Enhanced resilience in urban stormwater management through model predictive control and optimal layout schemes under extreme rainfall events.
Optimizing the layout of urban stormwater management systems is an effective method for mitigating the risk of urban flooding under extreme storms. However, traditional approaches that consider only economic costs or annual runoff control rates cannot dynamically respond to the uncertainties of extreme weather, making it difficult to completely avoid large accumulations of water and flooding in a short period. This study proposes an integrated method combining system layout optimization and Model Predictive Control(MPC)to enhance the system's resilience and effectiveness in flood control. An optimization framework was initially built to identify optimal system layouts, balancing annual average life cycle cost (AALCC) and resilience index. The MPC was then applied to the optimal layout selected using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, aiming to alleviate inundation cost-effectively. The adaptability of MPC to varying sets of control horizons and its efficacy in managing the hydrograph and flood dynamics of urban drainage system were examined. Conducted in Yubei, Chongqing, this study revealed patterns in optimal layout fronts among various extreme design rainfalls, showing that peak position rate and return period significantly influence system resilience. The contribution of MPC to the optimal system layout was particularly notable, resulting in improved instantaneous and overall flood mitigation. The application of MPC increased the resilience index by an average of 0.0485 and offered cost savings of 0.0514 million yuan in AALCC. Besides, our findings highlighted the importance of selecting an optimal set of control horizons for MPC, which could reduce maximum flood depth from 0.43m to 0.19m and decrease conduit peak flow by up to 14% at a flood-prone downstream location.
Chen T
，Chen L
，Shao Z
，Chai H
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Multi-objective optimization methodology for green-gray coupled runoff control infrastructure adapting spatial heterogeneity of natural endowment and urban development.
Cost-effective runoff control scheme drafting involves localization, multi-sector coordination, and configuration of multifunctional infrastructures. Numerous independent variables, parameters, weights, and objectives make runoff control optimization quantitatively arduous. This study innovatively proposed a multi-objective optimization methodology for green-gray coupled runoff control infrastructure adapting spatial heterogeneity of natural endowment and urban development. The quantitative methods of multi-objective evaluation, hydrological feature partition, and pressure-adapted multi-objective weight assignment were proposed. Remote sensing inversion of water quality, hydrological model simulation (using SWAT and SWMM software), landscape pattern index calculation, life cycle cost (LCC), life cycle assessment (LCA) on ecological impact, and NSGA-II optimization algorithm were applied. Wuhan, the most water-sensitive city in China, was studied as a case. Runoff control function (RCF), capital investment (CI), and ecological return on investment (EROI) served as optimized objectives. High, medium, and low built-up regions in Wuhan urban development planning district were extracted by topographic factors and landscape patterns, which comprised 28, 34, and 38% of the case area, respectively. Three corresponding hydrological models were then built to illustrate distinct runoff control cost-efficiency in each region. Pressure distributions on runoff control, economic constraints, and ecological resource scarcity were quantitatively evaluated. And four pressure zones were clustered, which occupied 36, 29, 16, and 19% of the case area, respectively. Then the zonal weighted optimization decision-making matrix (with 3 hydrological models and 5 wt) was established by overlaying the pressure zone and built-up zone. In high, medium, and low built-up regions, optimized solutions reduced annual runoff volume by 86, 82%, and 77%The average runoff investments per square meter of impervious underlying surface in high, medium, and low built-up regions were 34.2, 18.7, and 7.9 RMB yuan, respectively. Medium and low built-up regions may only need 55 and 23% of the high built-up region for the unitary impervious underlying surface to balance runoff control and ecological benefits. Runoff control and financial utilization efficiency enhance with hydrological differentiation zones. Thus, the optimization solutions are zonal adaptive, refined, comparable, replicable, and implementable.
Liu Z
，Han Z
，Shi X
，Liao X
，Leng L
，Jia H
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Integrated assessments of green infrastructure for flood mitigation to support robust decision-making for sponge city construction in an urbanized watershed.
Green Infrastructure (GI) has become increasingly important in urban stormwater management because of the effects of climate change and urbanization. To mitigate severe urban water-related problems, China is implementing GI at the national scale under its Sponge City Program (SCP). The SCP is currently in a pilot period, however, little attention has been paid to the cost-effectiveness of GI implementation in China. In this study, an evaluation framework based on the Storm Water Management Model (SWMM) and life cycle cost analysis (LCCA) was applied to undertake integrated assessments of the development of GI for flood mitigation, to support robust decision making regarding sponge city construction in urbanized watersheds. A baseline scenario and 15 GI scenarios under six design rainfall events with recurrence intervals ranging from 2-100 years were simulated and assessed. Model simulation results confirmed the effectiveness of GI for flood mitigation. Nevertheless, even under the most beneficial scenario, the results showed the hydrological performance of GI was incapable of eliminating flooding. Analysis indicated the bioretention cell (BC) plus vegetated swale (VS) scenario was the most cost-effective GI option for unit investment under all rainfall events. However, regarding the maximum potential of the implementation areas of all GI scenarios, the porous pavement plus BC + VS strategy was considered most reasonable for the study area. Although the optimal combinations are influenced by uncertainties in both the model and the GI parameters, the main trends and key insights derived remain unaffected; therefore, the conclusions are relevant regarding sponge city construction within the study area.
Mei C
，Liu J
，Wang H
，Yang Z
，Ding X
，Shao W
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ResearchGate
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钛学术
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