to understand complex freshwater ecosystems, and the drivers of change within their catchments. Understanding the scope of natural fluctuation and what goes beyond natural requires the national agencies responsible for monitoring to have systems and processes in place that enable the collection and management of data and a robust assessment capacity that includes rigorous and meaningful water quality criteria. In addition, if the potential impact of this information is to be realised, there must also be an enabling environment for assessment outputs to be disseminated and acted upon. In many countries this capacity, these criteria and this environment are often absent or inadequate to provide the necessary information for sound decision making. This leads to inaction where action is essential, with problems persisting and the efficacy of measures to protect and restore water quality going unchecked or untracked.
Why the urgency?
Globally freshwaters are under the influence of multiple pressures in concert, and climate change adds another layer of uncertainty as to how these systems will react and respond in the futureii. For example, whether a lake will be able to support the current fishery, or drinking water supply in five, 10- or 20-years’ time is essential information.
Widespread deterioration of freshwater ecosystem structure and function is already underway.iii Climate change effects layered on top of prevailing problems related to pollution, habitat destruction and fragmentation, over abstraction and land use practices that are detrimental to freshwater ecosystem health mean that we are in uncharted territory. Some impacts can be considered slow-onset processes such as increasing temperature or regional reductions in overall rainfalliv, Whereas others can be instant and devastating such as the catastrophic tailings dam failure in Brazil in 2016.v For the former, early intervention measures aimed to slow, stop and reverse the trend, and thereby avoid any ecosystem “tipping points” are needed. Ecosystem pressure-response interactions are often non-linear, and only when a threshold is reached is the impact realised - and this is often too late. For the latter, a good understanding of baseline conditions prior to the incident are essential to ensure that restoration objectives are evidence-based and that by continuous monitoring, progress towards these objectives can be measured. In all cases, water quality data are needed today, to plan for the future. Of great concern, is that often, those countries that lack the capacity to monitor and assess their freshwaters are in low and mid-latitude regions where climate change impacts are predicted to be felt most severely.
Understanding capacity gaps
Information at the global level on countries’ capacity to monitor and assess their freshwaters is needed to identify support-provision mechanisms. Bilateral engagement between a supporting organisation and the target country can provide targeted and useful information, but a global overview that allows comparison and regional assessment has so far been unavailable.
A global assessment of national capacity to monitor and assessment freshwaters is urgently needed. Information such as that gathered through the implementation of SDG indicator 6.3.2 provides some understanding of where and how freshwater quality is being monitored and assessed, but this could be extended. Currently, UNEP requests countries to report on this indicator on a three-year cycle, and in addition to asking countries to apply their water quality data to a standardised methodology to calculate the indicator score, information on the monitoring programme and assessment method are also requested. This includes information on the water body type (river, lake or aquifer), the number of monitoring values used, the number of water bodies assessed, as well as information on target threshold values used in the classification process. Combining this information with metrics such as, per capita GDP, country area, and country wetness makes it possible to benchmark monitoring and assessment capacity against other countries as well as allows support agencies to target capacity development activities where most needed.
Around half of UN Member States have so far reported on the indicator, and some countries that are known to have advanced monitoring and assessment capacity are yet to do so, but regardless, this indicator and the subsequent analyses provide useful insight and strengthens the case for promoting the implementation of this indicator further.
Data gaps = information gaps
Analysis of countries’ SDG indicator 6.3.2 submissions has made some important patterns clear. For example, assigning countries to quartile groups based on per capita GDP, revealed that although the number of countries reporting from each GDP group was relatively equal (Figure 1), there was significant difference in the number of water bodies that were included in the indicator calculation. Low-income countries reported on far fewer water bodies than richer countries. The 22 poorest countries reported on 1,300 of the 77,200 compared with the 26 richest countries that reported on nearly 60,000 (Figure 2).
It is neither practical nor necessary for all water bodies to be included in a country’s monitoring and assessment programme, but a measure of the proportion which are routinely monitored provides a useful comparison of coverage and progress. Delineating river and groundwater bodies is more complex and variable between countries, whereas for lakes it is more straightforward and makes drawing a comparison more meaningful. There are approximately 1.4 million lakes over 10 hectares in area worldwidevi and Table 1 shows these distributed by SDG region along with the number reported on in 2020. The vast majority of lakes are found in the Europe and North America SDG region, and it is in this region where monitoring is greatest. Coverage in Latin America and Caribbean and the Sub-Saharan regions is relatively high, but this is most likely a reflection of higher reporting rates from these regions compared with those of Asia.
Table 1: Number of lakes and the number included in SDG indicator 6.3.2 reporting in 2020 per SDG Region
SDG Region | No. Lakes | No. Lakes reported on in 2020 | Percentage lakes reported on |
| Australia and New Zealand | 12,021 | 57 | 0.5% |
| Central and Southern Asia | 28,514 | 31 | 0.1% |
| Eastern and South-Eastern Asia | 37,151 | 72 | 0.2% |
| Europe and North America | 1,267,264 | 11,281 | 0.9% |
| Latin America and the Caribbean | 59,987 | 999 | 1.7% |
| Northern Africa and Western Asia | 2,502 | 13 | 0.5% |
| Oceania | 1,030 | 3 | 0.3% |
| Sub-Saharan Africa | 15,189 | 366 | 2.4% |
Assessment gaps
Many countries implement monitoring programmes that collect significant volumes of data, yet still the water bodies they monitor continue to degrade. The reasons for this degradation are often beyond the controls of the monitoring and assessment programme and relate to enforcement or legislative failures, but regardless, significant progress can be made by ensuring that the information generated from the collected data are properly assessed and fit for purpose.
