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 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.

Supply-Demand Evaluation of Green Stormwater Infrastructure (GSI) Based on the Model of Coupling Coordination.

The rational spatial allocation of Green Stormwater Infrastructure (GSI), which is an alternative land development approach for managing stormwater close to the source, exerts a crucial effect on coordinating urban development and hydrological sustainability. The balance between the supply and demand of urban facilities has been an influential standard for determining the rationality of this allocation. However, at this stage, research on evaluating planning from the perspective of supply-demand in GSI is still limited. This study proposed an evaluation method for assessing supply-demand levels in GSIs in Guangzhou, China, using the coupling coordination model consisting of Coupling Degree (CD) and Coupling Coordination Degree (CCD). Furthermore, the spatial distributions of supply-demand balance and resource mismatch were identified. The results indicated that the supply and demand levels of GSI exhibited significant spatial differences in distribution, with most streets being in short supply. The GSI exhibited a high CD value of 0.575 and a poor CCD value of 0.328, implying a significant imbalance in facility allocation. A lot of newly planned facilities failed to effectively cover the streets in need of improvement, so it became essential to adjust the planning scheme. The findings of this study can facilitate the decision-makers in assessing the supply-demand levels in GSI and provide a reference of facility allocation for the sustainable construction of Sponge City.

Designing coupled LID-GREI urban drainage systems: Resilience assessment and decision-making framework.

As flooding risks rise in urban areas, research suggests combining low impact development (LID) and grey infrastructure (GREI) in urban drainage systems. Several frameworks have been proposed to plan such coupled systems, but there is not a comprehensive framework to assess their resilience under diverse failure scenarios and sources of uncertainty. This study proposes a framework which considers both technological and operational resilience. Technological resilience has to do with the performance of the system under extreme loads. Operational resilience has to do with the performance and long-term efficiency of the system after structural damage or degradation, using appropriate probability distributions to quantify the likelihood of failures. The proposed framework is based on an optimization and multi-criteria decision-making platform. It improves on previous research, which lacked consideration of uncertainty in resilience over the life span. We also apply the proposed framework to a real-world test case, and find that in a high-density urban area, a coupled system is more cost-effective than GREI alone. Furthermore, decentralized systems with greater flexibility show significantly better technological and operational resilience. The proposed framework can better support decision-making for planning robust and cost-effective urban drainage systems, particularly in highly urbanized areas.