Metro systems have become high-risk entities due to the increased frequency and severity of urban flooding. Therefore, understanding the flood risk of metro systems is a prerequisite for mega-cities’ flood protection and risk management. This study proposes a method for accurately assessing the flood risk of metro systems based on an improved trapezoidal fuzzy analytic hierarchy process (AHP). We applied this method to assess the flood risk of 14 lines and 268 stations of the Guangzhou Metro. The risk results validation showed that the accuracy of the improved trapezoidal fuzzy AHP (90% match) outperformed the traditional trapezoidal AHP (70% match). The distribution of different flood risk levels in Guangzhou metro lines exhibited a polarization signature. About 69% (155 km²) of very high and high risk zones were concentrated in central urban areas (Yuexiu, Liwan, Tianhe, and Haizhu); the three metro lines with the highest overall risk level were lines 3, 6, and 5; and the metro stations at very high risk were mainly located on metro lines 6, 3, 5, 1, and 2. Based on fieldwork, we suggest raising exits, installing watertight doors, and using early warning strategies to resist metro floods. This study can provide scientific data for decision-makers to reasonably allocate flood prevention resources, which is significant in reducing flood losses and promoting Guangzhou’s sustainable development.

Flooding is one of the most destructive natural events that severely damage the ground and inundate underground infrastructure. Subway systems in metropolitan areas are susceptible to flooding, which may be exacerbated when land subsidence occurs. However, previous studies have focused on flood risk evaluation on regional/watershed-scales and land subsidence monitoring in plains, instead of on subway flood risk evaluation and how land subsidence aggravates the flood risk in subway systems. Using the proposed risk indicators and field survey data, we present a method assessing the flood risk of metropolitan subway systems under a subsidence condition based on the fuzzy analytic hierarchy process (FAHP) combined with a geographic information system (GIS). We use the regional risk level within the 500 m buffer zone of the subway line to depict the flood risk of the subway system. The proposed method was used to evaluate the flood risk of the Beijing subway system. The results show that the flood risks of the Beijing subway show a ring-like distribution pattern—risk levels decreasing from the central urban area to the suburbs. Very high and high risks are mainly located within third and fourth ring roads, accounting for 63.58% (29.40 km²) and 63.83% (81.19 km²) of the total area. Land subsidence exacerbated the Beijing subway system’s flood risk level—the moderate to very high risk increased by 46.88 km² (16.33%), indicating that land subsidence is an essential factor affecting the flood risk level of subway systems. In addition to enhancing flood warnings, future subway flooding could be reduced by elevating the height of the stations’ exit (entrance) and installing water stop plates and watertight doors. This study is of great significance for flood warning and prevention in the Beijing subway system; it provides a theoretical basis for flood risk evaluation in other metropolitan areas.

Flooding is one of the most devastating natural events and leads to enormous and recurring loss of life, properties, and resources around the globe. With climate change and accelerating urbanization, flood disasters in China have increasingly affected the sustainable development of metropolitan areas. Risk assessment is an essential step in flood management and disaster mitigation, which provide a quantitative measure of flood risk. However, the difficulty of flood risk zoning is dealing with the uncertainty of the evaluation process and the complicated non-linear relationship between indicators and risk levels. To address this issue, a fuzzy synthetic evaluation (FSE) method based on combined weight (CW) was utilized in this paper to generate flood risk maps at a grid-scale (1 × 1 km). For the case study in the Beijing-Tianjin-Hebei metropolitan area (BTH) in China, fourteen indicators were selected to construct the flood risk assessment model based on the FSE approach integrated with ArcGIS. The research demonstrates that moderate, high, and very high risk zones are distributed in the southeast fluvial plain of the BTH area, accounting for 31.36% of the total land area. Meanwhile, low and very-low risk zones occupy 68.64% of the total land area, and are primarily located in the high plateau and mountain regions in the northwest. We analyzed the risk level of each county and proposed risk mitigation measures based on field investigations. The verified risk assessment results were spatially consistent with the historical flood disaster records and loss positions, indicating the accuracy and reliability of the risk assessment map using the FSE approach. Compared with the IPCC (Intergovernmental Panel on Climate Change) TAR (Third Assessment Report) and AR5 (Fifth Assessment Report) methods, FSE has significant advantages in handling uncertainty, complexity, and the non-linear relationship between indices and risk grades. This study provides a novel quantitative method for flood risk assessment in metropolitan areas and practical implications for urban flood management.

Built-up land in floodplains (BLF) is a driver and a disaster-bearing body of flood risk from a socio-hydrological perspective. The relationship between BLF growth and flood vulnerability is the key to understanding and managing flood risk. However, previous studies have focused more on the relationship between BLF growth and flood exposure, ignoring flood vulnerability. We examined the BLF expansion pattern (patch size and expansion type) in the North China Plain Area from 1975 to 2014 (1975–1990–2000–2014) using GIS (geographic information system)-based landscape analysis and revealed its relationship with flood vulnerability. The results show that the BLF area experienced rapid growth (288.26%) from dispersion to coalescence. Small patches dominated the number and area of BLF growth, and edge-expansion patches were the expansion type with the most area growth. We discovered that flood vulnerability was significantly correlated with the growth in small (R = 0.36, p < 0.01), edge-expansion (R = 0.53, p < 0.01), and outlying patches (R = 0.51, p < 0.01). Large patches were not significantly correlated with flood vulnerability (R = 0.18, p > 0.1), but there was a negative trend. Infilling patch growth was significantly associated with flood vulnerability over a long period (R = 0.27, p < 0.05). In addition, we suggest nature-based soft adaptations or village merging for small patches and outlying patches. Our findings have important scientific significance for adequately understanding the interplay between BLF growth and flood risk. It has practical implications for the formulation of integrated flood risk management strategy and the sustainable development of floodplains.

Anxiety and depressive symptoms are prevalent in women with polycystic ovary syndrome (PCOS), and there is a great need for culturally relevant interventions to improve anxiety and depressive symptoms in women with PCOS. The current study aimed to analyze the factors influencing body-image satisfaction, anxiety, and depressive symptoms in Chinese women with PCOS. It also aimed to clarify the association between body-image satisfaction and anxiety and depressive symptoms in women with PCOS, and whether this association was mediated by cognitive reappraisal and expressive suppression. A total of 477 women with PCOS were recruited from the Department of Gynecology and Reproductive Medicine Center of one university-affiliated tertiary hospital in China. They completed the Generalized Anxiety Disorder-7 scale, the Patient Health Questionnaire-9, the Body Image States Scale, and the Emotion Regulation Questionnaire. The study found body-image satisfaction showed significant associations with anxiety and depressive symptoms. This association was mediated by cognitive reappraisal and expressive suppression. The findings of this study offer new insights into the relationship between body image and anxiety and depressive symptoms in women with PCOS. They also emphasize the potential value of promoting body-image satisfaction and enhancing cognitive reappraisal abilities to improve the mental health of women with PCOS.