青海公路沿线暴雨洪涝灾害风险指数特征与模型研究

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Characteristics and model of rainstorm and flood disaster risk index along Qinghai Highway

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doi:10.12118/j.issn.1000－6060.2023.283

Abstract:

Based on daily precipitation and geographic and socioeconomic data collected from 50 national and 39 traffic meteorological stations in Qinghai Province of China from January 2012 to December 2021, this study analyzes the spatiotemporal distribution and characteristics of rainfall intensities along the highway. The analytic hierarchy process and natural breakpoint methods were applied to summarize the risk indices of rainstorms and flood disasters. These indices include the disaster-bearing environment, meteorological risk, and disaster prevention and reduction capability. By integrating these factors, a rainstorm and flood disaster risk model for a highway in Qinghai Province was developed. The key findings are as follows: (1) The spatial distribution of rainfall days along highways decreases from southeast to northwest. High-risk areas include the Xining-Tianjun section of National Highway G315 and the Xining-Ebaoling section of National Highway G227. (2) Environmental vulnerability risk gradually decreases from the southeast and northeast to the west. High-risk areas include the Qilian section of National Highway G227 and the Gonghe-Nangqian section of National Highway G214. (3) The risk of disaster body exposure is concentrated in the Minhe-Gonghe section of National Highway G109 and the Xining-Ebaoling section of National Highway G227. (4) Regions with high disaster prevention and reduction capability are mainly Xining City, Haidong City, east Haibei Prefecture, and west Haixi Prefecture. (5) The rainstorm and flood disaster risk model, categorized into five levels (lowest, low, medium, high, and higher risk), offers a practical tool for meteorological disaster risk management and provides a scientific basis for local transportation departments’ disaster prevention and relief efforts.

Key words: rainstorm and flood disaster, disaster causing factor, disaster-prone environment, disaster bearing body, disaster prevention and mitigation capacity, risk model, Qinghai Province

ZHANG Jing, BAO Guangyu, LIU Wei, YANG Chunhua, YAN Zhenning, DAI Qingcuo, FU Yongchao. Characteristics and model of rainstorm and flood disaster risk index along Qinghai Highway[J].Arid Land Geography, 2024, 47(1): 28-37.

