Search Results (23)

Nature-Based Solutions (NBSs) offer promising pathways to enhance ecological resilience and address urban water challenges, particularly in heritage cities where conventional gray infrastructure often fails to balance environmental needs with cultural preservation. This study proposes a strategic framework for the integration of NBSs into historic urban landscapes by employing Internal–External (IE) matrix modeling and an impact–uncertainty assessment, grounded in a structured evaluation of key internal strengths and weaknesses, as well as external opportunities and threats. The Internal Factor Evaluation (IFE) score of 2.900 indicates a favorable internal environment, characterized by the multifunctionality of NBS and their ability to reconnect urban populations with nature. Meanwhile, the External Factor Evaluation (EFE) score of 2.797 highlights moderate support from policy and public awareness but identifies barriers such as funding shortages and interdisciplinary coordination. Based on these findings, two strategies are developed: an SO (Strength–Opportunity) strategy, promoting community-centered and policy-driven NBS design, and a WO (Weakness–Opportunity) strategy, targeting resource optimization through legal support and cross-sectoral collaboration. This study breaks new ground by transforming theoretical NBS concepts into actionable, culturally sensitive planning tools that enable decision-makers to navigate the unique challenges of implementing adaptive stormwater and environmental management in historically constrained urban environments. Full article

Green Stormwater Infrastructure (GSI), as a nature-based solution, has gained widespread recognition for its role in mitigating urban flood risks and enhancing resilience. Equitable spatial distribution of GSI remains a pressing challenge, critical to harmonizing urban hydrological systems and maintaining ecological balance. However, the complexity of matching GSI supply with urban demand has limited comprehensive spatial assessments. This study introduces a quantitative framework to identify priority zones for GSI deployment and to evaluate supply–demand dynamics in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) using a coupled coordination simulation model. Clustering and proximity matrix analysis were applied to map spatial relationships across districts and to reveal underlying mismatches. Findings demonstrate significant spatial heterogeneity: over 90% of districts show imbalanced supply–demand coupling. Four spatial clusters were identified based on levels of GSI disparity. Economically advanced urban areas such as Guangzhou and Shenzhen showed high demand, while peripheral regions like Zhaoqing and Huizhou were characterized by oversupply and misaligned allocation. These results provide a systematic understanding of GSI distribution patterns, highlight priority intervention areas, and offer practical guidance for large-scale, equitable GSI planning. Full article

Grass swales have emerged as a cost-effective and sustainable stormwater management solution, addressing the increasing challenges of urbanization, flooding, and water pollution. This study conducted a bibliometric analysis of 224 publications to assess research trends, key contributors, and knowledge gaps in grass swale applications. Findings highlighted the growing emphasis on optimizing hydrological performance, particularly in response to intensifying climate change and urban flood risks. Experimental and simulation-based studies have demonstrated that grass swale efficiency is influenced by multiple design factors, including vegetation type, substrate composition, hydraulic retention time, and slope gradient. Notably, pollutant removal efficiency varies significantly, with total suspended solids (TSS) reduced by 34.09–89.90%, chemical oxygen demand (COD) by 7.75–56.71%, and total nitrogen (TN) by 32.37–56.71%. Additionally, studies utilizing the Storm Water Management Model (SWMM) and TRAVA models have demonstrated that integrating grass swales into urban drainage systems can result in a 17% reduction in total runoff volume and peak flow attenuation. Despite these advancements, key research gaps remain, including cost-effective design strategies, long-term maintenance protocols, and integration with other green infrastructure systems. Future research should focus on developing innovative, low-cost swale designs, refining optimal vegetation selection, and assessing seasonal variations in performance. Addressing these challenges will enhance the scientific foundation for grass swale implementation, ensuring their sustainable integration into climate-resilient urban planning. Full article

