气候变化领域集成服务门户(CCPortal): Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series

CCPortal

DOI	10.1016/j.watres.2023.119720
	Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series
	Wang, Mo; Liu, Ming; Zhang, Dongqing; Qi, Jinda; Fu, Weicong; Zhang, Yu; Rao, Qiuyi; Bakhshipour, Amin E.; Tan, Soon Keat
发表日期	2023
ISSN	0043-1354
EISSN	1879-2448
卷号	232
英文摘要	Climate change has led to the increased intensity and frequency of extreme meteorological events, threatening the drainage capacity in urban catchments and densely built-up cities. To alleviate urban flooding disasters, strategies coupled with green and grey infrastructure have been proposed to support urban stormwater management. However, most strategies rely largely on diachronic rainfall data and ignore long-term climate change impacts. This study described a novel framework to assess and to identify the optimal solution in response to uncertainties following climate change. The assessment framework consists of three components: (1) assess and process climate data to generate long-term time series of meteorological parameters under different climate conditions; (2) optimise the design of Grey-Green infrastructure systems to establish the optimal design solutions; and (3) perform a multi-criteria assessment of economic and hydrological performance to support decision-making. A case study in Guangzhou, China was carried out to demonstrate the usability and application processes of the framework. The results of the case study illustrated that the optimised Grey-Green infrastructure could save life cycle costs and reduce total outflow (56-66%), peak flow (22-85%), and TSS (more than 60%) compared to the fully centralised grey infrastructure system, indicating its high superior in economic competitiveness and hydrological performance under climate uncertainties. In terms of spatial configuration, the contribution of green infrastructure appeared not as critical as the adoption of decentralisation of the drainage networks. Furthermore, under extreme drought scenarios, the decentralised infrastructure system exhibited an exceptionally high degree of removal performance for non-point source pollutants.
英文关键词	Urban stormwater management; Green infrastructure; Coupled Grey-Green system; Climate change; Regional climate model; Antecedent dry days
语种	英语
WOS研究方向	Engineering, Environmental ; Environmental Sciences ; Water Resources
WOS类目	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000967724600001
来源期刊	WATER RESEARCH
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/280397
作者单位	Guangzhou University; Guangzhou University; Guangdong University of Petrochemical Technology; National University of Singapore; Fujian Agriculture & Forestry University; University of Kaiserslautern; Nanyang Technological University; National University of Singapore
推荐引用方式 GB/T 7714	Wang, Mo,Liu, Ming,Zhang, Dongqing,et al. Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series[J],2023,232.
APA	Wang, Mo.,Liu, Ming.,Zhang, Dongqing.,Qi, Jinda.,Fu, Weicong.,...&Tan, Soon Keat.(2023).Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series.WATER RESEARCH,232.
MLA	Wang, Mo,et al."Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series".WATER RESEARCH 232(2023).