Eutrophication is a major global concern in lakes, caused by excessive nutrient loadings (nitrogen and phosphorus) from human activities and likely exacerbated by climate change. Present use of indicators to monitor and assess lake eutrophication is restricted to water quality constituents (e.g., total phosphorus, total nitrogen) and does not necessarily represent global environmental changes and the anthropogenic influences within the lake’s drainage basin. Nutrients interact in multiple ways with climate, basin conditions (e.g., socio-economic development, point-source, diffuse source pollutants), and lake systems. It is therefore essential to account for complex feedback mechanisms and non-linear interactions that exist between nutrients and lake ecosystems in eutrophication assessments. However, the lack of a set of water quality indicators that represent a holistic understanding of lake eutrophication challenges such assessments, in addition to the limited water quality monitoring data available. In this review, we synthesize the main indicators of eutrophication for global freshwater lake basins that not only include the water quality constituents but also the sources, biogeochemical pathways and responses of nutrient emissions. We develop a new causal network (i.e., multiple links of indicators) using the DPSIR (drivers-pressure-state-impact-response) framework that highlights complex interrelationships among the indicators and provides a holistic perspective of eutrophication dynamics in freshwater lake basins. We further review the 30 key indicators of drivers and pressures using seven cross-cutting themes: (i) hydro-climatology; (ii) socio-economy; (iii) land use; (iv) lake characteristics; (v) crop farming and livestock; (vi) hydrology and water management; (vii) fishing and aquaculture. This study indicates a need for more comprehensive indicators that represent the complex mechanisms of eutrophication in lake systems, to guide the global expansion of water quality monitoring networks, and support integrated assessments to manage eutrophication. Finally, the indicators proposed in this study can be used by managers and decision-makers to monitor water quality and set realistic targets for sustainable water quality management to achieve clean water for all, in line with Sustainable Development Goal 6.
<p>Excessive nutrient (nitrogen and phosphorus) loadings to freshwater lakes cause eutrophication, which is a global water quality issue. Anthropogenic activities in lake basins emit nutrients, either as point- (e.g., sewage) or diffuse sources (e.g., agricultural runoff). Their typical impacts on lake water quality include the occurrence of harmful algal blooms, hypoxia and fish kills. These impacts are likely to worsen due to climate change, population growth and economic development. The response of lakes to a change in nutrient inputs depends on their interactions with the climate, land-use, hydrology and socio-economic conditions of a lake basin. These feedback mechanisms, however, are not often included in the eutrophication assessments for lakes. In this study, we present a new causal network of the drivers-pressure-state-impact-response (DPSIR) framework using a total of 58 sub-indicators to characterize all the DPSIR elements and systematically conceptualize the complex interactions of nutrients in freshwater lake basins. The network provides a holistic perspective on nutrient dynamics of multiple indicators and their interactive effects on water quality in lake basins, which is key to improving water quality management. Furthermore, we disentangle the complex eutrophication mechanisms using drivers and pressures, that represent different sources and nutrient pathways. The study highlights coupling of lake systems in water quality modeling frameworks and assessments which is required to understand its impact on water quality from human activities in the basin. The drivers and pressures can be used as proxies to provide meaningful information on nutrient emissions and biogeochemical pathways, that can fill the gap in water quality monitoring data, especially in data scarce regions such as Asia and Africa. These indicators can be used to set realistic water quality targets, and are, therefore, beneficial in long-term policy making and sustainable water quality management.</p>
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