Planning Tool Tracks Climate Change Effect on Infrastructure

Together with the University of Colorado Boulder, the city and county of Denver has developed a stormwater planning tool that uses GIS and data forecasting to inform policymaking ahead of predicted rainfall increase.

by / March 27, 2019

MetroLab Network has partnered with Government Technology to bring its readers a segment called the MetroLab Innovation of the Month Series, which highlights impactful tech, data and innovation projects underway between cities and universities. If you’d like to learn more or contact the project leads, please contact MetroLab at info@metrolabnetwork.org for more information.

In this month’s installment of the Innovation of the Month series, we learn how Denver has partnered with the University of Colorado Boulder to develop the Green Infrastructure Decision Tool, a data-rich forecasting and action tool that assesses the effects of growth and climate change on built and natural urban surfaces. The tool can be used for citywide green infrastructure policymaking, as it has been in Denver, as well as neighborhood planning. MetroLab’s Executive Director Ben Levine spoke with Brian Muller, director of the Community Engagement, Design and Research Center (CEDaR) and Environmental Design Program (ENVD) associate professor at the University of Colorado Boulder, and Sarah Anderson, green infrastructure program manager for the City and County of Denver to learn more.

Ben Levine: Please describe the Green Infrastructure Decision Tool. Who is involved in this effort?

Brian Muller: Working with the city of Denver, a team of researchers at the University of Colorado Boulder developed an innovative, data-rich forecasting and decision-making tool that is used to project and assess high-resolution change in different types of impervious and pervious cover under climate and growth scenarios. The tool can be used for citywide green infrastructure policymaking, as it has been in Denver, as well as neighborhood planning. It also handles analysis at a parcel scale (e.g., detail of gardens, lots, etc.). The tool can be used to assess policy options ranging from landscape codes and green factor assessments to permitting based on parcel-size thresholds.  

This tool is data-intensive and relies on varied data types including GIS data collected from the city, and remote sensing data generated with innovative machine-learning-based processes. The tool can also accommodate data collected by sensors at distributed locations across the city. Output measures address both primary and secondary effects (e.g., stormwater treatment levels, inundation, tree interception and urban heat). We are currently working on more fully implementing these outputs. 

At the University of Colorado Boulder (CU Boulder), the team developing this tool was led by me and included David Kahn, landscape architect and instructor, Program in Environmental Design; Sara Tabatabaie and Mehdi Heris, doctoral students; and Ben Harden, CEDaR GIS specialist. Sarah Anderson led the program at the city and county of Denver.

Levine: Can you describe what this project focused on and what motivated the city and university to address this particular challenge?

Sarah Anderson: Denver’s water-quality goal is to have fishable and swimmable waters in our river, lakes and streams. To accomplish this, Denver needs to implement strategies that will reduce pollutant loading to our urban waterways. Since pollutant loading is directly correlated to upstream imperviousness, it’s important to understand not only current imperviousness but also future conditions. Through the partnership with CU Boulder and MetroLab, Denver better understands both the rate of change in imperviousness and the drivers of the change. This allows us to target specific green infrastructure policies, programs and capital improvements to mitigate the increases in imperviousness. 

The city’s green infrastructure strategy is focused on the implementation of both large-scale green infrastructure (parks, greenways and drainageways) and site-scale green infrastructure (stormwater planters, green gutters and permeable pavers) to mitigate the increased runoff from additional impervious surfaces. In addition to growing imperviousness, precipitation variability is expected to increase due to climate change. Currently, Denver receives about 16 inches of rainfall and 55 inches of snowfall per year, with high-intensity storms on average seven times a year that produce more than 0.5 inches of rain that can quickly overwhelm the current drainage system. Recent climate models and projections suggest that such heavy storms may increase in frequency. By utilizing green infrastructure systems, we not only improve water quality, but we also can address some of the variability in storm intensities. Green infrastructure absorbs and slows stormwater flows from storm events, which frees capacity in pipes and potentially delays or reduces localized street flooding. Infiltration through green infrastructure can also reduce the burden on gray stormwater systems by returning peak flows directly to groundwater. 

Studies have found that the incorporation of green infrastructure in highly impervious, dense environments also has a noticeable impact in reducing maximum surface temperatures. This is important because Denver faces an urban heat problem as the climate warms. These same studies found that removing green cover results in a significant increase in surface temperatures, emphasizing the need to protect existing green assets. Green infrastructure also reduces ground-level ozone through both pollutant removal and by providing a cooling effect that results in fewer emissions. This study was directly motivated by the need to know how quickly Denver’s impervious surfaces are expanding and what policies and programs are needed to address this expansion.


Street-side stormwater planters along roadways on Brighton Boulevard in Denver. Courtesy of Sarah Anderson.


Levine: Discuss how the city and university organized the partnership through which the project was designed and implemented?

Muller: The University of Colorado Boulder has implemented two different types of MetroLab projects: basic science research related to city priorities and technology needs, and applied research using classes, studios, internships and other short-term efforts to test policy and design applications. The basic research relies on funding from sources such as the National Science Foundation; the applied research relies on funding from local agencies, the university and other sources. This project employs both approaches.

