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SMPSS GI Assessment
Green infrastructure (GI) is widely recognized for reducing risk of flooding, improving water quality, and harvesting stormwater for potential future use. GI can be an important part of a strategy used in urban planning to enhance sustainable development and urban resilience. However, existing literature lacks a comprehensive assessment framework to evaluate GI performance in terms of promoting ecosystem functions and services for social-ecological system resilience. We propose a scenario-based planning support system to assess the capacity of urban resilience by using a robust indicator set consisting of quantitative and qualitative measurements. Green Infrastructure in Urban Resilience Planning Support System (GIUR-PSS) supports decision-making for GI planning through scenario comparisons with the urban resilience capacity index. To demonstrate GIUR-PSS, we developed five scenarios for the Congress Run sub-watershed (Mill Creek watershed, Ohio, USA) to test common types of GI (rain barrels, rain gardens, detention basins, porous pavement, and open space). Results show the open space scenario achieves the overall highest performance (GI Urban Resilience Index = 4.27/5). To implement the open space scenario in our urban demonstration site, suitable vacant lots could be converted to greenspace (e.g., forest, detention basins, and low-impact recreation areas). GIUR-PSS is easy to replicate, customize, and apply to cities of different sizes to assess environmental, economic, and social benefits provided by different types of GI installations.
Additional data described in the manuscript are available through identified data sources indicated therein.
This dataset is associated with the following publication:
Fu, X., M. Hopton, and X. Wang. Assessment of green infrastructure performance through an urban resilience lens. JOURNAL OF CLEANER PRODUCTION. Elsevier Science Ltd, New York, NY, USA, 289: 125146, (2021).
Complete Metadata
| bureauCode |
[ "020:00" ] |
|---|---|
| identifier | https://doi.org/10.23719/1519010 |
| programCode |
[ "020:096" ] |
| references |
[ "https://doi.org/10.1016/j.jclepro.2020.125146" ] |
| rights | null |