Abstract
Continued urbanization has led to tremendous changes on the landscape. These changes have exacerbated the effects of extreme climatic events such as flooding because of constrained water infiltration and increased surface flow. Typical runoff control measures involve sophisticated gray infrastructure that guide excess surface flow into storage and disposal sites. In a dynamic climate system, these measures are not sustainable since they cannot be easily modified to accommodate large volumes of runoff. Green Infrastructure (GI) is an adaptable technique that can be used to minimize runoff, in addition to offering an array of additional benefits (urban heat regulation, aesthetics, improved air quality etc.). Strategic placement of GI is key to achieving maximum utility. While physical site characteristics play a major role in determining suitable GI placement sites, knowledge of future precipitation patterns is crucial to ensure successful flood mitigation. In this paper, suitable GI sites within the city of Knoxville, Tennessee, were determined based on potential impact of an extreme flood event as indicated by site characteristics. Then, the relative potential likelihood of a flood event was determined based on projected precipitation data and knowledge of existing flood zones. By combining potential impact with likelihood information, low, medium, and high priority GI implementation sites were established. Results indicate that high priority sites are in the central parts of the city with priority decreasing outward. The GI prioritization scheme presented here, offers valuable guidance to city planners and policy makers who wish to exploit the GI approach for flood mitigation.
Original language | English |
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Article number | 111718 |
Journal | Journal of Environmental Management |
Volume | 279 |
DOIs | |
State | Published - Jan 15 2021 |
Funding
The authors thank Linda Sylvester, Thomaz Calvahaes, Michele Thorton, Rui Mei and Parul Kaushal for their help with some of the data. The authors also thank Erin Gill and Jim Hagerman of City of Knoxville for their support of the Urban-CAT project. The authors would like to acknowledge the financial support for this research from the U.S. Government for Oak Ridge National Laboratory's Laboratory Directed Research and Development (LDRD) project number 7451. This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). The authors thank Linda Sylvester, Thomaz Calvahaes, Michele Thorton, Rui Mei and Parul Kaushal for their help with some of the data. The authors also thank Erin Gill and Jim Hagerman of City of Knoxville for their support of the Urban-CAT project. The authors would like to acknowledge the financial support for this research from the U.S. Government for Oak Ridge National Laboratory's Laboratory Directed Research and Development (LDRD) project number 7451. This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ).
Funders | Funder number |
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DOE Public Access Plan | |
US Department of Energy | |
U.S. Department of Energy | |
Laboratory Directed Research and Development | 7451, DE-AC05-00OR22725 |
Keywords
- Climate change adaptation
- Downscaling
- Floods
- Green infrastructure
- Projected precipitation