气候变化领域集成服务门户(CCPortal): Spatiotemporal prediction of Escherichia coli and Enterococci for the Commonwealth Games triathlon event using Bayesian Networks

CCPortal

DOI	10.1016/j.marpolbul.2019.05.066
	Spatiotemporal prediction of Escherichia coli and Enterococci for the Commonwealth Games triathlon event using Bayesian Networks
	Bertone E.; Purandare J.; Durand B.
发表日期	2019
ISSN	0025326X
起始页码	11
结束页码	21
卷号	146
英文摘要	A number of Bayesian Networks were developed in order to nowcast and forecast, up to 4 days ahead and in different locations, the likelihood of water quality within the 2018 Commonwealth Games Triathlon swim course exceeding the critical limits for Enterococci and Escherichia coli. The models are data-driven, but the identification of potential inputs and optimal model structure was performed through the parallel contribution of several stakeholders and experts, consulted through workshops. The models, whose main nodes were discretised with a customised discretisation algorithm, were validated over a test set of data and deployed in real-time during the Commonwealth Games in support to a traditional water quality monitoring program. The proposed modelling framework proved to be cost-effective and less time-consuming than process-based models while still achieving high accuracy; in addition, the added value of a continuous stakeholder engagement guarantees a shared understanding of the model outputs and its future deployment. © 2019 Elsevier Ltd
英文关键词	Bayesian Network; Enterococci; Escherichia coli; Prediction modelling; Triathlon; Water resources management
语种	英语
scopus关键词	Cost effectiveness; Escherichia coli; Forecasting; Software testing; Stadiums; Structural optimization; Water quality; Water resources; Enterococci; Optimal model structures; Prediction modelling; Spatio-temporal prediction; Stakeholder engagement; Triathlon; Water quality monitoring; Water resources management; Bayesian networks; Bayesian analysis; coliform bacterium; marine pollution; modeling; pollution monitoring; prediction; spatiotemporal analysis; sport; stakeholder; water management; water quality; water resource; article; Escherichia coli; human; monitoring; nonhuman; prediction; stakeholder engagement; water availability; water quality; Bayes theorem; Enterococcus; Escherichia coli; growth, development and aging; isolation and purification; microbiology; Escherichia coli; fresh water; Bayes Theorem; Enterococcus; Escherichia coli; Fresh Water; Water Quality
来源期刊	Marine Pollution Bulletin
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/149758
作者单位	School of Engineering and Built Environment, Griffith University, Gold Coast CampusQLD 4222, Australia; Cities Research Institute, Griffith University, Gold Coast CampusQLD 4222, Australia; Gold Coast Water and Waste, City of Gold Coast, QLD 4211, Australia
推荐引用方式 GB/T 7714	Bertone E.,Purandare J.,Durand B.. Spatiotemporal prediction of Escherichia coli and Enterococci for the Commonwealth Games triathlon event using Bayesian Networks[J],2019,146.
APA	Bertone E.,Purandare J.,&Durand B..(2019).Spatiotemporal prediction of Escherichia coli and Enterococci for the Commonwealth Games triathlon event using Bayesian Networks.Marine Pollution Bulletin,146.
MLA	Bertone E.,et al."Spatiotemporal prediction of Escherichia coli and Enterococci for the Commonwealth Games triathlon event using Bayesian Networks".Marine Pollution Bulletin 146(2019).