Limnetica 38

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Decision support framework to identify lakes that are likely to meet water quality targets if external inputs of phosphorus from agriculture are reduced

Linda May, Philip Taylor, Bryan Spears, Jo-Anne Pitt, Adrian L. Collins, Isabel Corkley, Steven Anthony, David Skirvin, David Lee and Pamela Naden
2019
38
1
489-501
DOI: 
10.23818/limn.38.28

About 40 % of European lakes are failing water quality targets for chemistry that have been set under the EU Water Framework Directive (WFD). One of the main causes of this problem is excessive inputs of phosphorus (P) to lakes from their catchments, including those from agricultural sources and wastewater treatment works. This study used WFD monitoring data from England and Wales to develop a method of identifying lakes that are failing WFD water quality targets for good status in terms of total phosphorus (TP) concentrations and whose problems could be solved by reducing P inputs from agricultural sources. A decision support framework is presented that (1) identifies lakes that are failing to achieve good status due to high TP inputs from agriculture; (2) predicts how in-lake TP concentrations are likely to respond to reduced inputs from agricultural sources, and (3) identifies sites where recovery is likely to be delayed by factors that induce resistance to TP mitigation measures. Through a worked example, we demonstrate how a decision support framework can be used to screen lake WFD monitoring data to identify where expensive restoration measures are likely to be more cost effective. We demonstrate that, in general, reducing the external TP load from agricultural sources would be effective only if introduced as part of a more comprehensive programme of restoration measures targeting other sources of TP, such as waste water treatment works, and taking into account lake-specific factors that affect lake response. The outputs from this decision support framework are designed to enable water managers to identify sites where recovery may be delayed by lake specific biological, chemical or physical characteristics, allowing them to manage expectations of the recovery process better by providing realistic timescales.

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