基于GIS的陕西省干旱灾害风险评估及区划
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摘要
在分析陕西省干旱灾害气候背景和社会经济环境的基础上,结合灾害学相关理论,从致灾因子危险性、孕灾环境脆弱性、承灾体暴露性、防灾减灾能力4个子系统选取指标,建立干旱灾害风险评估模型。依据陕西省气象、生态和社会经济数据,运用GIS空间数据分析功能将干旱的自然和社会属性统一起来进行干旱灾害风险评估及区划。结果表明:(1)致灾因子危险性等级具有自北向南递减趋势,危险性等级最高的是榆林,其次是延安、铜川、宝鸡、咸阳、杨凌区、渭南、西安、商洛、安康和汉中。(2)孕灾环境脆弱性呈自北向南依次递减的分布趋势。脆弱性由强到弱分别是榆林、延安、铜川、宝鸡、西安、渭南、咸阳、杨凌区、商洛、安康和汉中。(3)承灾体暴露性由高到低依次是榆林、关中中部、渭南、咸阳、宝鸡、铜川、商洛、安康和汉中。(4)防灾减灾能力大小依次是榆林、关中地区、延安、汉中、安康、商洛。(5)干旱灾害风险等级自北向南呈逐渐降低趋势。干旱灾害风险由高到低依次为榆林、延安、铜川、宝鸡、渭南、西安、咸阳、杨凌区、商洛、安康和汉中。
In order to understand the actual situation of drought disaster risk in Shaanxi Province in a more comprehensive way,on the basis of the climatic background and social economic environment of drought disaster in Shaanxi,and combining with the related theory of natural disaster,we established the risk assessment model of drought disaster with the four assessment index subsystems containing the dangerousness of disaster risk,the vulnerability of the disaster environment,the exposure of the disaster bearing body,and the ability of disaster prevention and reduction;Based on the meteorological,ecological and social economic data of Shanxi Province,the assessment and regionalization of drought disaster risk in Shaanxi Province were carried out by using the GIS spatial data analysis.The results shows that:(1)The risk level of the disaster factor decreases from north to south,the highest hazard rank is in Yulin,followed by Yan'an,Tongchuan,Baoji,Xianyang,Yangling,Weinan,Xi'an,Shangluo,Ankang and Hanzhong.(2)The vulnerability of disaster environment also decreases from north to south.The size of vulnerability respectively is Yulin,Yan'an,Tongchuan,Baoji,Xi'an,Weinan,Xianyang,Yangling.(3)The exposure of disaster-bearing body of drought disaster is the highest in Yulin,followed by middle Guanzhong Area, Weinan, Xianyang,Baoji, Tongchuan Shangluo,Ankang and Hanzhong.(4)The disaster prevention and reduction capability from large to small is Yulin,Guanzhong Area,Yan'an,Hanzhong,Ankang,Shangluo;(5)The comprehensive risk level of drought disaster in Shaanxi Province gradually decreases from north to south.Drought risk from high to low respectively is Yulin,Yan'an,Tongchuan,Baoji,Weinan,Xi'an,Xianyang,Yangling,Shangluo,Ankang and Hanzhong.