Essential to the success of an assessment is knowing how to contextualise current water quality trends. This can be achieved by establishing water quality criteria that are either use-based, such as the quality of water required for drinking or irrigation, or ecosystem health-based that aim to ensure that natural or near-natural conditions are maintained or aspired to. For the latter, establishing a natural or near-natural baseline is essential, and this allows any deviation of water quality from these conditions to be identified as early as possible. This early identification and intervention is essential for protection, yet this key piece of information is often missing.
Even in regions where a strong legislative framework is in place, such as the European Union’s Water Framework Directive, the criteria designed to protect water quality are often too lenient to protect ecosystem health.vii This is despite active and extensive monitoring programmes with a rich and plentiful long-term data record being available. In regions where this is not the case, such as in many countries of the global south, this task of establishing meaningful water quality criteria is even more challenging. Most water bodies have already deviated from their natural condition, and the concept of the ‘shifting baseline syndrome’viiimeans that estimating by how far, is the only option left in many cases.
Building resilience
Ensuring that freshwaters continue to provide essential services for ecosystem and human health, as well as maintain and provide opportunities for livelihoods, and ensure food and water security requires management decisions to be made that rely on long-term water quality datasets and a robust assessment capacity. Understanding where gaps exist and where national capacity needs strengthening is an essential first step in this process.
In countries where capacity is weak, capacity development is urgently required to make best use of existing resources and to expand monitoring activities. Promoting the collection and assessment of basic data to meet immediate information requirements allows further capacity gaps to be explored and strategies developed to help fill them.
Once a solid and robust monitoring and assessment framework is established, this provides the basis for incorporating innovative and novel approaches. For example, combining nationally derived data with international data and products such as those from Earth observation or modelling approaches that rely on local validation, or similarly, developing new national data streams such as those from community or citizen initiatives become an option. These approaches only become realistic options once a solid foundation is in place upon which to build.
Summary
A national agency with a strong capacity are well positioned to collect water quality data that can feed into the assessment process. This agency can make use of ancillary data and products, it can establish baselines and trends, and feed this “decision-ready” information at spatial scales as required to those responsible for determining relevant policies and investments that affect freshwater protection and restoration (Figure 3). It is robust and science-based information that is critically needed to ensure that climate resilience is increased – especially in those countries where it is currently weakest.
FURTHER READING
- Scientists’ Warning to Humanity on the Freshwater Biodiversity Crisis. https://doi.org/10.1007/S13280-020-01318-8/METRICS
- Brazil’s Worst Mining Disaster: Corporations Must Be Compelled to Pay the Actual Environmental Costs https://doi.org/10.1002/eap.1461
- Climate Change 2022_ Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change https://doi.org/10.1017/9781009325844.Front
- Scientists’ Warning to Humanity: Rapid Degradation of the World’s Large Lakes https://doi.org/10.1016/J.JGLR.2020.05.006
- Investigating the Implications of Shifting Baseline Syndrome on Conservation https://doi.org/10.1002/PAN3.10140/SUPPINFO
- Estimating the Volume and Age of Water Stored in Global Lakes Using a Geo-Statistical Approach https://doi.org/10.1038/ncomms13603
- Associations between Climate Variables and Water Quality in Low- and Middle-Income Countries: A Scoping Review https://doi.org/10.1016/J.WATRES.2021.117996
- Establishing Nutrient Thresholds in the Face of Uncertainty and Multiple Stressors: A Comparison of Approaches Using Simulated Datasets https://doi.org/10.1016/J.SCITOTENV.2019.05.343
- Need for Harmonized Long-Term Multi-Lake Monitoring of African Great Lakes https://doi.org/10.1016/J.JGLR.2022.01.016
- European Aquatic Ecological Assessment Methods: A Critical Review of Their Sensitivity to Key Pressures https://doi.org/10.1016/J.SCITOTENV.2020.140075
- Shifting Baseline Syndrome: Causes, Consequences, and Implications https://doi.org/10.1002/FEE.1794
- Progress on Ambient Water Quality. Tracking SDG 6 Series: Global Indicator 6.3.2 Updates and Acceleration Needs https://www.unwater.org/publications/progress-on-ambient-water-quality-632-2021-update/
References
i United Nations Environment Programme 2021.
ii Nijhawan and Howard 2022; Plisnier et al. 2022; Jenny et al. 2020
iii Albert et al. 2021
iv IPCC 2022
v Garcia et al. 2016
vi Messager et al. 2016
vii Phillips et al. 2019; Poikane et al. 2020
viii Soga and Gaston 2018; Jones et al. 2020