Search Results (169)

Urban flood resilience depends not only on the scale of infrastructure investment, but also on whether such investment can be translated into observable flood-mitigation outcomes. Focusing on the transformation from infrastructure response to flood outcomes, this study uses panel data for 21 prefecture-level cities in Guangdong Province from 2016 to 2022. Annual maximum monthly precipitation is used to represent rainfall pressure, stormwater pipe density to represent infrastructure scale, and the number of reported flood events to represent the outcome variable. A two-way fixed-effects Poisson pseudo-maximum likelihood (PPML) model is employed. The results show that, in the full sample, rainfall pressure is positively, but not significantly, associated with reported flood occurrence, while stormwater pipe density does not exhibit a stable negative moderating effect. The main conclusion remains broadly unchanged when alternative outcome and precipitation indicators are used, when pipe density is lagged by one period, and when a conservative sample is adopted. Extended analysis provides only limited weak negative evidence for Pearl River Delta cities, and this evidence is not robust across alternative specifications. The findings indicate that pipe length per unit of built-up area primarily reflects the scale of infrastructure provision and cannot be directly equated with the operational performance of the drainage system. By separating response inputs from outcome performance, this study reveals the conditional nature of the transformation from infrastructure scale to operational performance in urban flood resilience research and provides empirical support for a shift from infrastructure expansion toward performance-oriented and integrated governance in high-density coastal cities. Full article

The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a densely populated, highly connected coastal urban region that is exposed to typhoons, extreme rainfall, flooding, storm surges, heat-related risks, and public health emergencies. Existing studies have clarified many aspects of hazard exposure and spatial vulnerability, but evidence on how residents receive warnings, interpret risks, prepare, evacuate, and contribute to community resilience remains dispersed across disciplines and jurisdictions. This study maps the intellectual structure and thematic evolution of research on residents’ responses to urban disaster risks in the GBA. Following a PRISMA 2020-aligned identification and screening process, 144 records from the Web of Science Core Collection were manually screened. Bibliometric analysis, keyword co-occurrence analysis, a region–hazard matrix, and a BERTopic-inspired topic modelling procedure were then used to identify publication trends, disciplinary sources, spatial hazard patterns, and latent themes. The results show accelerated growth after 2020 and identify six interrelated themes: risk perception and preparedness; evacuation and shelter accessibility; urban flooding vulnerability; typhoon, storm surge, and coastal community risk; community resilience and climate adaptation governance; and health emergency response and psychosocial resilience. The review synthesises these findings into a heuristic framework linking risk information, cognitive appraisal, response action, and community resilience. The GBA is treated as an analytically informative, rather than statistically representative, case of a high-density, coastal, and multi-jurisdictional urban region. The findings suggest that resident-centred resilience planning should connect trusted and actionable warnings with inclusive digital communication, accessible protective resources, and cross-boundary coordination for compound hazards. Full article

Traditional species distribution models can identify climatically suitable areas but offer limited guidance for spatially explicit agricultural planning. In this study, we constructed a three-dimensional coupled framework of “suitability prediction–habitat quality filtering–ecological security screening” by integrating BIOMOD2 ensemble modeling, InVEST habitat quality assessment, and ecological security evaluation to identify candidate cultivation zones for Piper nigrum L. in China under climate change. Based on occurrence records and environmental variables, we simulated potential suitable habitats under current and future climate scenarios, identified key climatic drivers, and delineated candidate zones by overlaying habitat quality and ecological security levels. The results show that the current total suitable area for P. nigrum is 87.76 × 10⁴ km², with low-, moderate-, and high-suitability areas accounting for 37.28 × 10⁴ km², 25.12 × 10⁴ km², and 25.36 × 10⁴ km², respectively. Temperature seasonality and winter cold stress were identified as the dominant factors shaping the suitability pattern. Under future climate scenarios, the total suitable area shows an increasing trend, with highly suitable areas expanding toward the coastal regions of South China and the low-latitude hilly zones. After overlaying with habitat quality and ecological security, climatically suitable but ecologically fragile or intensively disturbed areas were effectively excluded, and the current candidate cultivation zones were identified as mainly concentrated in the southern Yunnan–southern Guangxi–Guangdong–Hainan coastal region. This framework enables a transition from identifying climatic suitability to collaborative climate–habitat–ecology screening, providing a scientific basis for sustainable cultivation and germplasm management of P. nigrum, and is transferable to priority cultivation area identification for other tropical cash crops. Full article

