Published In

Science of the Total Environment

Document Type

Post-Print

Publication Date

1-31-2019

Subjects

Landscape assessment, Sustainable development, Green infrastructure, Geographic information systems, Environmental justice, Urban runoff -- Management

Abstract

This study explores the spatial distribution of green stormwater infrastructure (GSI) relative to sociodemographic and landscape characteristics in Portland, OR, and Baltimore, MD, USA at census block group (CBG) and census tract scales. GSI density is clustered in Portland, while it is randomly distributed over space in Baltimore. Variables that exhibit relationships with GSI density are varied over space, as well as between cities. In Baltimore, GSI density is significantly associated with presence of green space (+), impervious surface coverage (+), and population density (−) at the CBG scale; though these relationships vary over space. At the census tract scale in Baltimore, a different combination of indicators explains GSI density, including elevation (+), population characteristics, and building characteristics. Spatial regression analysis in Portland indicates that GSI density at the CBG scale is associated with residents identifying as White (−) and well-draining hydrologic soil groups A and B (−). At both census tract and CBG scales, GSI density is associated with median income (−) and sewer pipe density (−). Hierarchical modelling of GSI density presents significant spatial dependence as well as group dependence implicit to Portland at the census tract scale. Significant results of this model retain income and sewer pipe density as explanatory variables, while introducing the relationship between GSI density and impervious surface coverage. Overall, this research offers decision-relevant information for urban resilience in multiple environments and could serve as a reminder for cities to consider who is inherently exposed to GSI benefits.

Description

© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license

DOI

10.1016/j.scitotenv.2019.01.417

Persistent Identifier

https://archives.pdx.edu/ds/psu/28027

Available for download on Sunday, January 31, 2021

Included in

Geography Commons

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