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Professor Kuczera is recognised as a world authority on the theory and application of Bayesian statistical methods in hydrology and water resources. His research addresses the fundamental problem in application of hydrology to water engineering, namely limited predictive ability arising from large errors in data and model errors arising from limited understanding of dynamics and complexity. His work has focused on developing methods that make the best use of limited information and quantifying uncertainty to inform the decision making process. In recent years he and his team have developed BATEA, Bayesian total error analysis, which provides a comprehensive treatment of all major sources of uncertainty affecting hydrologic prediction.
He has made significant contributions in the area of water resources systems analysis. In recent years his team has developed decision support systems for urban water resource planning that use multi-objective optimization to identify optimal trade-off portfolios of capital and operational options. His work on integrated urban water management seeks to maximize community benefits by integrating water supply, storm water and waste water at small to large scales.
He has made significant contributions in the area of water resources systems analysis. In recent years his team has developed decision support systems for urban water resource planning that use multi-objective optimization to identify optimal trade-off portfolios of capital and operational options. His work on integrated urban water management seeks to maximize community benefits by integrating water supply, storm water and waste water at small to large scales.
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