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[1]	黄荣辉, 杜振彩. 全球变暖背景下中国旱涝气候灾害的演变特征及趋势[J]. 自然杂志, 2010, 32(4): 187-195.
	[Huang Ronghui, Du Zhencai. Evolution characteristics and trends of droughts and floods in China under the background of global warming[J]. Chinese Journal of Nature, 2010, 32(4): 187-195.]
[2]	史培军. 中国自然灾害、减灾建设与可持续发展[J]. 自然资源学报, 1995, 10(3): 267-278.
	[Shi Peijun. The natural disasters, constructions works for disaster reduction and sustainable development of China[J]. Journal of Natural Resources, 1995, 10(3): 267-278.]
[3]	何宗宜, 韩用顺. 基于GIS技术的洪水淹没计算分析系统[J]. 地理空间信息, 2003, 1(3): 5-7.
	[He Zongyi, Han Yongshun. Flood drowning analysis system based on GIS[J]. Geospatial Information, 2003, 1(3): 5-7.]
[4]	刘艳, 何清, 戴晓爱, 等. 新疆铁路沿线主要气象灾害风险区划及减灾对策探讨[J]. 自然灾害学报, 2016, 27(3): 48-57.
	[Liu Yan, He Qing, Dai Xiaoai, et al. Risk mapping of main meteorological disasters and disaster mitigation startegies for Xinjiang Railway lines[J]. Journal of Natural Disasters, 2016, 27(3): 48-57.]
[5]	汪超, 罗喜平. 基于GIS的贵州省道路结冰灾害风险区划分析[J]. 高原山地气象研究, 2017, 38(3): 71-77.
	[Wang Chao, Luo Xiping. Analysis of icy road disaster risk zoning in Guizhou Province base on GIS[J]. Plateau and Mountain Meteorology Research, 2017, 38(3): 71-77.]
[6]	董鹏捷, 王建捷. 北京地区冰雹灾害风险评估模型及风险区划[J]. 暴雨灾害, 2012, 31(1): 29-34.
	[Dong Pengjie, Wang Jianjie. Risk assessment model and regionalization of hail disaster in Beijing area[J]. Torrential Rain and Disasters, 2012, 31(1): 29-34.]
[7]	代娟, 崔新强, 刘文清, 等. 高速铁路气象灾害风险分析与区划方法探讨[J]. 灾害学, 2016, 31(4): 33-36.
	[Dai Juan, Cui Xinqiang, Liu Wenqing, et al. Research on meteorological disaster risk analysis and regionalization in high speed railway[J]. Journal of Catastrophology, 2016, 31(4): 33-36.]
[8]	高展, 许剑勇, 王胜, 等. 黄山风景区暴雨山洪灾害风险区划研究[J]. 暴雨灾害, 2015, 34(3): 281-285.
	[Gao Zhan, Xu Jianyong, Wang Sheng, et al. Research on regional risk zonation of mountain torrent disasters in Huangshan Scenic Area[J]. Torrential Rain and Disasters, 2015, 34(3): 281-285.]
[9]	朱小凡, 张明军, 王圣杰, 等. 1962—2012年青海省降雪初始终止日期和降雪日数时空变化特征[J]. 生态学杂志, 2014, 33(3): 761-770.
	[Zhu Xiaofan, Zhang Mingjun, Wang Shengjie, et al. Spatiotemporal variation patterns of the beginning and ending dates of snowfall, and snowfall days in Qinghai Province during 1962 to 2012[J]. Chinese Journal of Ecology, 2014, 33(3): 761-770.]
[10]	宁贵财, 康彩燕, 陈东辉, 等. 2005—2014年我国不利天气条件下交通事故特征分析[J]. 干旱气象, 2016, 34(5): 753-762. doi: 10.11755/j.issn.1006-7639(2016)-05-0753
	[Ning Guicai, Kang Caiyan, Chen Donghui, et al. Analysis of characteristics of traffic accidents under adverse weather conditions in China during 2005—2014[J]. Journal of Arid Meteorology, 2016, 34(5): 753-762.] doi: 10.11755/j.issn.1006-7639(2016)-05-0753
[11]	陈晓光, 李俊超, 李长林, 等. 风吹雪对公路交通的危害及其对策研讨[J]. 公路, 2001, 46(6): 113-118.
	[Chen Xiaoguang, Li Junchao, Li Changlin, et al. Study on the hazards of wind-blown snow in highway traffic and its countermeasures[J]. Highway, 2001, 46(6): 113-118.]
[12]	胡钰玲, 康延臻, 杨旭, 等. 2008—2015年北京高速公路道面结冰特征分析[J]. 冰川冻土, 2017, 39(4): 811-823.
	[Hu Yuling, Kang Yanzhen, Yang Xu, et al. An analysis of the temporal-spatial characteristics of highway surface freezing in Beijing from 2008 to 2015[J]. Journal of Glaciology and Geocryology, 2017, 39(4): 811-823.]
[13]	李刚, 罗喜平, 韩晓令. 贵州中西部道路结冰气象影响因子检验评估[J]. 贵州气象, 2016, 55(4): 6-10.
	[Li Gang, Luo Xiping, Han Xiaoling. Validation and assessment of road icing impact factors in midwest of Guizhou[J]. Journal of Guizhou Meteorology, 2016, 55(4): 6-10.]
[14]	罗生洲, 汪青春, 戴升. 青海省气象灾害的若干气候特征分析[J]. 冰川冻土, 2012, 34(6): 1380-1387.
	[Luo Shengzhou, Wang Qingchun, Dai Sheng. An analysis of climatic characteristics of meteorological disasters in Qinghai Province[J]. Journal of Glaciology and Geocryology, 2012, 34(6): 1380-1387.]
[15]	保广裕, 王文英, 张景华, 等. 青海省路结冰变化时空分布特征及其影响等级划分[J]. 气象科技, 2016, 44(1): 104-110.
	[Bao Guangyu, Wang Wenying, Zhang Jinghua, et al. Temporal-spatial distribution of road icing in Qinghai and its impact[J]. Meteorological Science and Technology, 2016, 44(1): 104-110.]
[16]	保广裕, 周丹, 郑玲, 等. 青海省公路沿线强降雪天气灾害风险区划方法研究[J]. 沙漠与绿洲气象, 2019, 13(4): 109-116.
	[Bao Guangyu, Zhou Dan, Zheng Ling, et al. A study of severe snowfall disaster risk zoning along highway in Qinghai Province[J]. Desert and Oasis Meteorology, 2019, 13(4): 109-116.]
[17]	保广裕, 杨春华, 周丹, 等. 京藏高速柴达木腹地路面温度变化特征及与气温要素影响分析[J]. 干旱区地理, 2021, 44(5): 1213-1221.
