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Development of a new risk-based framework to guide investment in water quality monitoring

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Abstract

An innovative framework for optimising investments in water quality monitoring has been developed for use by water and environmental agencies. By utilising historical data, investigating the accuracy of monitoring methods and considering the risk tolerance of the management agency, this new methodology calculates optimum water quality monitoring frequencies for individual water bodies. Such information can be applied to water quality constituents of concern in both engineered and natural water bodies and will guide the investment of monitoring resources. Here we present both the development of the framework itself and a proof of concept by applying it to the occurrence of hazardous cyanobacterial blooms in freshwater lakes. This application to existing data demonstrates the robustness of the approach and the capacity of the framework to optimise the allocation of both monitoring and mitigation resources. When applied to cyanobacterial blooms in the Swan Coastal Plain of Western Australia, we determined that optimising the monitoring regime at individual lakes could greatly alter the overall monitoring schedule for the region, rendering it more risk averse without increasing the amount of monitoring resources required. For water resources with high-density temporal data related to constituents of concern, a similar reduction in risk may be observed by applying the framework.

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Acknowledgments

This project was supported under the Australian Research Council’s Linkage Project funding scheme (LP0776571). The authors would like to thank E. S. Reichwaldt, L. X. Coggins, M. J. Francis, D. D. Boland and H. Barrington for comments on the manuscript.

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Authors and Affiliations

  1. Aquatic Ecology and Ecosystem Studies, M015, School of Environmental Systems Engineering, The University of Western Australia, 35 Stirling Highway, Crawley, Western Australia, 6009

    Dani J. Barrington, Anas Ghadouani & Som Cit Sinang

  2. Geophysical Fluid Dynamics, M015, School of Environmental Systems Engineering, The University of Western Australia, 35 Stirling Highway, Crawley, Western Australia, 6009

    Gregory N. Ivey

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  1. Dani J. Barrington
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  2. Anas Ghadouani
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  3. Som Cit Sinang
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  4. Gregory N. Ivey
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Correspondence to Dani J. Barrington.

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Barrington, D.J., Ghadouani, A., Sinang, S.C. et al. Development of a new risk-based framework to guide investment in water quality monitoring. Environ Monit Assess 186, 2455–2464 (2014). https://doi.org/10.1007/s10661-013-3552-1

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  • DOI: https://doi.org/10.1007/s10661-013-3552-1

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