The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) comprises the two Special Administrative Regions of Hong Kong and Macao, and the nine municipalities of Guangzhou, Shenzhen, Zhuhai, Foshan, Huizhou, Dongguan, Zhongshan, Jiangmen and Zhaoqing in Guangdong Province. The GBA serves as China’s strategic maritime hub and a core engine for marine economic development. However, existing research has underexplored the structural connectivity and topological resilience of its port network from the perspective of a maritime corridor within the GBA. Therefore, using port network data from 2022 to 2023, this study identifies the core topological structure of the GBA maritime corridor and examines how resilience evolves under stochastic connection disruptions. The results show that the GBA maritime corridor exhibits an asymmetric cross-shaped backbone structure that connects domestic coastal ports with international markets (Southeast Asia, Japan, and South Korea). The network density of the GBA port system reaches 0.41258, indicating substantial connectivity that supports efficient regional and global logistics circulation. Regarding resilience level, the probability of connection disruption is the key factor that significantly affects the stability and anti-interference ability of the GBA maritime network. These findings clarify the backbone framework of the maritime corridor for marine economic development, thereby providing theoretical support for strengthening the safety and stability of the GBA maritime transport system. Full article

Forest ecological product value realization depends on ecological resource endowment, human demand, and value-conversion capacity. This study developed a dual-scale framework to assess supply–demand mismatch and value realization of forest ecological products in Guangdong Province, China, from 2012 to 2022. At the 1-km grid scale, ecological supply was represented by forest cover and forest NPP intensity, while human demand was characterized by impervious surface, summer land surface temperature, and nighttime lights. At the prefecture-level city scale, grid-based indicators were linked with forestry industry output value to evaluate realized economic value, relative value-realization efficiency, supply–realization mismatch, and city typology. OLS regression and random forest models were used to identify driving factors. Results showed that ecological supply was concentrated in mountainous areas of northern, eastern, and western Guangdong, whereas demand and value-conversion capacity were clustered in the Pearl River Delta and coastal urbanized areas. Impervious surface ratio, forest NPP intensity, GDP, and population were key predictors. These findings reveal the spatial decoupling between ecological resource spaces and value realization spaces and support differentiated forest ecological product governance. Full article

Under the background of global warming, high-tide floods pose growing threats to China’s coastal ecosystems, infrastructure and freshwater supplies. Although the occurrence of high-tide flooding events is widely recognized as being related to relative sea-level rise, tides, and residuals, the analysis and attribution of individual events remain relatively scarce. Based on tide-gauge data and numerical simulations, this study conducted a quantitative analysis of the high-tide flooding events along China’s southern coast around 19 November 2024 and provides mitigation recommendations. Results indicate that coastal sea levels south of the Yangtze River Estuary in November 2024 hit the third-highest November value on record. Sea levels south of the Taiwan Strait were 26 cm above those of normal years, with the highest monthly level since that recorded in 1980. Around 19 November, the coastal area levels coincided with the astronomical spring tide period, with the astronomical high water levels in Shanwei (Guangdong), Dongfang (Hainan), and Beihai (Guangxi) reaching 116 cm, 186 cm, and 292 cm above local mean sea level, respectively. Additionally, influenced by the outer circulation of the tropical cyclone Man-Yi and a cold-air process, an extensive coastal surge occurred, with 30~80 cm surges persisting for nearly 30 h. The combined effects of high sea levels, spring tides, and abnormal surges triggered extreme sea levels that broke historical records, with multiple stations reaching once-in-20-year levels. The contributions of astronomical tides to the extreme sea levels in Shanwei, Dongfang and Beihai were 49.5%, 69.3%, and 77.8%, respectively, while the contributions of surges were 23.6%, 6.4%, and 4.6%. This high-tide flooding event affected multiple coastal areas in Guangdong, Guangxi, and Hainan. Developing a comprehensive adaptation strategy encompassing emergency observation and early warning, risk assessment and zoning, coastal protection, coastal adaptive planning, and freshwater resources management is crucial for effectively addressing the risks of high-tide flooding events. Full article

Typhoon disaster chains—cascading sequences of hazards triggered by tropical cyclones—pose significant risks to highly urbanized coastal regions. However, quantitative modelling of their stochastic evolution, including both propagation probabilities and temporal dynamics, remains limited. This study develops a typhoon disaster chain evolution model by integrating the FBIREC (Factor-Bearing body- Incident-Response-Environment-Consequence) scenario representation framework with a Graphical Evaluation and Review Technique (GERT) stochastic network. The model is applied to the Guangdong–Hong Kong–Macao Greater Bay Area using Typhoon Mangkhut (2018) as a case study. Ten cascading event sequences are identified, and their transmission probabilities and expected durations are calculated. The model reproduces the observed event probabilities for Typhoon Mangkhut with high fidelity, with a mean absolute error of 4.31% and a coefficient of determination R² = 0.816. Power facility damage was identified as one of the most influential infrastructure nodes, exhibiting high propagation potential to multiple downstream service systems. The disaster chain unfolds across two temporal scales: short-term risks (0–48 h) and long-term risks (>48 h), providing quantifiable targets for phased emergency response planning. The proposed framework provides a methodological reference that can be adapted to other typhoon-prone regions following case-specific re-parameterization. Full article