	[Bao Guangyu, Yang Chunhua, Zhou Dan, et al. Variation characteristics of road surface temperature and its influence on air temperature factors of Beijing-Tibet Expressway in the Qaidam Hinterland[J]. Arid Land Geography, 2021, 44(5): 1213-1221.]
[18]	代青措, 保广裕, 祁栋林, 等. 京藏高速青海东部地区汛期路面水膜厚度变化特征及预报模型构建[J]. 干旱区地理, 2022, 45(6): 1814-1823.
	[Dai Qingcuo, Bao Guangyu, Qi Donglin, et al. Variation characteristics of pavement water film thickness in flood season and construction of forecast model for Beijing-Tibet Expressway in the eastern part of Qinghai[J]. Arid Land Geography, 2022, 45(6): 1814-1823.]
[19]	陈真莲. 小流域山洪灾害成因及防治技术研究[D]. 广州: 华南理工大学, 2014.
	[Chen Zhenlian. Study on cause and prevention technology of mountain torrent disaster in small watershed[D]. Guangzhou: South China University of Technology, 2014.]
[20]	谢五三, 田红, 卢燕宇. 基于FloodArea模型的大通河流域暴雨洪涝灾害风险评估[J]. 暴雨灾害, 2015, 34(4): 384-387.
	[Xie Wusan, Tian Hong, Lu Yanyu. Risk evaluation of rainstorm and flood disasters in Datong River Basin based on the flood area model[J]. Torrential Rain and Disasters, 2015, 34(4): 384-387.]
[21]	刘家福, 李京, 刘荆, 等. 基于GIS/AHP集成的洪水灾害综合风险评价:以淮河流域为例[J]. 自然灾害学报, 2008, 17(6): 110-114.
	[Liu Jiafu, Li Jing, Liu Jing, et al. Integration GIS/AHP-based flood risk assessment: A case study of Huaihe River Basin in China[J]. Journal of Natural Disasters, 2008, 17(6): 110-114.]
[22]	管珉, 陈兴旺. 江西省山洪灾害风险区划初步研究[J]. 暴雨灾害, 2007, 26(4): 339-343.
	[Guan Min, Chen Xingwang. Research of regional torrent risk zonation in Jiangxi Province[J]. Torrential Rain and Disasters, 2007, 26(4): 339-343.]
[23]	甘薇薇, 范江琳, 肖天贵, 等. 四川省暴雨过程综合评估模型的研究及建立[J]. 冰川冻土, 2017, 39(6): 1336-1343.
	[Gan Weiwei, Fan Jianglin, Xiao Tiangui, et al. Research and establishment of a comprehensive evaluation model of rainstorm process in Sichuan Province[J]. Journal of Glaciology and Geocryology, 2017, 39(6): 1336-1343.]
[24]	王慧, 毛炜峄, 李元鹏, 等. 新疆易灾暴雨的风险区划[J]. 冰川冻土, 2011, 33(6): 1407-1413.
	[Wang Hui, Mao Weiyi, Li Yuanpeng, et al. Risk zoning of torrential rain which easily causes damage in Xinjiang region[J]. Journal of Glaciology and Geocryology, 2011, 33(6): 1407-1413.]
[25]	苏军锋, 肖志强, 魏邦宪, 等. 基于GIS的甘肃省陇南市暴雨灾害风险区划[J]. 干旱气象, 2012, 30(4): 650-655.
	[Su Junfeng, Xiao Zhiqiang, Wei Bangxian, et al. The risk zoning of rainstorm based on GIS in Longnan of Gansu Province[J]. Journal of Arid Meteorology, 2012, 30(4): 650-655.]
[26]	万昔超, 殷伟量, 孙鹏, 等. 基于云模型的暴雨洪涝灾害风险分区评价[J]. 自然灾害学报, 2017, 26(4): 77-83.
	[Wan Xichao, Yin Weiliang, Sun Peng, et al. Risk division assessment of rainstorm-flood disasters based on cloud model[J]. Journal of Natural Disasters, 2017, 26(4): 77-83.]
[27]	唐川, 朱静. 基于GIS的山洪灾害风险区划[J]. 地理学报, 2005, 60(1): 87-94. doi: 10.11821/xb200501010
	[Tang Chuan, Zhu Jing. A GIS based regional torrent risk zonation[J]. Acta Geographica Sinica, 2005, 60(1): 87-94.] doi: 10.11821/xb200501010
[28]	祁元, 刘勇, 杨正华, 等. 基于GIS的兰州滑坡与泥石流灾害危险性分析[J]. 冰川冻土, 2012, 34(1): 96-104.
	[Qi Yuan, Liu Yong, Yang Zhenghua, et al. GIS-based analysis of landslide and debris flow hazard in Lanzhou[J]. Journal of Glaciology and Geocryology, 2012, 34(1): 96-104.]
[29]	李美娟, 陈国宏, 陈衍泰. 综合评价中指标标准化方法研究[J]. 中国管理科学, 2004, 12(10): 45-48.
	[Li Meijuan, Chen Guohong, Chen Yantai. Study on target standardization method of comprehensive evaluation[J]. Chinese Journal of Management Science, 2004, 12(10): 45-48.]
[30]	Karhunen J, Joutsensalo J. Representation and separation of signals using nonlinear PCA type learning[J]. Neural Networks, 1994, 7(1): 113-127. doi: 10.1016/0893-6080(94)90060-4
[31]	Chen Y L, Zheng Y F. Face recognition for target detection on PCA features with outlier information[C]// 50^th Midwest Symposiumon Circuits and Systems. Montreal: Institute of Electrical and Electronic Engineers, 2007: 823-826.
[32]	李万志, 余迪, 冯晓莉, 等. 基于风险度的青海省暴雨洪涝灾害风险评估[J]. 冰川冻土, 2019, 41(3): 680-688.
	[Li Wanzhi, Yu Di, Feng Xiaoli, et al. Risk assessment of rainstorm and flood disasters based on the hazard grades/indices in Qinghai Province[J]. Journal of Glaciology and Geocryology, 2019, 41(3): 680-688.]
[33]	DB63/T372-2018. 青海省地方标准: 气象灾害标准[S]. 西宁: 青海省质量技术监督局, 2018.
	[DB63/T372-2018. Local standard of Qinghai Province: Meteorological disaster standard[S]. Xining: Qinghai Provincial Bureau of Quality and Technical Supervision, 2018.]

