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基于自然的沿海灾害脆弱区恢复模拟——利用绿色基础设施效应

Nature-Based Restoration Simulation for Disaster-Prone Coastal Area Using Green Infrastructure Effect.

机构信息

OJEong Resilience Institute, Korea University, Seoul 02841, Republic of Korea.

Department of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Republic of Korea.

出版信息

Int J Environ Res Public Health. 2023 Feb 10;20(4):3096. doi: 10.3390/ijerph20043096.

DOI:10.3390/ijerph20043096
PMID:36833795
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9960258/
Abstract

Floods in coastal areas are caused by a range of complex factors such as typhoons and heavy rainfall, and this issue has become increasingly serious as interference has occurred in the social-ecological system in recent years. Given the structural limitations and high maintenance costs of the existing gray infrastructure, the need for a nature-based restoration plan utilizing green infrastructure has been raised. The purpose of this study is to simulate the restoration process through the quantification of green infrastructure effects along with resilience in disaster-prone coastal areas, and to present it as nature-based restoration planning. For this purpose, first, a disaster-prone area was derived from Haeundae-gu, Busan, Republic of Korea, which was affected by typhoons. In order to simulate the runoff from typhoon "Chaba" in the target area and the effects of reducing the runoff of green infrastructure, relevant data was collected and a model constructed. Finally, the effects of the green infrastructure as applied to the disaster-prone area were quantified by means of resilience and a nature-based restoration plan was presented. As a result of this study, first, the runoff reduction effect was greatest when the maximum biotope area ratio of 30% was applied to the artificial ground. In the case of the green roof, the effect was the greatest 6 h following the typhoon passing through, and the effects of the infiltration storage facility was greater 9 h following the same. Porous pavement exhibited the lowest runoff reduction effect. In terms of resilience, it was found that the system was restored to its original state after the biotope area ratio of 20% was applied. This study is significant in that it analyzes the effects of green infrastructure based upon the concept of resilience and connects them to nature-based restoration planning. Based on this, it will be provided as an important tool for planning policy management to effectively respond to future coastal disasters.

摘要

沿海地区的洪水是由台风和暴雨等一系列复杂因素引起的,近年来,由于社会-生态系统受到干扰,这个问题变得越来越严重。鉴于现有灰色基础设施的结构限制和高维护成本,需要提出一种利用绿色基础设施的基于自然的恢复计划。本研究旨在通过量化易受灾沿海地区的绿色基础设施效应和弹性,来模拟恢复过程,并将其呈现为基于自然的恢复规划。为此,首先从韩国釜山的海云台区确定了一个易受灾地区,该地区曾受到台风的影响。为了模拟目标区域的台风“查帕卡”径流和减少绿色基础设施径流的效果,收集了相关数据并构建了模型。最后,通过弹性量化了绿色基础设施在易受灾地区的应用效果,并提出了基于自然的恢复计划。本研究的结果表明,首先,当人工地面的最大生物区面积比达到 30%时,径流减少效果最大。对于绿色屋顶,在台风过境后 6 小时内效果最大,而渗透存储设施的效果在同一时间后 9 小时内更大。多孔路面的径流减少效果最低。在弹性方面,发现当生物区面积比达到 20%时,系统恢复到原始状态。本研究具有重要意义,因为它基于弹性概念分析了绿色基础设施的效果,并将其与基于自然的恢复规划联系起来。在此基础上,它将作为一种有效的沿海灾害规划政策管理工具,为未来的沿海灾害提供重要的规划决策支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/0f0fa165a8eb/ijerph-20-03096-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/2927a4b51957/ijerph-20-03096-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/72e9d8a7362d/ijerph-20-03096-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/76f47392621f/ijerph-20-03096-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/3560ee537691/ijerph-20-03096-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/88eb5ad677ff/ijerph-20-03096-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/01ba5a465468/ijerph-20-03096-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/8cd65a692167/ijerph-20-03096-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/a54ecc3d151c/ijerph-20-03096-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/e6848df73b5e/ijerph-20-03096-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/3c57b966f861/ijerph-20-03096-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/55059f721906/ijerph-20-03096-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/0d5de2b2f3d1/ijerph-20-03096-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/0f0fa165a8eb/ijerph-20-03096-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/2927a4b51957/ijerph-20-03096-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/72e9d8a7362d/ijerph-20-03096-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/76f47392621f/ijerph-20-03096-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/3560ee537691/ijerph-20-03096-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/88eb5ad677ff/ijerph-20-03096-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/01ba5a465468/ijerph-20-03096-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/8cd65a692167/ijerph-20-03096-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/a54ecc3d151c/ijerph-20-03096-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/e6848df73b5e/ijerph-20-03096-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/3c57b966f861/ijerph-20-03096-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/55059f721906/ijerph-20-03096-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/0d5de2b2f3d1/ijerph-20-03096-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99e6/9960258/0f0fa165a8eb/ijerph-20-03096-g013.jpg

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Stormwater runoff reduction simulation model for urban flood restoration in coastal area.沿海地区城市洪水恢复的雨水径流减少模拟模型
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