地球信息科学学报

地球信息科学学报 ›› 2019, Vol. 21 ›› Issue (6): 865-874.doi: 10.12082/dqxxkx.2019.180580

• 地理空间分析综合应用 • 上一篇    下一篇

顾及空间集聚程度的中国高温灾害危险性评价

张婷1,2,3,4(), 程昌秀1,2,3,4,*()   

  1. 1. 北京师范大学地理数据与应用分析中心,北京 100875
    2. 北京师范大学 环境演变与自然灾害教育部重点实验室,北京 100875
    3. 北京师范大学地理科学学部,北京 100875
    4. 北京师范大学 地表过程与资源生态国家重点实验室,北京 100875
  • 收稿日期:2018-11-14 修回日期:2019-02-25 出版日期:2019-06-15 发布日期:2019-06-15
  • 作者简介:

    作者简介：张婷（1994-）,女,内蒙古呼和浩特人,硕士生,主要从事灾害类数据分析。E-mail: zhangting_bnu@mail.bnu.edu.cn

  • 基金资助:
    国家自然科学基金面上项目(41771537)

Assessment of China's High-Temperature Hazards: Accounting for Spatial Agglomeration

Ting ZHANG1,2,3,4(), Changxiu CHENG1,2,3,4,*()   

  1. 1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    2. Key Laboratory of Environmental Change and Natural Disaster, Beijing Normal University, Beijing 100875, China
    3. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    4. Center for Geodata and Analysis, Beijing Normal University, Beijing 100875, China
  • Received:2018-11-14 Revised:2019-02-25 Online:2019-06-15 Published:2019-06-15
  • Contact: Changxiu CHENG
  • Supported by:
    National Natural Science Foundation of China, No.41771537

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摘要：

高温危险性评估是高温灾害研究的基础性工作。本研究在传统高温灾害危险性评价的基础上增加了高温空间集聚程度指标,完善了高温危险性的评价角度,考虑了高温灾害群发对高温危险性的增强作用。基于高温日数、高温强度、高温空间集聚程度对1979-2017年中国高温危险性进行了综合评价,并分析了各项指标及其年际变化速率的空间分布特征,提取出高温综合高危区及和各指标同时增强的区域。研究结果表明：① 不考虑高温空间集聚程度会造成内蒙古西部及东北部、山西北部等地的高温危险性被低估,存在4级高温危险性被低估为2级或3级;② 目前高温综合危险性最强的地区分布在新疆天山南部、湖南东部等地,表现为年平均高温日数2036 d,高温强度1.190~2.180 ℃,平均集聚程度13.390~18.710 个;③ 江苏、内蒙古甘肃交界处及四川重庆交界处等地的3项评价指标均逐年显著增强,具体表现为从1979-2017年,年平均高温日数变率0.419~0.740 天/年,高温强度变率0.30~0.42 ℃/10年,平均集聚程度变率0.250~0.390 个/年。今后这些地区可能成为高温综合危险性最高的地区。该高温危险性评价方法有助于提升高温灾害风险评估的准确性,危险性变化趋势结果有助于预估未来高温灾害的高危区。

关键词: 高温灾害, 危险性评价, 综合高温危险性指标, 空间聚集程度, 变化趋势, 中国

Abstract:

Hazardness assessment is the basis of high temperature hazard (HTH) research. The spatial aggregation of multiple extreme high temperature events will magnify the impacts of extreme events, which not only strengthen high temperature risk, but also increase the vulnerability of disaster-bearing bodies. Previous studies mainly use high temperature days and high temperature intensity to depict HTH, yet seldom consider the the spatial agglomeration of high temperature events. To address this gap, the HTH assessment in this paper integrates the traditional HTH assessment and the spatial agglomeration of high temperature events. In so doing, the evaluation of HTH is more comprehensive by accunting for the synergy effect of high temperature hazard agglomeration. Based on high temperature days, high temperature intensity, and high temperature spatial agglomeration, HTH in China from 1979 to 2017 was evaluated integratively. The spatial distribution characteristics of these indices were illustrated and their inter-annual variations were analyzed. Finally, areas with the highest integrative high temperature intensity and regions with simultaneous enhancement of the three indices were idenified separately. The results show that the strength of HTH in western and northeastern Inner Mongolia and northern Shanxi is underestimated due to the lack of consideration of high temperature spatial agglomeration, where the Grade 4 HTH is underestimated to be Grade 2 or 3. On the other hand, if HTH assessment considered only the number of high temperature days, the high temperature hazardness in most areas of Inner Mongolia, Heilongjiang, Shandong, and the northern part of western Shaxi would have been underestimated. This indicates that HTH assessment needs to account for the three indices simultaneouly. From the results of integrative assessment, for now, the most dangerous areas due to high temperature are located in southern Tianshan Mountains and eastern Hunan, where high temperature days are 20-36 days, high temperature intensity ranges from 1.190 ℃ to 2.180 ℃ and high temperature spatial agglomeration ranges from 13.390 to 18.710. From the results of inter-annual variations, all of the three indices significantly increased in the junction of Inner Mongolia and Gansu, Jiangsu, and the junction of Sichuan and Chongqing. These areas may become the most dangerous areas of high temperature hazards in the future, where from 1979 to 2017 the variability of high temperature days is 0.419-0.740 days/year, the variability of high temperature intensity is 0.30-0.42 ℃/10 years and the variability of high temperature spatial agglomeration is 0.250-0.390 per year. The proposed HTH assessment method is helpful to improve the accuracy of risk assessment of high temperature hazards, and the results of our trend analysis of these indices can help predict the high-risk areas. In addition, the method can identify the high-risk areas of each hazard factor and also the dominant factor of each high-risk area. It provides a scientific basis for targeted high temperature prevention and mitigation, as well as resource allocation over the whole China.

Key words: high temperature hazards, hazard assessment, integrative high temperature hazardness index, spatial agglomeration degree, trend analysis, China