This study develops a systematic framework for assessing the temporal dynamics of tropical cyclone (TC) risk in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) from 2013 to 2023. A unified composite index was constructed by integrating hazard, vulnerability, and mitigation capacity, allowing for the quantification of the interannual evolution of TC risk. The analysis showed that maximum storm surge and extreme precipitation drove hazard variability, with distinct peaks during the super typhoons of 2017 and 2018. In the vulnerability dimension, GDP and population density together accounted for over 50% of the total weight, and the vulnerability index shows an upward trend, though its growth slowed in 2020. Mitigation capacity improved steadily, accelerating after 2020 and partly offsetting the risk pressure from growing vulnerability. The risk index broadly mirrored the hazard index, peaking in 2018. Notably, in the two TC-free years (2014 and 2019), the risk index was higher in 2019 than in 2014, reflecting an increased vulnerability-to-mitigation ratio over the intervening period. A coherence check against three disaster loss indicators (2018–2023) yielded a correlation of r = 0.8, indicating broad consistency in the interannual patterns of the risk index and observed losses. This study provides a temporally explicit baseline for understanding recent TC risk dynamics and offers methodological support for resilience planning in coastal megaregions facing climate-related hazards. Full article

Ground-level ozone (O₃) has become a major air pollutant in China following PM_2.5, particularly in the southeastern coastal region, where the frequent interaction of typhoons and the subtropical high complicates pollution control. In this paper, spatial autocorrelation and a multiscale geographically weighted regression (MGWR) model were employed to estimate the spatiotemporal heterogeneity and driving mechanisms of O₃ in the Southeast Coastal urban agglomerations from 2015 to 2024. Temporally, the annual average O₃ concentration exhibited a fluctuating trend of an initial increase, followed by a decrease and a subsequent rebound. A bimodal monthly pattern was observed, with peaks in May–June and August–September and minima in winter. Diurnally, the concentration showed a consistent pattern of being higher in the daytime and lower at night, peaking in the afternoon, driven by solar radiation and temperature. Spatially, O₃ exhibited a distinct north–south gradient, with the highest in Jiangsu Province, followed by Shanghai, Zhejiang and Guangdong, and the lowest in Fujian. Significant spatial autocorrelation was detected, with hot spots in the Yangtze River Delta and cold spots in Fujian and adjacent areas. Seasonally, the most severe pollution with the greatest spatial heterogeneity, occurred in summer, contrasting with the uniformly low concentrations in winter. Compared with OLS and GWR, the MGWR demonstrated superior explanatory power. O₃ was jointly influenced by precursors, natural factors, and socioeconomic factors, with the influence intensity ranked as follows: NO₂ > average elevation > population density > annual precipitation> wind speed > built-up area > proportion of the secondary industry in GDP. Notably, the effects of NO₂, annual precipitation, and the proportion of the secondary industry exhibited strong spatial heterogeneity, operating at finer spatial scales. These findings provide scientific support for sustainable air quality management and region-specific O₃ control in southeastern coastal China. Full article

