U-M Industrial and Operations Engineering (IOE), associate professor, Seth Guikema and PhD candidate, Thomas Chen have won the 2019 Robert C Williams Engineering Literary Award from the U.S. Public Health Service for their work as co-authors on a paper exploring the risks to drinking water systems from extreme precipitation and flooding events.
“It is an honor to receive this award, particularly given both the societal importance of this problem and the interdisciplinary nature of both the problem and the research team brought together to address it. I thank David Harvey and Natalie Exum for their leadership in bringing this team together,” said Guikema.
The annual award recognizes exemplary written works of engineers and architects within the U.S. Public Health Service with an impact on public health being a key scoring factor.
“We explored the impact of drinking water regulations on the risks of disease outbreaks during flooding events, focusing on the aftermath of Hurricane Maria in Puerto Rico as a case study,” said Chen. “A review on the public communication efforts highlights some shortcomings that contributed to greater health risks to the community.”
The paper helps to enhance the understanding of the risks to drinking water systems from extreme precipitation and flooding events and the role that the current regulatory structure plays in how this risk is managed.
“There are needed changes in the regulatory structure that would allow these risks to be better managed. Examples include changes to the current practice of water quality sampling and issuances of emergency public notifications,” said Guikema.
The research team was comprised of Natalie Exum and Kellog Schwab from the Bloomberg School of Public Health at Johns Hopkins, David Harvey from the U.S. Department of Health and Human Services and Ellin Betanzo of Safe Water Engineering LLC.
Guikema joined IOE in 2015 and his recent research is grounded in risk analysis, particularly data-driven risk analysis and complex systems simulation. This research focuses on the challenges of urban and infrastructure resilience and sustainability in a changing climate.
Chen’s research interests focus on the application of mathematical tools to aid better decision making for critical infrastructure management. Such methodologies include statistical learning theory, data mining, and optimization routines.