Abstract
As coastal populations increase, considerable pressures are exerted on estuarine environments. Recently, there has been a trend towards the development and use of estuarine assessment schemes as a decision support tool in the management of these environments. These schemes offer a method by which complex environmental data is converted into a readily understandable and communicable format for informed decision making and effective distribution of limited management resources. Reliability and effectiveness of these schemes are often limited due to a complex assessment framework, poor data management and use of ineffective environmental indicators. The current scheme aims to improve reliability in the reporting of estuarine condition by including a concise assessment framework, employing high-value indicators and, in a unique approach, employing fuzzy logic in indicator evaluation. Using Sydney estuary as a case study, each of the 15 sub-catchment/sub-estuary systems were assessed using the current scheme. Results identified that poor sediment quality was a significant issue in Blackwattle/Rozelle Bay, Iron Cove and Hen and Chicken Bay while poor water quality was of particular concern in Duck River, Homebush Bay and the Parramatta River. Overall results of the assessment scheme were used to prioritise the management of each sub-catchment/sub-estuary assessed with Blackwattle/Rozelle Bay, Homebush Bay, Iron Cove and Duck River considered to be in need of a high priority management response. A report card format, using letter grades, was employed to convey the results of the assessment in a readily understood manner to estuarine managers and members of the public. Letter grades also provide benchmarking and performance monitoring ability, allowing estuarine managers to set improvement targets and assesses the effectiveness of management strategies. The current assessment scheme provides an effective, integrated and consistent assessment of estuarine health and provides an effective decision support tool to maximise the efficient distribution of limited management resources.
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