大邑县高温热浪灾害风险区划

为了提高对四川省成都市大邑县高温热浪灾害风险区划的评估能力,为未来的精细化灾害防控提供科学依据。本研究通过收集大邑县21个气象站点2013~2023年逐日气温观测资料、基础地理数据以及社会经济数据,构建了包括致灾因子危险性、孕灾环境敏感性、承灾体易损性和防灾减灾能力在内的大邑县高温热浪灾害风险评估体系。采用了层次分析法、自然断点法以及加权综合评分法等,结合ArcGIS的空间叠加分析功能,对致灾因子(高温日数和年极端最高气温)、孕灾环境(地形高程和河网密度)、承灾体易损性(耕地比重、人均GDP和人口密度)以及防灾减灾能力(人均GDP、归一化植被指数和综合医院数量)进行了综合分析,得到了大邑县高温热浪灾害风险等级分布,并分析了不同地区风险程度的差异及可能机理。研究结果显示,大邑县高温热浪灾害风险在总体上呈现出自东向西逐渐降低的趋势。高风险区主要集中在晋原镇、苏家镇、三岔镇东部及其以东的县境地区,主要受到低海拔、夏季散热性差以及防灾减灾能力较弱等因素的影响。而低风险区则主要分布在县境以西的山区及北部地区,如西岭镇和雾山乡,受山丘影响以及孕灾环境较差和较强的防灾减灾能力使得高温灾害风险较低。In order to improve the assessment capability of heatwave disaster risk zoning in Dayi County, Chengdu City, Sichuan Province, and provide a scientific basis for future refined disaster prevention and control, this study constructed a risk assessment system for heatwave disasters in Dayi County, including hazard factors, disaster-pregnant environmental sensitivity, disaster bearing body vulnerability, and disaster prevention and mitigation capabilities. This was achieved by collecting daily temperature observation data from 22 meteorological stations in Dayi County from 2013 to 2023, as well as basic geographic and socio-economic data. The Analytic Hierarchy Process (AHP), Natural Breaks classification method, and Weighted Comprehensive Scoring method were employed, combined with the spatial overlay analysis function of ArcGIS. Comprehensive analysis was conducted on hazard factors (number of high-temperature days and annual extreme maximum temperature), disaster-pregnant environment (topographic elevation and river network density), disaster bearing body vulnerability (proportion of cultivated land, GDP per capita, and population density), and disaster prevention and mitigation capabilities (GDP per capita, Normalized Difference Vegetation Index, and the number of general hospitals). The risk level distribution of heatwave disasters in Dayi County was obtained, and the differences in risk levels in different regions and their possible mechanisms were analyzed. The results showed that the risk of heatwave disasters in Dayi County gradually decreases from east to west. The high-risk areas are mainly concentrated in the eastern part of Jinyuan Town, Sujia Town, Sancha Town, and the eastern part of the county, mainly affected by low altitude, poor heat dissipation in summer, and weak disaster prevention and mitigation capabilities. The low-risk areas are mainly distributed in the mountainous areas west of the county and northern regions, such as Xiling Town and Wushan Township. Due to the influence of hills, poor disaster-pregnant environment, and strong disaster prevention and mitigation capabilities, the risk of high-temperature disasters is relatively low.

基于GIS的南宁市高温热浪灾害风险评估与区划

运用南宁市气象数据、自然地理数据和社会经济数据,形成4个指标,分别是孕灾环境敏感性、致灾因子易发性、承灾体易损性与防灾减灾能力,借助GIS的空间分析和叠加分析功能,构建南宁市高温热浪灾害风险评估指标体系,得出南宁市1000m×1000m为单位的高温热浪灾害综合风险区划图.结果表明,南宁市的高温热浪灾害的高风险区主要集中在南宁市中心城区、江南区南部、西乡塘区与隆安县交界地带、武鸣县中南部、宾阳县和横县的中部区域.该风险区划结果基本反映了南宁市高温热浪灾害的潜在风险.

基于居民健康的城市高温热浪灾害脆弱性评价——研究进展与框架

随着全球气候变化和城市热岛效应增强,近年来城市高温热浪灾害在世界各地频繁发生,给城市居民健康和社会经济带来了极大的负面影响。目前,国内已有的高温热浪灾害研究大多关注热浪强度、发生频率、持续时间等灾害特征,以城市居民健康作为承灾体的城市高温热浪灾害脆弱性研究尚不多见,相关的评价框架和方法亟待梳理和完善。本文从高温热浪灾害脆弱性的研究主题、脆弱性框架和定量化方法三个方面系统梳理了高温热浪灾害脆弱性国内外研究进展;在广义脆弱性概念框架的基础上完善了基于"暴露—敏感—适应能力"的高温热浪灾害脆弱性评价概念框架,并梳理了相应的指标体系;强调通过自然环境、社会经济、居民感知等多角度的定性、定量数据综合表征城市居民高温热浪灾害脆弱性,以期为高温热浪灾害脆弱性评价提供理论与方法支持,并为规避高温热浪灾害风险、响应高温热浪紧急事件及适应气候变化等提供科学指引。