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目标层因子	权重	因素层因子	权重	数据类型
致灾因子	0.42	年均小雨日数/d	0.10	气象数据
		年均中雨日数/d	0.30	气象数据
		年累积强降雨日数/d	0.60	气象数据
孕灾环境	0.25	地形起伏度/%	0.26	环境数据
		河网密度/km·km^-2	0.42	环境数据
		植被覆盖度/%	0.32	环境数据
承灾体	0.21	人口密度/人·km^-2	0.11	人口密度数据
		地均耕地面积/m²	0.35	耕地密度数据
		地均大牲畜数量/头	0.30	地均大牲畜数量
		地均可利用草场面积/hm²	0.24	可利用草场面积
防灾减灾能力	0.12	人均GDP/10⁴元·人^-1	1.00	人均GDP

等级	强降水	评估风险	影响建议
1级	MDRI≤0.58	最低风险	暴雨洪涝灾害风险很小，对交通无影响。
2级	0.58<MDRI≤0.61	次低风险	暴雨洪涝灾害风险较小，对交通影响不大。
3级	0.61<MDRI≤0.63	中等风险	暴雨洪涝灾害风险较大，对交通影响较大。
4级	0.63<MDRI≤0.65	次高风险	暴雨洪涝灾害风险很大，对交通运行影响很大。
5级	MDRI>0.65	最高风险	暴雨洪涝灾害风险极大，对交通运行影响极大。

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