Urban heat island (UHI) effects pose significant challenges to sustainable urban development, necessitating innovative modeling techniques to optimize urban morphology for thermal resilience. This study integrates the Pix2Pix and CycleGAN architectures to generate high-fidelity urban morphology models aligned with local climate zones (LCZs), enhancing their applicability to urban climate studies. This research focuses on eight major Chinese coastal cities, leveraging a robust dataset of 4712 samples to train the generative models. Quantitative evaluations demonstrated that the integration of CycleGAN with Pix2Pix substantially improved structural fidelity and realism in urban morphology synthesis, achieving a peak Structural Similarity Index Measure (SSIM) of 0.918 and a coefficient of determination (R²) of 0.987. The total adversarial loss in Pix2Pix training stabilized at 0.19 after 811 iterations, ensuring high convergence in urban structure generation. Additionally, CycleGAN-enhanced outputs exhibited a 35% reduction in relative error compared to Pix2Pix-generated images, significantly improving edge preservation and urban feature accuracy. By incorporating LCZ data, the proposed framework successfully bridges urban morphology modeling with climate-responsive urban planning, enabling adaptive design strategies for mitigating UHI effects. This study integrates Pix2Pix and CycleGAN architectures to enhance the realism and structural fidelity of urban morphology generation, while incorporating the LCZ classification framework to produce urban forms that align with specific climatological conditions. Compared to the model trained by Pix2Pix coupled with LCZ alone, the approach offers urban planners a more precise tool for designing climate-responsive cities, optimizing urban layouts to mitigate heat island effects, improve energy efficiency, and enhance resilience. Full article

Urban flooding presents acute challenges in heritage cities, where dense populations and valuable cultural assets coexist. While Nature-Based Solutions (NbSs) have been widely studied, their implementation in heritage cities remains underexplored due to spatial constraints and cultural sensitivities. This study develops a quantitative evaluative framework integrating the Spatial Multi-Criteria Evaluation (SMCE) and NbSs to address urban flooding in Quanzhou, a UNESCO World Heritage site. In GIS-based spatial analysis, the framework prioritizes high-risk zones by synthesizing hydrological and socio-economic factors. The analysis reveals that the Surface Runoff Coefficient (SRC) contributes 30% to urban flooding exposure, with high building congestion and elevated PM2.5 levels exacerbating risks by 17% and 16.8%, respectively. Vulnerability mapping underscores the critical role of cultural heritage, accounting for 71.1% of the vulnerability index, and highlights priority townships such as Linjiang, Kaiyuan, and Lizhong, with integrated exposure and vulnerability rates of 11.8%, 10.3%, and 9.5%, respectively. This study proposes four NbS models tailored to heritage urban landscapes, with Solution I—direct surface infiltration—identified as the most applicable, covering 170.9 ha, followed by Solution II—subterranean stormwater infiltration—at 52.3 ha. Despite limited spatial feasibility (1.3–33.5% of township areas), the framework demonstrates significant potential for integrating NbSs with existing grey infrastructure, contributing to flood risk mitigation and broader sustainability goals. The findings provide actionable insights for urban planners and policymakers, offering a replicable methodology for the deployment of NbSs in heritage-rich urban contexts worldwide. By bridging flood risk management with cultural preservation, this work advances the discourse on resilient and sustainable urban planning. Full article

For the accurate estimation of daily influent total nitrogen of sewage plants, a novel hybrid approach is proposed in this study, where a gradient-based optimization (GBO) algorithm is employed to adjust the hyper-parameters of an adaptive neuro-fuzzy system (ANFIS). Several benchmark methods for optimizing ANFIS parameters are compared, which include particle swarm optimization (PSO), gray wolf optimization (GWO), and gradient-based optimization (GBO). The prediction accuracy of the ANFIS-GBO model is evaluated against other models using four statistical measures: root-mean-squared error (RMSE), mean absolute error (MAE), and Nash–Sutcliffe efficiency (NSE), and coefficient of determination (R²). Test results show that the suggested ANFIS-GBO outperforms the standalone ANFIS, hybrid ANFIS-PSO and ANFIS-GWO methods in daily influent total nitrogen prediction from the sewage treatment plant. The ANFIS, ANFIS-PSO, ANFIS-GWO, and ANFIS-GBO models are evaluated using seven distinct input combinations to predict daily TN_inf. The results from both the testing and training periods demonstrate that these models, namely ANFIS, ANFIS-PSO, ANFIS-GWO, and ANFIS-GBO, exhibit the highest level of accuracy for the seventh input combination (Q_w, pH, SS, TP, NH₃-N, COD, and BOD5). ANFS-GBO-7 reduced the RMSE in the prediction of ANFIS-7, ANFIS-PSO-7, and ANFIS-GWO-7 by 21.77, 10.73, and 6.81%, respectively, in the test stage. Results from testing and training further demonstrate that increasing the number of parameters (NH₃-N, COD, and BOD) as input improves the models’ ability to make predictions. The outcomes show that the ANFIS-GBO model can potentially be suggested for the daily prediction of influent total nitrogen (TN_inf) in full-scale wastewater treatment plants. Full article