In order to understand the actual situation of drought disaster risk in Shaanxi Province in a more comprehensive way,on the basis of the climatic background and social economic environment of drought disaster in Shaanxi,and combining with the related theory of natural disaster,we established the risk assessment model of drought disaster with the four assessment index subsystems containing the dangerousness of disaster risk,the vulnerability of the disaster environment,the exposure of the disaster bearing body,and the ability of disaster prevention and reduction;Based on the meteorological,ecological and social economic data of Shanxi Province,the assessment and regionalization of drought disaster risk in Shaanxi Province were carried out by using the GIS spatial data analysis.The results shows that:(1)The risk level of the disaster factor decreases from north to south,the highest hazard rank is in Yulin,followed by Yan'an,Tongchuan,Baoji,Xianyang,Yangling,Weinan,Xi'an,Shangluo,Ankang and Hanzhong.(2)The vulnerability of disaster environment also decreases from north to south.The size of vulnerability respectively is Yulin,Yan'an,Tongchuan,Baoji,Xi'an,Weinan,Xianyang,Yangling.(3)The exposure of disaster-bearing body of drought disaster is the highest in Yulin,followed by middle Guanzhong Area, Weinan, Xianyang,Baoji, Tongchuan Shangluo,Ankang and Hanzhong.(4)The disaster prevention and reduction capability from large to small is Yulin,Guanzhong Area,Yan'an,Hanzhong,Ankang,Shangluo;(5)The comprehensive risk level of drought disaster in Shaanxi Province gradually decreases from north to south.Drought risk from high to low respectively is Yulin,Yan'an,Tongchuan,Baoji,Weinan,Xi'an,Xianyang,Yangling,Shangluo,Ankang and Hanzhong.
引文
[1]刘航,蒋尚明,金菊良,等.基于GIS的区域干旱灾害风险区划研究[J].灾害学,2013,28(3):198-203.
[2]IPCC.Climate Change 2007:Impacts,Adaptation and Vulnerability[R].London,UK:Cambridge University Press,2007.
[3]赵宗慈,王邵武,罗勇.IPCC成立以来对温度升高的评估与预估[J].气候变化研究进展,2007,3(3):183-184.
[4]贾慧聪,王静爱.国内外不同尺度的旱灾风险评价研究进展[J].自然灾害学报,2011,20(2):138-145.
[5]Santos M A.区域干旱研究中的工程风险[M].北京:中国水利水电出社,1993:12-18.
[6]Blaikei P,Cannon T.Risk:Natural Hazard.People's Vulnerability and Disasters[M].London,UK:Rutledge,1994:147-167.
[7]王莺,王劲松,姚玉璧.甘肃省河东地区气象干旱灾害风险评估与区划[J].中国沙漠,2014,34(4):1115-1124.
[8]罗培.基于GIS的重庆市干旱灾害风险评估与区划[J].中国农业气象,2007,28(1):100-104.
[9]石界,姚玉璧,雷俊.基于GIS的定西市干旱灾害风险评估及区划[J].干旱气象,2014,32(2):305-309.
[10]魏建波,赵文吉,关鸿亮,等.基于GIS的区域干旱灾害风险区划研究——以武陵山片区为例[J].灾害学,2015,30(1):198-204.
[11]姚玉璧,李耀辉,石界,等.基于GIS的石羊河流域干旱灾害风险评估与区划[J].干旱地区农业研究,2014,32(2):21-28.
[12]韩兰英,张强,赵红岩,等.甘肃省农业干旱灾害损失特征及其对气候变暖的响应[J].中国沙漠,2016,36(3):767-776.
[13]赵光平,任小芳.1979—2012年中国西北地区东部低层水汽异常特征及成因[J].中国沙漠,2016,36(3):749-759.
[14]王鹏涛,延军平,蒋冲,等.2000-2012年陕甘宁黄土高原区地表蒸散时空分布及影响因素[J].中国沙漠,2016,36(2):499-507.
[15]李雪萍,史兴民,王阿如娜.中国典型等降水量线年代际空间演变[J].中国沙漠,2016,36(1):232-238.
[16]姚玉璧,张强,李耀辉,等.干旱灾害风险评估技术及其科学问题与展望[J].资源科学,2013,35(9):1884-1897.
[17]杜继稳.陕西省干旱监测预警评估与风险管理[M].北京:气象出版,2005:29-35,170.
[18]张俊香,黄崇福.自然灾害区划与风险区划研究进展[C]//中国灾害防御协会风险分析专业委员会第一届年会论文集,2004:55-61.
[19]徐小钰,朱记伟,解建仓,等.陕西省1470—2012年旱涝灾害时空分布特征及演变趋势分析[J].西安理工大学学报,2015,31(2):231-237.
[20]陕西省地情网统计数据:http://www.sxsdq.cn/whsy/dfzwh/.