The humid coastal Lingnan region of South China, including the Chaoshan area of eastern Guangdong, is frequently exposed to disaster-prone weather conditions such as high humidity, typhoon-related winds, heavy rainfall, and salt-laden coastal air. These long-term environmental exposures may contribute to surface deterioration risks of architectural heritage. Located in Shantou, Yingchuan Shijia has shown five visible surface deterioration types—cracks, staining, saltpetering, plants, and spalling—under the combined influence of environmental exposure, material aging, previous disturbance, and insufficient maintenance. To address the limitations of manual inspection, this study explores a conservation-oriented intelligent workflow integrating YOLO-based detection, digital documentation, and screening-level conservation interpretation. Digital documentation used UAV imagery, mobile LiDAR scanning, measured drawings, and SketchUp-based three-dimensional modeling. The dataset was built in three stages: a 99-image preliminary dataset, where YOLOv8 showed only basic learning capability with low performance metrics, including Precision of 33.0 ± 3.0%, Recall of 28.0 ± 1.0%, mAP50 of 25.0 ± 1.0%, and mAP50-95 of 11.0 ± 1.0%; a 362-image non-augmented case-study dataset, where YOLOv8 still showed limited performance, with mAP50 of 20.0 ± 1.0% and mAP50-95 of 8.0 ± 1.0%; and a final YOLO-format case-study dataset of 2000 images after training-set-only augmentation using 11 geometric and photometric transformation methods. After augmentation, YOLOv8 mAP50 increased to 62.0 ± 2.0%. Under the same augmented-data condition, YOLOv13 showed Precision of 89.0 ± 1.0%, Recall of 77.0 ± 1.0%, mAP50 of 84.0 ± 1.0%, and mAP50-95 of 65.0 ± 1.0%, indicating relatively higher validation performance than YOLOv8. In the normalized confusion matrix, the background missed-detection values for cracks and saltpetering were 0.29 and 0.22, respectively, indicating that weak-feature and low-contrast deterioration types remained challenging. Based on YOLOv13, a mini program was developed to organize detection outputs and provide field-oriented preliminary conservation hints. Overall, this study provides a preliminary workflow linking digital collection, image-based deterioration detection, Grad-CAM visualization, and assisted field recording for the preventive conservation of Chaoshan overseas-Chinese residences in humid coastal heritage environments. Full article

Exploring the interaction relationship among multiple ecosystem services is vital for maintaining ecosystem function. However, traditional approaches are limited in their ability to: (i) characterize complex interactions and (ii) visualize the spatial connectivity of various ecosystem services delivered by social–ecological systems. To address these challenges, a framework for constructing spatial networks of multiple ecosystem services was proposed. The framework is implemented by: (i) estimating the spatial distribution of multiple ecosystem services using the InVEST model, and (ii) generating network nodes and edges with geographical attributes based on the minimum cumulative resistance model and a multiresolution segmentation method. We conducted a case study in the Guangdong–Hong Kong–Macao Greater Bay Area and examined the topological features of the spatial networks using complex network indicators. For each network, winding and multiple edges connected adjacent nodes and formed continuous linkages across the entire study area, indicating that the proposed framework is feasible for capturing the spatial connectivity of multiple ecosystem services. The different ecosystem service networks exhibited conspicuous spatial heterogeneity and generally maintained relatively high connectivity, as evidenced by their tree-like structure with winding pathways and the distribution of multi-edge nodes, indicating that each ES was predominantly connected with multiple other ecosystem services. Meanwhile, nodes with high values of degree centrality and clustering coefficient were mainly concentrated in coastal and mountainous regions. This study advances the representation of complex interactions among multiple ecosystem services from a spatial perspective, thereby facilitating a deeper understanding of the interaction mechanisms underlying ecosystem functioning. Full article

Located in the northern South China Sea (SCS), the Guangdong Sea areas exhibit a highly complex hydrodynamic structure driven by the combined effects of tides, monsoons, and offshore current systems, serving as a core region for China’s marine economy and offshore engineering. Although the Regional Ocean Modeling System (ROMS) is widely applied in current simulations, its accuracy is often constrained by the inadequate adaptability of its parameterization schemes to the regional environment. Furthermore, systematic parameter optimization tailored to this specific domain remains scarce. To address these limitations, this study conducts an observation-driven parameter optimization for surface current simulations in the western Guangdong Sea areas, aiming to enhance the reliability of hydrodynamic simulations and forecasting. A three-dimensional ROMS hydrodynamic model was employed to systematically design 18 physical parameterization experiments. The model’s performance was rigorously evaluated against 26 h continuous in situ current measurements from four observation stations, utilizing statistical metrics including the correlation coefficient (R), root mean square error (RMSE), Taylor diagrams, and the MMS standardized evaluation. The results indicate that the Mellor–Yamada vertical mixing scheme yields the optimal regional adaptability. For horizontal diffusion, the biharmonic scheme outperforms the Laplacian approach. Regarding bottom friction, the logarithmic formulation demonstrates superior accuracy compared to the quadratic and linear schemes, with the latter proven unsuitable for this region. A comprehensive evaluation identifies the ‘MY–Biharmonic–Logarithmic’ combination as the optimal parameterization configuration for the western Guangdong Sea areas. This study establishes an adaptable ROMS parameterization framework for the western Guangdong Sea areas and elucidates the influence mechanisms of key physical parameters on simulation outcomes. These findings not only provide high-precision hydrodynamic support for short-term pollutant dispersion forecasting, and disaster mitigation in this region but also offer valuable methodological references for numerical modeling in the broader SCS and analogous complex coastal environments. Full article