This study addresses the route scheduling problem for the heterogeneous robotic delivery system (HRDS) that perform delivery tasks in an urban environment. The HRDS comprises two distinct types of vehicles: an unmanned ground vehicle (UGV), which is constrained by road networks, and an unmanned aerial vehicle (UAV), which is capable of traversing terrain but has limitations in terms of energy and payload. The problem is formulated as an optimal route scheduling problem in a road network, where the goal is to find the route with minimum delivery cost and maximum customer satisfaction (CS) enabling the UAV to deliver packages to customers. We propose a new method of route scheduling based on an improved artificial bee colony algorithm (ABC) and the non-dominated sorting genetic algorithm II (NSGA-II) that provides the optimal delivery route. The effectiveness and superiority of the method we proposed are demonstrated by comparison in simulations. Moreover, the physical experiments further validate the practicality of the model and method. Full article

In this study, a multi-stage planning framework was constructed by using SWMM simulation modeling and NSGA-II and applied to optimize the layout of integrated grey–green infrastructure (IGGI) under land use change and climate change scenarios. The land use change scenarios were determined based on the master plan of the study area, with imperviousness of 50.7% and 62.0% for stage 1 and stage 2, respectively. Rainfall trends for stage 1 and stage 2 were determined using Earth-E3 from the CMIP6 model. The rainfall in stage 2 increased by 14.9% from stage 1. Based on these two change scenarios, the spatial configuration of IGGI layouts with different degrees of centralization of the layout (DCL) under the two phases was optimized, with the lowest life cycle cost (LCC) as the optimization objective. The results showed that the layout with DCL = 0 had better performance in terms of LCC. The LCC of the layout with DCL = 0 was only 66.9% of that of the layout with DCL = 90.9%. In terms of Tech-R, stage 2 had better performance than stage 1. Furthermore, the average technological resilience (Tech-R) index of stage 2 was 0.8–3.4% higher than that of stage 1. Based on the LCC and Tech-R indices of all of the layouts, TOPSIS was used to compare the performance of the layouts under the two stages, and it was determined that the layout with DCL = 0 had the best economic and performance benefits. The results of this study will be useful in exploring the spatial configuration of urban drainage systems under land use change and climate change for sustainable stormwater management. Full article

Skyrise greenery, including green roofs and vertical gardens, has emerged as an indispensable tool for sustainable urban planning with multiple ecological and economic benefits. A bibliometric analysis was used to provide a systematic review of the functions associated with skyrise greenery in urban landscapes. Key research tools, including the “Bibliometrix” R package and “CiteSpace” 6.2 R4, highlight the depth and breadth of the literature covering skyrise greenery. In 2000–2022, a total of 1474 original journal articles were retrieved. Over this period, there was an exponential increase in the number of publications, reflecting both enhanced knowledge and increasing concerns regarding climate change, the urban heat island, and urbanization. Of the total, ~58% of the articles originated from China, followed by the USA, Italy, Australia, and Canada. The research themes, such as urban heat islands, carbon sequestration, hydrology, and air quality, have been identified as the frontier in this fields. Furthermore, researchers from developed countries contributed the most publications to this domain, while developing countries, such as China, play an increasing role in the design and performance evaluation of vertical greenery. Key benefits identified in vertical green systems (e.g., green roofs and walls) include thermal regulation, sustainable water management, air-quality improvement, noise reduction, and biodiversity enhancement. In addition, several potential future research prospectives are highlighted. This review provides a comprehensive insight into exploring the pivotal role of skyrise greenery in shaping sustainable, resilient urban futures, coupled with sustainable urban planning. Full article

