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Runzi Wang

Runzi Wang
Assistant Professor
Landscape Architecture
Cities + Mobility + Built Environment
runziw@umich.edu
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About

Runzi Wang, PhD, is a transdisciplinary researcher who studies change in natural and urban environments across space and over time, with the objective to drive positive change with ecological planning and design strategies. Combining technologies such as big data, machine learning, remote sensing, and spatial statistics, her primary research explores how land cover change and urban development pattern influence stream water quality and stormwater quality at the watershed basis, together with a variety of environmental, climatic and sociocultural factors. By enhancing the interpretability of machine learning in its application to landscape architecture, the most innovative part of her research is to uncover the nonlinear relationships between environmental, technological and sociocultural dimensions of landscape systems.

The focus areas of Runzi’s research include 1) Neighborhood-scale green infrastructure design optimization. 2) Regional-scale water quality management. 3) Continental-scale landscape change monitoring and projection. Runzi is also a landscape designer engaged in evidence-based landscape and urban design projects, with the focus on stormwater management. She integrates research with the teaching topics of ecological design studio, landscape analysis, and site engineering.

Publications

Guan, J., Wang, R*., Van Berkel, D., & Liang, Z. (2023). How spatial patterns affect urban green space equity at different equity levels: A Bayesian quantile regression approach. Landscape and Urban Planning, 233, 104709.

Wang, R., Ma, Y., Zhao, G.*, Zhou, Y., Shehab, I., & Burton, A. (2023). Investigating water quality sensitivity to climate variability and its influencing factors in four Lake Erie watersheds. Journal of Environmental Management, 325, 116449.

Goodspeed, R., Wang, R., Lizundia, C., Du, L., & Jaipuria, S. (2022). Incorporating water quality into land use scenario analysis with random forest models. Environment and Planning B: Urban Analytics and City Science, 23998083221138842.

Guzman, C. B., Wang, R.*, Muellerklein, O., Smith, M., & Eger, C. G. (2022). Comparing stormwater quality and watershed typologies across the United States: A machine learning approach. Water Research, 216, 118283.

Wang, R.*, Kim, J. H., & Li, M. H. (2021). Predicting stream water quality under different urban development pattern scenarios with an interpretable machine learning approach. Science of The Total Environment, 761, 144057.

Song, Y., Wang, R.*, Fernandez, J., & Li, D. (2021) Investigating sense of place of the Las Vegas Strip using online reviews and machine learning approaches. Landscape and Urban Planning, 205, 103956.

Wang, R.*, Zhang, X., & Li, M.-H. (2019). Predicting bioretention pollutant removal efficiency with design features: A data-driven approach. Journal of Environmental Management, 242, 403–414.

Research

2023, PI, “Investigating the role of forest characteristics in mitigating climate change effects on water quality and fish community composition”. $138,000, USDA NIFA McIntire-Stennis. Collaborate with Karen Alof and Bill Curie

2022, PI, IRISE: “Intersecting Research Ideas towards Sustainable Environments-- Improving Built Environment Outcomes in the Face of Increasing Chemical and Pathogen Exposures”. $50,000, Bold Challenges Team Formation. Collaborate with Simone Charles (U-M public health) and Allen Burton

2022-2023, PI, “Investigating stream water contamination and prioritizing green stormwater infrastructure in the River Rouge Watershed from a socioecological perspective.” $5,000, Funded by Detroit Urban Research Center. Co-PI: Matthew Bertrand (Friends of the Rouge)

2022-2023, Co-PI, “Developing an Interdisciplinary Approach to Studying Urban Stream Water Quality.” $75,000, Funded by School for Environment and Sustainability. PI: Sara Hughes (U-M, SEAS), Co-PI: Seth Guikema (U-M, CoE)

2021-2022, PI, “Data science approach towards a socio-ecological framework for the investigation of continental urban stream water quality pattern.” $70,000, Funded by Michigan Institute for Data Science and Artificial Intelligence. Co-PI: Yang Chen (U-M, Statistics), Bill Currie (U-M, SEAS)

2021-2022, PI, “Urban water quality management towards a sustainable framework— the investigation of fine scale urban form effects on stream water quality”. $10,000, Funded by Graham Sustainability Institute Catalyst Grant Program. Co-PI: Robert Goodspeed (U-M, Taubman), Branko Kerkez (U-M, CoE), Joshua Newell (U-M SEAS), Yang Chen (U-M Statistics)

Education

Michigan State University (PhD, Environmental Design) 2018-2020

Texas A&M University (Urban and Regional Sciences) 2014-2017

Peking University (MS, Landscape Architecture) 2011-2013

Shandong University (BE, Architecture) 2006-2011

In the News
When creating more equitable urban green spaces in Michigan, the shape of green space matters
February 7, 2023

When creating more equitable urban green spaces in Michigan, the shape of green space matters

ANN ARBOR—Most Southeast Michigan residents do not have equal access to urban green spaces, according to a new University of Michigan study. Researchers at U-M’s School...

The Rouge River in Detroit, where an interdisciplinary study will utilize watershed data to understand how urban form and local policies contribute to urban water quality.
News date
October 28, 2022

Developing Water Policy Solutions that Ensure a Just and Resilient Future

Water is one of Earth’s most precious resources, and although it’s abundant, water quality and access are not always equitably distributed. The impacts of decisions made...

Landscape Architecture alum Matthew Bertrand: Rain gardens, community and Friends of the Rouge
July 14, 2022

Landscape Architecture alum Matthew Bertrand: Rain gardens, community and Friends of the Rouge

Growing up in Tucson, Arizona, may have been an unlikely start for a leading rain garden designer. But perhaps that’s what inspired Matthew Bertrand (MLA ’17) to devote...

PODS award winners: Ayumi Fujisaki-Manome (PI), Joshua Newell (PI), Runzi Wang (PI), and Bill Currie (Co-PI)
January 20, 2022

SEAS researchers well represented in 2021 Propelling Original Data Science grants

SEAS and Cooperative Institute for Great Lakes Research (CIGLR) faculty received three of the 17 Propelling Original Data Science (PODS) grants awarded by the Michigan...

SEAS Professors Runzi Wang and Joshua Newell Awarded 2021 Catalyst Grant
May 20, 2021

SEAS Professors Runzi Wang and Joshua Newell Awarded 2021 Catalyst Grant

Professors Runzi Wang and Joshua Newell of the School for Environment and Sustainability are among numerous U-M professors whose projects are being funded through the U-M...

New SEAS Faculty

Welcome New Faculty

Four faculty members with expertise in landscape architecture, environmental justice, and sustainable systems have joined SEAS. Lisa DuRussel and Runzi Wang have joined...

In the Media
01/19/2023
Runzi Wang
Jennifer Blesh
Graham Institute announces 2023 Dow Sustainability Fellows and Dow Distinguished Awards
11/06/2022
Runzi Wang
Climate change has been an underrated driver of Lake Erie algal blooms (The Toledo Blade)
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