It is crucial to evaluate the spatio-temporal dynamics of habitat quality, which is highly sensitive to land use change. Sea-level rise and rapid urbanization are major driving forces of this change, yet their coupled impacts on future habitat quality remain poorly quantified, particularly in highly urbanized coastal regions such as the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). This study develops an integrated framework combining the Dyna-CLUE (Dynamic Conversion of Land Use and its Effects) model and SLAMM (Sea Level Affecting Marshes Model), incorporating local sea-level rise data and climate projections under the SSP3–7.0 scenario to simulate land use transitions and their impacts on coastal land use patterns and habitat quality across short-, medium-, and long-term periods. The results indicate that (1) by the end of the 21st century, accelerated urban expansion is projected to dominate land use change, with associated declines in habitat quality; (2) sea-level rise exerts heterogeneous effects on coastal wetlands, with wetland area increasing by 3232 ha between 2020 and 2050, followed by a decrease of 4110 ha by 2100, potentially contributing to habitat degradation; and (3) between 2020 and 2100, the proportion of lower-grade habitats will increase from 14.59% to 27.60%, whereas higher-grade habitats will decline from 5.49% to 4.47%. These findings highlight the need to regulate urban expansion, accommodate coastal wetland migration, and prioritize the conservation of high-quality habitats. The proposed framework provides a context-specific analytical approach for scenario-based assessment of land use management under combined urbanization and climate change pressures. Full article

Identifying and optimizing core factor configurations for anchorage operational safety under typhoon scenarios is critical to enhancing anchorage operational resilience and sustainable port development. This study develops a complementary hybrid SEM–fsQCA framework: key factors are identified via literature review and expert interviews; SEM quantifies factor correlations and contribution weights and corrects expert-evaluated anchorage capacity; six core factors are extracted, three typhoon types (heavy-rainfall, strong-wind, complex-track) are defined, and a coupled anchorage–typhoon case dataset is constructed. Subsequently, fsQCA performs necessary condition analysis and identifies causal configurations driving safety effectiveness. Based on these configurations, we establish a dynamic three-tier risk classification framework for refined anchorage management. Validated using 36 coupled cases (12 anchorages × 3 typhoon types) from Huizhou Port, a core hub in the Guangdong–Hong Kong–Macao Greater Bay Area, this framework enables adaptive vessel traffic scheduling throughout the entire typhoon cycle through dynamic tiered management. The proposed “identification-intervention-feedback” closed-loop governance model delivers theoretical rigor and operational implementation ability for coastal port typhoon risk mitigation. Full article

Coastal waters of eastern Guangdong are important fishing grounds and ecologically sensitive areas in the northern South China Sea, where nekton communities are increasingly affected by environmental heterogeneity and human activities. However, systematic studies on the spatial differentiation and driving mechanisms of nekton communities in this region remain insufficient. This study aimed to clarify the community structure, diversity distribution characteristics, and key driving environmental factors of nekton in the coastal waters of eastern Guangdong, and thereby provide scientific support for an ecological health assessment and sustainable utilization of fishery resources in this region. Based on bottom-trawl survey data from 19 stations in the coastal waters of eastern Guangdong, northern South China Sea, this study systematically analyzed the species composition, dominant species, and diversity distribution pattern of nekton and their correlations with environmental factors using methods including the Index of Relative Importance, Alpha diversity indices, Beta diversity indices, and redundancy analysis. A total of 119 nekton species belonging to three phyla, four classes, 14 orders, and 56 families were collected. Among them, there were 79 fish species (accounting for 66.39%), 36 crustacean species (30.25%), and four cephalopod species (3.36%). The dominant species were Trachypenaeus curvirostris and Portunus sanguinolentus (IRI ≥ 1000). Wilcoxon’s test showed that there were significant differences in the Shannon–Wiener index, Gini–Simpson index, and Pielou’s evenness between the nearshore and offshore groups, while no significant regional difference was observed in the richness index. Cluster analysis, based on the Bray–Curtis distance, divided the 19 stations into five clusters, with significant differentiation in species composition and functional structure within the nearshore group. RDA results indicated that environmental factors collectively explained 99.66% of the variation in community structure. Particulate Inorganic Carbon (PIC), Phosphate (PO₄³⁻), Distance to Port, Summer Maximum Chlorophyll-a (Chl-a), and Total Suspended Matter (TSM) were identified as the key driving factors. The coastal waters of eastern Guangdong boast rich nekton species, with significant differences in community structure between nearshore and offshore areas. The heterogeneity of the natural environment and human activity disturbances jointly shape the nekton diversity pattern in this region. The research results can provide a theoretical basis for regional marine ecological protection and fishery resource management. Full article