doi:10.12202/j.0476-0301.2019258井源源^{1, 2,},
方建²,
史培军^{1, 3, 4,,}
1.北京师范大学地表过程与资源生态国家重点实验室，100875，北京
2.武汉大学资源与环境科学学院，430079，湖北武汉
3.北京师范大学地理科学学部，应急管理部-教育部减灾与应急管理研究院，100875，北京
4.青海师范大学高原科学与可持续发展研究院，810016，青海西宁
基金项目:国家重点研发计划资助项目（2016YFA0602404）；国家自然科学基金创新研究群体资助项目（41621061）

详细信息

通讯作者:史培军（1959-），男，博士，教授。研究方向：环境演变与自然灾害研究. e-mail：spj@bnu.edu.cn

中图分类号:X43

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出版历程

收稿日期:2019-12-16
网络出版日期:2020-11-03
刊出日期:2020-10-31

Analysis of population exposure to extreme precipitation in Hubei Province under the climate change scenarios

Yuanyuan JING^{1, 2,},
Jian FANG²,
Peijun SHI^{1, 3, 4,,}
1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, 100875, Beijing, China
2. School of Resource and Environmental Science, Wuhan University, 430079, Wuhan, Hubei，China
3. Academy of Disaster Reduction and Emergency Management, Emergency Management Department and Ministry of Education, Beijing Normal University, 100875, Beijing, China
4. Institute of Plateau Science and Sustainable Development, Qinghai Normal University, 810016, Xining, Qinghai， China



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摘要
摘要:基于湖北省历史灾情数据构建受灾率与雨强、人均GDP的回归模型，选取RCP4.5和RCP8.5情景下的日降水数据及对应SSPs路径下的人口和GDP资料，分析了湖北省不同时期极端降水事件、人口及人口暴露度的时空分布特征及变化情况. 结果表明：受灾率与雨强、人均GDP都存在着显著的相关性（P < 0.01）。通过构建受灾率模型，使之能够更加准确地刻画人口暴露情况。湖北省的极端降水事件在空间上自东南向西北递减，且整体强度随时间变化而增加；湖北省人口总数整体东密西疏，SSP3路径始终高于SSP2；人均GDP分布由武汉向四周递减，随时间快速增长，SSP2路径下的值始终大于SSP3；湖北省极端降水人口暴露度的高值中心，随时间变化向南向东发展，同时由于人均GDP的快速增长，设防水平大幅提升，人口总量减少，暴露总量不断减少，RCP8.5情景下，极端降水人口暴露度和暴露总量始终高于RCP4.5情景，并在未来中期时差距加大.
关键词:极端降水/
典型浓度路径（RCPs）/
受灾率模型/
人口暴露/
湖北省
Abstract:Based on the historical disaster data of Hubei Province, we constructed a regression model between disaster loss rate, rainstorm intensity and Per Capita GDP. The daily precipitation data under RCP4.5 and RCP8.5 scenarios and population and GDP data under corresponding SSPs paths were selected to analyze temporal and spatial distribution characteristics and changes of extreme precipitation events, population and population exposure during different periods in Hubei Province. The results showed that: the disaster loss rate is significantly (p < 0.01) correlated with rainfall intensity and per capita GDP. By constructing a disaster loss rate model, it can evaluate population exposure more accurately. Extreme precipitation events in Hubei province were found to decrease spatially from southeast to northwest, and the overall intensity increased with time. The total population of Hubei Province is dense in the east and sparse to the west, and total number under SSP3 path was found to be always higher than SSP2 path. The per capita GDP presents a pattern of decreasing distribution from Wuhan City to the surroundings, and grows rapidly over time, the value under the SSP2 path is always higher than SSP3. The high value center of population exposure to extreme precipitation in Hubei Province was found to shift south and eastward, and due to the rapid growth of per capita GDP, the greatly increase of fortification level, the decreased total population, the total exposure population has been continuously reduced, the extreme precipitation population exposure and total exposed population under the scenario of RCP8.5 are always higher than it under RCP4.5, and the gap will continue to increase in the medium future.
Key words:extreme precipitation/
representative concentration pathways (RCPs)/
disaster lose rate model/
population exposure/
Hubei Province