Researcher

2020 Bayesian Modeling for Socio-Environmental Data Short Course

 

Solutions to pressing environmental problems require understanding connections between human and natural systems. Analysis of these systems requires a model that can deal with complexity, is able to exploit data from multiple sources, and is honest about the uncertainty from multiple sources. Synthesis of results from multiple studies is often required. Bayesian hierarchical models provide a powerful approach to analysis of socio-environmental problems.

The Story of Urban Water Management Transitions

 

Looking to lessons from the past to inform the future 

Cities face increasing threats to water supplies, but how can they transition towards more sustainable water management? Rapid urbanization, population growth, regulatory frameworks, and multiple competing demands combine to complicate the ability for urban water managers to guarantee future water supplies.

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