The use of a GIS-based inventory to provide a national assessment of standing waters at risk from eutrophication in Great Britain

Abstract

A three-tiered, hierarchical, risk-based prioritisation system was developed to assess the number of standing waters in Great Britain (GB) at risk from eutrophication. The scheme is based on four properties: importance, hazard, sensitivity to enrichment and sensitivity to recovery. Lake size, conservation status and legislative requirements were used to assess importance. The anthropogenic total phosphorus (P) load estimated from land cover, livestock and population data was used as a measure of the eutrophication hazard. Lakes with a retention time >3 days were considered to be sensitive to enrichment. The Wederburn depth (an estimate of the average summer thermocline depth) was used to predict the potential response of a lake to nutrient reduction. Lakes which were mainly stratified or fully stratified during the summer were expected to respond quickly to remediation. An initial Tier 1 risk assessment was made for all standing waters in GB (approximately 14,300 with surface area greater than 1 ha), using the four parameters derived from nationally available, GIS-based data sources held in the GB Lakes Inventory. Of the 2362 important lakes in GB, the system identified 1736 with low hazard but under potential threat because of their high sensitivity to enrichment. The system assessed that the ecology of 212 was likely to be damaged by eutrophication owing to high hazard and high sensitivity but with relatively poor chance of recovery following remediation. A further 332 lakes were considered to be damaged but were likely to respond to rehabilitation. In summary, the risk-based prioritisation system performed well and provides a useful tool for assessing standing waters at risk of eutrophication on a national basis. Inevitably, however, the need for nationally available datasets at Risk Tier 1 results in data resolution issues and errors may occur. The results highlight the importance of data validation using lake-specific information at Risk Tier 2