Planning green infrastructure placement based on projected precipitation data

环境科学 绿色基础设施 地表径流 大洪水 防洪减灾 利用 城市化 低影响开发 水资源管理 雨水 洪水(心理学) 环境资源管理 气候变化 可持续发展 水文学(农业) 降水 环境规划 计算机科学 地理 气象学 工程类 法学 雨水管理 心理治疗师 心理学 岩土工程 考古 经济 生物 经济增长 计算机安全 生态学 政治学
作者
Olufemi A. Omitaomu,Susan M. Kotikot,Esther S. Parish
出处
期刊:Journal of Environmental Management [Elsevier]
卷期号:279: 111718-111718 被引量:19
标识
DOI:10.1016/j.jenvman.2020.111718
摘要

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.
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