My research aims primarily to enhance decision-making capacity in environmental management by characterizing tradeoffs that cross traditional disciplinary lines and by developing modeling capacity for environmental/health outcomes of interest.
I was trained as a hydraulic/water resources engineer, and my core technical expertise falls in environmental fluid mechanics and statistical modeling, where I have published focused work (e.g., Calder et al. 2013). I gained expertise in human health and exposure modeling in the course of my doctoral studies in environmental health, and my work now weaves together methods from engineering and public health.
My doctoral work developed forecasting tools for methylmercury exposure impacts associated with hydroelectric power development and screened the potential health impacts of food consumption advisories for Indigenous populations. This work synthesized methods from engineering (e.g., computational fluid dynamics) and public health (e.g., epidemiological forecasting) to develop holistic risk analysis and decision-support tools.
In my postdoctoral work, I have been developing tools to bridge the gap between the outputs of traditional environmental models (e.g., water quality parameters) and the ‘ecosystem services’ of ultimate interest to society (e.g., avoided water treatment costs). These tools demonstrate that mechanistic modeling approaches can produce narrower estimates for benefits and costs of management options than landcover-based benefits-transfer approaches.
I am interested in how environmental policy is driven by risk perception and measurement and by social and political conditions. My drinking water policy work describes the role of falling detection limits in advancing regulation and compares American and Canadian approaches to drinking water regulation through the lens of social and political realities.