CN 11-5366/S     ISSN 1673-1530
“风景园林,不只是一本期刊。”
黄海静,马金辉,杨雨飞.山地城市高温热浪灾害空间识别与风险评估:以重庆市为例[J].风景园林,2024,31(8):1-9.
引用本文: 黄海静,马金辉,杨雨飞.山地城市高温热浪灾害空间识别与风险评估:以重庆市为例[J].风景园林,2024,31(8):1-9.
HUANG H J, MA J H, YANG Y F. Spatial Identification and Risk Assessment of High-Temperature Heat Wave Disasters in Mountain Cities: A Case Study of Chongqing[J]. Landscape Architecture, 2024, 31(8): 1-9.
Citation: HUANG H J, MA J H, YANG Y F. Spatial Identification and Risk Assessment of High-Temperature Heat Wave Disasters in Mountain Cities: A Case Study of Chongqing[J]. Landscape Architecture, 2024, 31(8): 1-9.

山地城市高温热浪灾害空间识别与风险评估——以重庆市为例

Spatial Identification and Risk Assessment of High-Temperature Heat Wave Disasters in Mountain Cities: A Case Study of Chongqing

  • 摘要:
    目的 以重庆市为代表的山地城市高温热浪问题突出,对其风险进行准确识别与科学评估是增强城市韧性和气候适应性的重要途径。
    方法 采集社会经济、地理信息和人口数据,识别高温热浪风险要素,构建以“危险性—山地城市暴露度—脆弱性”为框架的山地城市高温热浪风险评估体系,并选择重庆市2018年7—9月典型高温热浪事件展开评估。
    结果 极高和高风险区县都分布在中心城区以内,其高温热浪平均风险水平超出中等级风险区的2倍以上,由危险性和暴露度共同主导,越靠近中心,综合风险越高;危险性与暴露度都呈“近高远低”的空间分布特征,脆弱性空间分布特征则为“近低远高”;危险性较小的区县往往收入、医疗、教育水平有限,脆弱性明显高于中心城区;根据高温热浪风险主导因子的不同,以“局地优化、区域互补”为思路,提出山地城市热灾害风险应对策略与规划建议。
    结论 完善了风景园林应对气候变化的策略体系,推动构建健康、安全、舒适的城市人居环境,为落实山地城市气候韧性发展规划提供理论支持与指导。

     

    Abstract:
    Objective This research focuses on addressing the increasingly severe issue of extreme urban heat, driven by climate change, both globally and within China. Recent temperature records highlight the urgent need to understand and mitigate impacts of heat waves. The Synthesis Report of the Sixth Assessment Report declares a red warning against global climate change, signifying the most perilous stage of climate change, with 18 out of 31 “planetary vital signs” surpassing historical records. The increase in global temperature in the last 50 years has exceeded the total increase over the previous 2,000 years, making the last seven years the hottest on record. While international efforts have initiated risk assessments for heat waves, previous research in China primarily focuses on spatiotemporal analyses based on meteorological data. Recent research has integrated multiple data sources and socio-economic indicators. However, most assessments are conducted regionally, neglecting intricate risk features within urban areas and precise resource allocation guidance. Moreover, research at the county level in China mainly centers on eastern plain cities, overlooking the unique challenges faced by southwestern mountain cities, known for their complex topography and ecosystems, resulting in higher heat wave risks. Chongqing, situated in the upper Yangtze River region, is a typical mountain city notorious for heat waves.
    Methods To establish a comprehensive risk assessment system for heat waves in mountain cities, this research employs a risk index model. The approach includes the following steps: Firstly, analyze the fundamental causes of heat wave disasters to understand their mechanisms; secondly, identify risk elements of heat waves, and define and quantify assessment factors to construct integrated assessment indicators; lastly, quantify heat wave risks using a quantitative method to establish a comprehensive risk assessment system for mountainous urban areas. This assessment system is based on the disaster risk assessment framework from the Synthesis Report of the Fifth Assessment Report, which additionally incorporate factors specific to mountainous urban areas such as elevation and terrain variation to accurately reflect its risk characteristics. Notably, the “exposure” factor has been transformed as “mountain city exposure” to enhance its specificity and guidance.
    Results Heat wave risks in Chongqing exhibit significant regional disparities, influenced by varying levels of urbanization. Hazardousness analysis reveals a distribution trend of “higher risk in the west and lower risk in the east” and “higher risk closer to the city center”. Urbanization-related factors, such as artificial surface, high population density, and urban heat island effect, are major contributors to increased hazardousness. Exposure analysis emphasizes high exposure in the central urban area due to increased population density and building coverage, making it more susceptible to heat waves. Key factors dominating exposure include population density, building density, and vegetation coverage. The central urban area exhibits lower vulnerability due to higher income and education level as well as better medical facilities. Conversely, the northeastern and southeastern regions, farther from the city center, experience higher vulnerability due to poorer socioeconomic conditions. To mitigate heat wave risks, the concept of “local optimization and regional complementarity” is proposed. Specific strategies address both intra-regional and inter-regional aspects, solving primary issues while leveraging the advantages of surrounding low-risk areas. For hazardousness-dominated regions, it is advisable to implement emergency plans, adopt long-term measures to address heat wave intensity and frequency, improve heat wave warnings, and strengthen energy systems. For exposure-dominated regions, it is recommended to provide cooling shelters, create cool communities through urban design, and expand urban functions to low-exposure areas. For vulnerability-dominated regions, it is crucial to strengthen social security, enhance care mechanisms for vulnerable populations, and develop the elderly care industry. Additionally, it is important to utilize education and medical resources from the central urban area to disseminate knowledge and provide medical assistance, while also improving living conditions for the elderly.
    Conclusion This research constructs a risk assessment system for heat waves in mountain cities, and maps the spatial distribution of heat risk levels and driving factors. Overall, the strategy system for landscape architecture has been improved in response to climate change, promoting healthier, safer, and more comfortable environments. However, there are some limitations: 1) The scale of urban heat wave risk assessment is mostly concentrated at the city and district levels. Due to the lack of detailed high-temperature data at the subdistrict level from the Chongqing Meteorological Bureau, more refined analysis at the subdistrict level has not yet been conducted. In the future, with improved demographic, meteorological, and socioeconomic data, and the application of technologies such as drone and airship remote sensing, it may be possible to study the spatiotemporal distribution characteristics and risk assessment of heat waves at the subdistrict and community levels; 2) integrating climate models like WRF, ENVI-met, and Fluent will advance the application of climate-resilient landscape architecture techniques in vegetation, terrain, water body, and building. Establishing a strategy system to enhance green infrastructure from the smaller block scale to the larger regional scale will provide a more scientific basis for the construction of climate-resilient cities in China.

     

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