Nature-based solutions (NbSs) are considered to form an innovative stormwater management approach that has living resolutions grounded in natural processes and structures. NbSs offer many other environmental benefits over traditional grey infrastructure, including reduced air pollution and climate change mitigation. This review predominantly centers on the hydrological aspect of NbSs and furnishes a condensed summary of the collective understanding about NbSs as an alternatives for stormwater management. In this study, which employed the CIMO (Context, Intervention, Mechanism, Outcome) framework, a corpus of 187 NbS-related publications (2000–2023) extracted from the Web of Science database were used, and we expounded upon the origins, objectives, and significance of NbSs in urban runoff and climate change, and the operational mechanisms of NbSs (including green roofs, permeable pavements, bioretention systems, and constructed wetlands), which are widely used in urban stormwater management, were also discussed. Additionally, the efficacy of NbSs in improving stormwater quality and quantity is discussed in depth in this study. In particular, the critical role of NbSs in reducing nutrients such as TSS, TN, TP, and COD and heavy metal pollutants such as Fe, Cu, Pb, and Zn is emphasized. Finally, the main barriers encountered in the promotion and application of NbSs in different countries and regions, including financial, technological and physical, regulatory, and public awareness, are listed, and future directions for improving and strategizing NbS implementation are proposed. This review gathered knowledge from diverse sources to provide an overview of NbSs, enhancing the comprehension of their mechanisms and applications. It underscores specific areas requiring future research attention. Full article

Constructing underground reservoirs has emerged as a crucial strategy to address the shortage of fresh water in Rizhao, Shandong Province, China. However, the water quality, microbial community composition, and biogeochemical cycling of nutrients in underground reservoirs compared to raw water remain unknown. To unveil the characteristics of microbial community structures and their nitrogen cycling metabolic potential in coastal underground reservoirs, we utilized a functional gene array (GeoChip 5.0) in conjunction with high-throughput sequencing of 16S rRNA and 18S rRNA genes. Our findings indicate that the water quality in the underground reservoir exhibits a certain degree of eutrophication compared to raw water, with higher concentrations of TN, TP, NO₃⁻N, NO₂⁻-N, and Chl a, but lower concentrations of DO and NH₄⁺-N. The alpha diversity of bacterial and microeukaryotic communities was significantly lower in the underground reservoir. The bacterial community presented a stronger correlation with environmental factors than the microeukaryotic community. Regarding the relative abundance of bacterial communities, Gammaproteobacteria dominated the bacterial community in raw water, while Gammaproteobacteria and Alphaproteobacteria dominated the bacterial community in underground reservoir water. Additionally, the relative abundance of Nitrospirae was noticeably higher in the underground reservoir water. Moreover, we found significantly higher sequence abundance of the archaea Thaumarchaeota in the underground reservoir. Furthermore, our analysis revealed that, except for the amoA functional gene, which significantly increased the metabolic potential of nitrification, the metabolic potential of other microbial nitrogen functional genes was significantly reduced. This reduction may contribute to the lower concentration of NH₄⁺-N in the underground reservoir. This study provides a comprehensive understanding of the microbial community characteristics and their nitrogen cycling metabolic potential in underground reservoirs. It serves as a valuable reference for water source selection, the formulation of water quality assurance measures, and the construction and management of underground reservoirs for subsequent impounding. Full article

Some dams globally have negatively affected downstream structures. Constructing subsidiary weirs may solve this problem. This novel study focuses on investigating the parameters of seepage beneath the original structure and the proposed subsidiary weir. Conformal mapping and finite element methods are used for the analysis. The proposed subsidiary weir consists of a sloping central apron, flat aprons on both the downstream and upstream ends, and upstream and downstream sheet piles of varying depths. The existing structure also has sheet piles of different depths at its upstream and downstream ends, with an impervious layer situated at a specific depth below both the structures. The study derives equations for the simulation of the upwards pressure on both the structures, seepage rate, and exit gradient along the downstream bed and the filter at an intermediate location. Our own developed software for the analysis and a commercial software for numerical methods named Finite Element Heat Transfer (FEHT)-version-1are used to calculate these parameters. The accuracy of the analytical and numerical methods is verified by comparing the results with experimental data, which demonstrate a good level of agreement. This study also simulates the impacts of various factors, such as sheet pile configurations, the depth of the stratum beneath the structure, the ratio of effective heads, and the length of the intermediate filter. Full article

