Large-Scale Geospatial Analysis of Suitable Siting for Green Stormwater Infrastructure: An Open-Source Tool for Promoting Sustainability and Environmental Justice in Urban CommunitiesSource: Journal of Environmental Engineering:;2024:;Volume ( 150 ):;issue: 012::page 04024059-1DOI: 10.1061/JOEEDU.EEENG-7586Publisher: American Society of Civil Engineers
Abstract: Urbanization has led to escalating challenges in stormwater management, impacting the sustainability and resilience of urban communities worldwide. The increase in impervious surfaces and pollutants in stormwater runoff necessitates sustainable solutions. Green Stormwater Infrastructure (GSI) has emerged as an environmentally friendly approach to control runoff quantity and improve quality by emulating natural processes. However, current GSI planning lacks a comprehensive framework, especially in considering environmental justice (EJ). In light of this challenge, our study presents an open-source GSI siting tool, iPlan-GreenS2, to identify suitable GSI locations by integrating geological, environmental, and sociodemographic factors at the state level. In doing so, we identified suitable sites for 11 different GSIs in Florida based on various environmental criteria such as land use, slope, imperviousness, hydrological soil type, and groundwater elevation. Furthermore, the developed tool is designed to prioritize locations where GSIs can promote EJ by incorporating a social vulnerability index (SVI). SVI was developed based on eight environmental justice metrics including demographic data (% African American; % Indigenous People; % Asian; % Hispanic) along with socioeconomic indicators (% persons without high school diploma; % unemployed; median household income; and % in poverty). Our analysis revealed that Miami-Dade County, Broward County, and Hillsborough County have the highest number of socially vulnerable census tracts, while also having the most modeled suitable locations for GSIs, highlighting not only the feasibility but also the significant potential for widespread GSI implementation to improve existing social vulnerabilities while controlling stormwater runoff and improving runoff quality. iPlan-GreenS2 is a user-friendly and open-access tool with several key features that allows users to filter suitable GSI locations based on various factors such as the GSI type, social vulnerability status, county jurisdictional area, or land ownership. The framework of the tool proposed in this study is adaptable and can be easily applied to both smaller and larger geographical scales. iPlan-GreenS2 serves as a valuable decision-making tool for urban planners and state officials, facilitating the identification of sustainable and equitable stormwater management solutions.
|
Collections
Show full item record
contributor author | S. M. Mushfiqul Hoque | |
contributor author | Sara Kamanmalek | |
contributor author | Nasrin Alamdari | |
date accessioned | 2025-04-20T10:30:25Z | |
date available | 2025-04-20T10:30:25Z | |
date copyright | 10/9/2024 12:00:00 AM | |
date issued | 2024 | |
identifier other | JOEEDU.EEENG-7586.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4304855 | |
description abstract | Urbanization has led to escalating challenges in stormwater management, impacting the sustainability and resilience of urban communities worldwide. The increase in impervious surfaces and pollutants in stormwater runoff necessitates sustainable solutions. Green Stormwater Infrastructure (GSI) has emerged as an environmentally friendly approach to control runoff quantity and improve quality by emulating natural processes. However, current GSI planning lacks a comprehensive framework, especially in considering environmental justice (EJ). In light of this challenge, our study presents an open-source GSI siting tool, iPlan-GreenS2, to identify suitable GSI locations by integrating geological, environmental, and sociodemographic factors at the state level. In doing so, we identified suitable sites for 11 different GSIs in Florida based on various environmental criteria such as land use, slope, imperviousness, hydrological soil type, and groundwater elevation. Furthermore, the developed tool is designed to prioritize locations where GSIs can promote EJ by incorporating a social vulnerability index (SVI). SVI was developed based on eight environmental justice metrics including demographic data (% African American; % Indigenous People; % Asian; % Hispanic) along with socioeconomic indicators (% persons without high school diploma; % unemployed; median household income; and % in poverty). Our analysis revealed that Miami-Dade County, Broward County, and Hillsborough County have the highest number of socially vulnerable census tracts, while also having the most modeled suitable locations for GSIs, highlighting not only the feasibility but also the significant potential for widespread GSI implementation to improve existing social vulnerabilities while controlling stormwater runoff and improving runoff quality. iPlan-GreenS2 is a user-friendly and open-access tool with several key features that allows users to filter suitable GSI locations based on various factors such as the GSI type, social vulnerability status, county jurisdictional area, or land ownership. The framework of the tool proposed in this study is adaptable and can be easily applied to both smaller and larger geographical scales. iPlan-GreenS2 serves as a valuable decision-making tool for urban planners and state officials, facilitating the identification of sustainable and equitable stormwater management solutions. | |
publisher | American Society of Civil Engineers | |
title | Large-Scale Geospatial Analysis of Suitable Siting for Green Stormwater Infrastructure: An Open-Source Tool for Promoting Sustainability and Environmental Justice in Urban Communities | |
type | Journal Article | |
journal volume | 150 | |
journal issue | 12 | |
journal title | Journal of Environmental Engineering | |
identifier doi | 10.1061/JOEEDU.EEENG-7586 | |
journal fristpage | 04024059-1 | |
journal lastpage | 04024059-13 | |
page | 13 | |
tree | Journal of Environmental Engineering:;2024:;Volume ( 150 ):;issue: 012 | |
contenttype | Fulltext |