More than 30 students were involved in different dimensions of this project. Faculty and doctoral students from several university programs worked on basic research problems related to city priorities (and also designed to produce publishable papers). Masters’ students in the environmental studies and engineering programs assessed policy and technical options as part of their capstone projects. Architecture and planning students created neighborhood green infrastructure plans intended to inspire community interest and help bring local and site-scale knowledge into higher-level policy discussion. Environmental science students performed measurements of infrastructure performance using sensors and other devices. By integrating faculty and student research, we created a hybrid bottom-up/top-down data model where many types of qualitative and quantitative data can be integrated and made available to decision-makers.

The MetroLab model — connecting university research activities to local policy efforts — was essential in organizing discussions between the university and city. It has helped create a foundation of ideas, common understandings and research relationships and foster a rich, ongoing collaboration.

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Topographical analysis in selected neighborhoods. Courtesy of Benjamin Harden.


Levine: I’m assuming that data collection and analysis is central to the project. Can you talk about the data strategy and share some of the project's initial findings?

Muller: This project is based on collection and processing of more than 20 spatial data sets, and analysis with both simulation and statistical methods. Data about development history and pattern and impervious cover change are employed to construct economic and demographic projections and forecast of impervious cover change. We build morphological case studies through analysis of aerial photographs, GIS data and onsite measurement, which are used to identify opportunities for best management practices. Water system data such as pipes, inlets and outlets, water planning data such as pollution levels, and water basin geography are used to project stormwater flows and development impact in priority basins. Data about urban heat patterns is collected with sensors and applied in analysis of heat effects. Lidar and remote sensing data are used to evaluate change in impervious cover, tree canopy and ground vegetation.

These data are modeled to assess patterns of impervious cover change and opportunities for green infrastructure practices including capital improvement projects, tree planting programs, bioretention and low-impact development. Policy and programmatic options are simulated as nested scenarios and analyzed at multiple scales down to the parcel. This tool also examines climate change effects focusing on shifts in seasonality of precipitation and greening, densification of urban form and heat increase.

Levine: How will the project impact city planning?

Anderson: This project has several important planning and policy implications. Denver will continue to make major large and site-scale green infrastructure investments on streets and other city-owned land. But this project allowed us to see that’s not nearly enough and that we need to utilize other policies and strategies including the redesign of the water-quality permitting program. This research is being used to assess and justify alternative permit thresholds. This project helped identify and document the benefit of stormwater treatment at smaller scales, and motivated an effort that is underway to evaluate alternative designs for treatment on small sites. From a partnership perspective, this close coordination at multiple scales from policy to neighborhood planning has been useful, and opportunities will be sought to extend and expand upon it.

Topographical analysis in selected neighborhoods. Courtesy of Benjamin Harden.


Levine: How does this project inform long-term planning and development issues in the region?

Anderson: The high rate of development and increase of impervious cover is the key finding. The city has the potential to become nearly 70 percent impervious by 2040. Moreover, the processes whereby impervious covers are generated are multiple and occur at many scales, which has significant policy and program implications. The responsibility to mitigate and reduce increases in impervious cover creation requires a shared approach between city investment and policies, the development community and Denver residents. This is based on the key finding that under existing policy, a substantial proportion of new stormwater runoff will not be treated. Unfortunately, at current development rates, the model projected that under existing policies, untreated impervious surfaces could increase by 25 percent over the next 20 years or so. New policy tools are needed to help the city avoid significant water quality and quantity problems that would be caused by this increase in the future. At the same time, these tools can be used to generate strategically located green infrastructure that addresses urban heat and other climate change impacts.  

Muller: From a technical perspective, the approach used in this project appears to be fairly versatile, and we are continuing to build the tool so that it can be applied to other types of green infrastructure-related design problems. We are continuing to conduct research on policy options and attitudes of participants in the development process and refine the method and program. We are also testing elements of the tool in places varied physical, social and policy environments and hope to be able to apply it in an additional city over the next year.

Finally, this project strengthened the continuing relationship between the city and university, and revealed multiple points of intersection between the city’s research needs and the agendas of university faculty. The work project produced real benefits. Most importantly, it helped the city address a critical research need. The university was able to support the research of two doctoral students and more than 20 masters' students and undergraduates. We generated momentum around this topic within the university, produced multiple papers and proposals, and are training a new generation of green infrastructure professionals and scholars.

About MetroLab: MetroLab Network introduces a new model for bringing data, analytics and innovation to local government: a network of institutionalized, cross-disciplinary partnerships between cities/counties and their universities. Its membership includes more than 40 such partnerships in the United States, ranging from mid-size cities to global metropolises. These city-university partnerships focus on research, development and deployment of projects that offer technologically and analytically based solutions to challenges facing urban areas including: inequality in income, health, mobility, security and opportunity; aging infrastructure; and environmental sustainability and resiliency. MetroLab was launched as part of the White House’s 2015 Smart Cities Initiative. Learn more at metrolabnetwork.org or on Twitter @metrolabnetwork.

Ben Levine Executive Director, MetroLab Network

Ben Levine is the executive director of MetroLab Network. Previously he was a policy adviser at the U.S. Department of the Treasury, where he was responsible for policy development pertaining to state and local government finance, with a focus on infrastructure policy. He worked closely with the White House’s Office of Science and Technology Policy on the organization and launch of MetroLab Network. Prior to that Ben worked at Morgan Stanley. He is a graduate of the Wharton School at the University of Pennsylvania.

 

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