Characterizing the Human Dimension of Urban Water Systems in the Southwestern United States

Abstract

Providing adequate water supply to the growing number of urban residents will be a challenge faced by many utility managers throughout the remainder of this century. This challenge will be exacerbated by intensifying climate change that is likely to bring more frequent and intense droughts to some regions in the United States, including the Southwest. Understanding the impacts of these droughts on urban areas and the role that people play in either mitigating or intensifying them is crucial if society is to maintain its current trajectory towards sustainable urban development. Focusing on the role of people, this talk will discuss the characterization of residents’ attitudes and values surrounding water conservation and climate change within three major southwestern cities—Denver (CO), Las Vegas (NV), and Phoenix (AZ). In particular, the modeling framework leverages a state-of-the-art statistical machine learning algorithm to cluster survey respondents into seven categories, or archetypes. These archetypes can be used by water managers that are interested in developing community-specific intervention plans for water conservation, as well as by researchers interested in modeling the impacts of attitudes and beliefs on actual water consumption. In the face of rapid urbanization and climate change, it will become increasingly important to understand the relationship between climate change and urban systems, as well as the impact that people can have on these systems. 

Presenters

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Renee Obringer

Postdoctoral Fellow

Dr. Renee Obringer is an interdisciplinary researcher working at the nexus of data science, urban systems, and climate change. Her research ranges from using machine learning to model urban reservoir levels to analyzing the impact of climate change on the water-energy nexus. Renee earned her PhD in environmental and ecological engineering from Purdue University in 2020. She was also a member of the Ecological Science and Engineering Interdisciplinary Graduate Program at Purdue. At SESYNC, Renee uses a combination of machine learning and agent-based modeling to better understand the...

Image

Renee Obringer

Postdoctoral Fellow

Dr. Renee Obringer is an interdisciplinary researcher working at the nexus of data science, urban systems, and climate change. Her research ranges from using machine learning to model urban reservoir levels to analyzing the impact of climate change on the water-energy nexus. Renee earned her PhD in environmental and ecological engineering from Purdue University in 2020. She was also a member of the Ecological Science and Engineering Interdisciplinary Graduate Program at Purdue. At SESYNC, Renee uses a combination of machine learning and agent-based modeling to better understand the relationship between urban residents and anthropogenic droughts. She is interested in the impact people may have on improving or exacerbating existing droughts, as well as the feedback loops that may develop over time. Currently, she is considering the southwestern United States as a case study with plans to develop a broad methodological technique that could be applied across the world.

External Links:
https://www.reneeobringer.com

Date
Time
11:00 a.m. ET
Location
This is a virtual seminar.
This seminar has been recorded.
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