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.

Multi-stage planning of LID-GREI urban drainage systems in response to land-use changes.

Long-term planning of urban drainage systems aimed at maintaining the sustainability of urban hydrology remains challenging. In this study, an innovative multi-stage planning framework involving two adaptation pathways for optimizing hybrid low impact development and grey infrastructure (LID-GREI) layouts in opposing chronological orders was explored. The Forward Planning and Backward Planning are adaptation pathways to increase LID in chronological order based on the initial development stage of an urban built-up area and reduce LID in reverse chronological order based on the final development stage, respectively. Two resilience indicators, which considered potential risk scenarios of extreme storms and pipeline failures, were used to evaluate the performance of optimized layouts when land-use changed and evolved over time. Compared these two pathways, Forward Planning made the optimized layouts more economical and resilient in most risk scenarios when land-use changed, while the layouts optimized by Backward Planning showed higher resilience only in the initial stage. Furthermore, a decentralized scheme in Forward Planning was chosen as the optimal solution when taking costs, reliability, resilience, and land-use changes into an overall consideration. Nevertheless, this kind of reverse optimization order offers a novel exploration in planning pathways for discovering the alternative optimization schemes. More comprehensive solutions can be provided to decision-makers. The findings will shed a light on the exploration of optimized layouts in terms of spatial configuration and resilience performance in response to land-use changes. This framework can be used to support long-term investment and planning in urban drainage systems for sustainable stormwater management.

Battle of centralized and decentralized urban stormwater networks: From redundancy perspective.

Recent research underpinned the effectiveness of topological decentralization for urban stormwater networks (USNs) during the planning stage in terms of both capital savings and resilience enhancement. However, how centralized and decentralized USNs' structures with various degrees of redundancy (i.e., redundant water flow pathways) project resilience under functional and structural failure remains an unresolved issue. In this work, we present a systemic and generic framework to investigate the impact of adding redundant flow paths on resilience based on three strategies for optimal centralized versus decentralized USNs. Furthermore, a tailored graph-theory based measure (i.e., eigenvector centrality) is proposed to introduce redundant paths to the critical locations of USNs. The proposed framework is then applied to a real large-scale case study. The results confirm the critical role of layout decentralization under both functional (e.g., extreme precipitation events), and structural failure (e.g., pipe collapse). Moreover, the findings indicate that the implementation of redundant paths could increase resilience performance by up to 8% under functional failure without changing the network's major structural characteristics (i.e., sewer diameters, lengths, and storage capacity), only by leveraging the effective flow redistribution. The scheme proposed in this study can be a fruitful initiative for further improving the USNs' resilience during both planning and rehabilitation stages.

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.

Hybrid green-blue-gray decentralized urban drainage systems design, a simulation-optimization framework.

Recent studies suggested hybrid green-blue-gray infrastructures (HGBGI) as the most promising urban drainage systems that can simultaneously combine reliability, resilience, and acceptability of gray infrastructures (networks of pipes) with multi-functionality, sustainability, and adaptability of green-blue infrastructures (GBI). Combining GBI and gray measures for designing new urban drainage systems forms a nonlinear multimodal mixed integer-real optimization problem that is highly constrained and intractable. For this purpose, this study presents a simulation-optimization framework to optimize urban drainage systems considering HGBGI alternatives and different degrees of centralization. The proposed framework begins with the characterization of the site under design and drawing the base graph. Then, different layouts with different degrees of centralization are generated and hydraulically designed using a recent algorithm called hanging gardens algorithm. After introducing the feasible GBI to the model, we now perform second optimization to find the optimum distribution of GBIs in a way that minimizes total life cycle costs of GBIs and pipe networks. Finally, resiliency and sustainability of different scenarios are evaluated using several design storms that provide material for final assessment and decision-making. The performance of the proposed framework is evaluated using a real large-scale case study, a part of the city of Ahvaz in Iran. Finally, results are presented and discussed with recommendations for future studies.