Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series
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 supp...
| Main Authors: | , , , , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Online Access: | https://hdl.handle.net/10356/172051 |
| _version_ | 1826110348449546240 |
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| author | Wang, Mo Liu, Ming Zhang, Dongqing Qi, Jinda Fu, Weicong Zhang, Yu Rao, Qiuyi Bakhshipour, Amin E. Tan, Soon Keat |
| author2 | School of Civil and Environmental Engineering |
| author_facet | School of Civil and Environmental Engineering Wang, Mo Liu, Ming Zhang, Dongqing Qi, Jinda Fu, Weicong Zhang, Yu Rao, Qiuyi Bakhshipour, Amin E. Tan, Soon Keat |
| author_sort | Wang, Mo |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T02:32:56Z |
| format | Journal Article |
| id | ntu-10356/172051 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:32:56Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1720512023-11-20T08:18:16Z 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 School of Civil and Environmental Engineering Engineering::Environmental engineering Urban Stormwater Management Green Infrastructure 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. This work was supported by the National Natural Science Foundation of China [grant number 51808137], Natural Science Foundation of Guangdong Province [grant number 2019A1515010873], and Science and Technology Program of Guangzhou, China [grant number 202201010431]. 2023-11-20T08:18:16Z 2023-11-20T08:18:16Z 2023 Journal Article Wang, M., Liu, M., Zhang, D., Qi, J., Fu, W., Zhang, Y., Rao, Q., Bakhshipour, A. E. & Tan, S. K. (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, 119720-. https://dx.doi.org/10.1016/j.watres.2023.119720 0043-1354 https://hdl.handle.net/10356/172051 10.1016/j.watres.2023.119720 36774753 2-s2.0-85147863130 232 119720 en Water Research © 2023 Elsevier Ltd. All rights reserved. |
| spellingShingle | Engineering::Environmental engineering Urban Stormwater Management Green Infrastructure Wang, Mo Liu, Ming Zhang, Dongqing Qi, Jinda Fu, Weicong Zhang, Yu Rao, Qiuyi Bakhshipour, Amin E. Tan, Soon Keat Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series |
| title | Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series |
| title_full | Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series |
| title_fullStr | Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series |
| title_full_unstemmed | Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series |
| title_short | Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series |
| title_sort | assessing and optimizing the hydrological performance of grey green infrastructure systems in response to climate change and non stationary time series |
| topic | Engineering::Environmental engineering Urban Stormwater Management Green Infrastructure |
| url | https://hdl.handle.net/10356/172051 |
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