Amidst the growing urgency to mitigate the impacts of anthropogenic climate change, urban flooding stands out as a critical concern, necessitating effective stormwater management strategies. This research presents a bibliometric analysis of the literature on urban stormwater management optimization from 2004 to 2023, with the aim of understanding how the field has responded to these escalating challenges. Aiming to map the evolution and current state of the field, this study employed a methodical approach, using CiteSpace to analyze publication trends, authorship patterns, and geographical distributions, as well as keyword and citation dynamics. The findings reveal a marked increase in research activity after 2014, with significant contributions observed between 2019 and 2022. Key research themes identified include low-impact development, green infrastructure, and stormwater management, with a notable shift towards hybrid grey–green infrastructure solutions that combine traditional and ecological elements. The prevalence of terms such as ‘best management practices’ and ‘Green Roofs’ in recent publications indicates a growing emphasis on practical, case-study-based research, particularly in green infrastructure technologies like bioretention cells. These insights underscore the field’s movement towards pragmatic, multi-objective optimization frameworks with tangible applications, guiding future research directions in this increasingly complex domain. Full article

Low-Impact Development (LID) represents a cogent strategy designed to conserve or reestablish antecedent hydrological states through an array of innovative mechanisms and methodologies. Since the dawn of the millennium, LID-centric research has demonstrated a persistent upward trajectory, mainly focusing on its capacity to mitigate climate change repercussions, particularly runoff and peak flows. However, a standardized rubric and toolkit for LID evaluation remain elusive. While numerous studies have documented the hydrological and water quality benefits of LID, the impacts of climate change on its effectiveness remain uncertain due to varying spatial and temporal climate patterns. This comprehensive review examined 1355 peer-reviewed articles in English, comprising both research articles and reviews, indexed in the Web of Science up until 2022. Findings from the bibliometric analysis revealed significant contributions and emergent trends in the field. Notably, there is an increasing emphasis on performance evaluation and efficiency of LID systems, and on understanding their impact on hydrology and water quality. However, this review identified the lack of a standardized LID evaluation framework and the uncertainty in LID effectiveness due to varying climate patterns. Furthermore, this study highlighted the urgent need for optimization of current hydrological models, advancement of LID optimization, modeling, monitoring, and performance, and stakeholder awareness about LID functionality. This review also underscored the potential future research trajectories, including the need to quantify LID’s effectiveness in urban flooding and water quality management and refining LID simulation models. Cumulatively, this review consolidates contemporaneous and prospective research breakthroughs in urban LID, serving as an indispensable compendium for academics and practitioners in the discipline. Full article

This bibliometric review elucidates the emerging intersection of Internet of Things (IoT) technologies and Green Stormwater Infrastructure (GSI), demonstrating the potential to reshape urban stormwater management. The study analyzes a steadily increasing corpus of literature since 2013, pointing out considerable international collaboration. Prominent contributions originate from the United States, Canada, Italy, China, and Australia, underscoring the global acknowledgement of the potential of IoT-enhanced GSI. Diverse GSI applications such as green roofs, smart rain barrels, bioretention systems, and stormwater detention ponds have demonstrated enhanced efficiency and real-time control with IoT integration. However, existing literature reveals several challenges, notably the requirement of advanced monitoring, the development of predictive optimization strategies, and extensive scalability. Comprehensive cost–benefit analyses are also critical for the widespread acceptance of IoT-integrated GSI. Current research addresses these challenges by exploring innovative strategies such as microbial-fuel-cell-powered soil moisture sensors and large-scale RTC bioretention systems. Emphasis is also on the need for security measures against potential digital threats. Future research needs to focus on real-time data-based monitoring plans, model validation, continuous optimization, and supportive policy frameworks. As the world confronts urban development, climate change, and aging infrastructure, IoT and GSI synergism presents a promising solution for effective stormwater management and enhancement of cultural ecosystem services. Continued exploration in this promising domain is crucial to pave the way for smarter, greener urban environments. Full article