ERI: CAS- Climate: Improving green roof technologies by modeling species-specific impacts in the urban microclimate

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This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). As the benefits of green roofs become clearer, local governments are increasingly beginning to mandate or incentivize their use in new construction. Green roofs have been shown to increase stormwater retention, lower cooling costs, and mitigate the urban heat island effect, but these effects depend strongly on the implementation details. For example, certain photosynthetic succulent species, such as Sedum sp., are commonly selected for use on green roofs because of their resiliency and low maintenance requirements. However, the water use efficiency of these species ranges from six to ten times higher than that of typical herbaceous plants, leading to significant changes in rooftop temperature and runoff rates. A critical consideration of vegetation choice, substrate, and maintenance strategies is needed to advance our understanding of these technologies. The investigator seeks to build upon recent advances in plant modeling to accurately predict water use and ecosystem services of green roof scenarios as a function of vegetation type and under a variety of environmental conditions. The modelling efforts will be informed using data collected from green roof monitoring sites, including a garden green roof experiment on the Portland State University campus. It is anticipated that the work will result in modeling approaches for green roof cooling and runoff as a function of vegetation type, climate conditions, and substrate depth.While recent experimental work has shown significant impacts of vegetation type on green roof ecosystem services, the mechanisms of these impacts have not been thoroughly evaluated, making it difficult to generalize the results to different climates and vegetation types. This work will improve understating of, and ability to model, vegetation impacts on green roof cooling in a systematic manner. Results will also improve understanding of model upscaling, taking into account the inherently nonlinear response to moisture, temperature, and light conditions. This work will enable the development of tools for evaluating the appropriateness of various vegetation types in green roof settings as a function of prevailing climate conditions, aiding in the formulation of green roof policy guidelines and the valuation of appropriate green roof incentives. Data collected at the green roof site on the Portland State University campus will be made publicly accessible on a university website. In conjunction with the open-source Photo3 model of the soil-plant-atmosphere continuum, the data will be employed to develop easy-to-use, hands-on modules in a new Ecohydrology class at Portland State University. The combined data and model will be packaged together in Google Colaboratory as a teaching tool for the engineering community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.