[21]崔兆韵,黄华,王玉荣,等.岱岳区干旱风险评价及区划分析[J].山西农业科学,2012,40(6):669-674.
[22]黄崇福.自然灾害动态风险分析基本原理的探讨[J].灾害学,2015,30(2):1-7.
[23]李树军,袁静,何永健,等.基于GIS的潍坊市暴雨洪涝灾害风险区划[J].中国农学通报,2012,28(20):295-301.
[24]董四辉,宿博.层次分析法的改进方法在煤矿安全评价中的应用[J].辽宁工程技术大学学报:自然科学版,2012,31(5):690-694.
[25]邹旭恺,张强.近半个世纪我国干旱变化的初步研究[J].应用气象学报,2008,19(6):679-687.
[26]刘晓梅,李晶,吕志红,等.近50年辽宁省干旱综合指数的动态变化[J].生态学杂志,2009,28(5):938-942.
[27]张刚,杨昕,汤国安.GIS软件的空间分析功能比较[J].南京师范大学学报:工程技术版,2013,13(2):41-47.
[28]李晓军.GIS空间分析方法研究[D].杭州:浙江大学,2007.
[29]邹敏.基于GIS技术的黄水河流域山洪灾害风险区划研究[D].济南:山东师范大学,2007.
[2]IPCC.Climate Change 2007:Impacts,Adaptation and Vulnerability[R].London,UK:Cambridge University Press,2007.
[3]赵宗慈,王邵武,罗勇.IPCC成立以来对温度升高的评估与预估[J].气候变化研究进展,2007,3(3):183-184.
[4]贾慧聪,王静爱.国内外不同尺度的旱灾风险评价研究进展[J].自然灾害学报,2011,20(2):138-145.
[5]Santos M A.区域干旱研究中的工程风险[M].北京:中国水利水电出社,1993:12-18.
[6]Blaikei P,Cannon T.Risk:Natural Hazard.People's Vulnerability and Disasters[M].London,UK:Rutledge,1994:147-167.
[7]王莺,王劲松,姚玉璧.甘肃省河东地区气象干旱灾害风险评估与区划[J].中国沙漠,2014,34(4):1115-1124.
[8]罗培.基于GIS的重庆市干旱灾害风险评估与区划[J].中国农业气象,2007,28(1):100-104.
[9]石界,姚玉璧,雷俊.基于GIS的定西市干旱灾害风险评估及区划[J].干旱气象,2014,32(2):305-309.
[10]魏建波,赵文吉,关鸿亮,等.基于GIS的区域干旱灾害风险区划研究——以武陵山片区为例[J].灾害学,2015,30(1):198-204.
[11]姚玉璧,李耀辉,石界,等.基于GIS的石羊河流域干旱灾害风险评估与区划[J].干旱地区农业研究,2014,32(2):21-28.
[12]韩兰英,张强,赵红岩,等.甘肃省农业干旱灾害损失特征及其对气候变暖的响应[J].中国沙漠,2016,36(3):767-776.
[13]赵光平,任小芳.1979—2012年中国西北地区东部低层水汽异常特征及成因[J].中国沙漠,2016,36(3):749-759.
[14]王鹏涛,延军平,蒋冲,等.2000-2012年陕甘宁黄土高原区地表蒸散时空分布及影响因素[J].中国沙漠,2016,36(2):499-507.
[15]李雪萍,史兴民,王阿如娜.中国典型等降水量线年代际空间演变[J].中国沙漠,2016,36(1):232-238.
[16]姚玉璧,张强,李耀辉,等.干旱灾害风险评估技术及其科学问题与展望[J].资源科学,2013,35(9):1884-1897.
[17]杜继稳.陕西省干旱监测预警评估与风险管理[M].北京:气象出版,2005:29-35,170.
[18]张俊香,黄崇福.自然灾害区划与风险区划研究进展[C]//中国灾害防御协会风险分析专业委员会第一届年会论文集,2004:55-61.
[19]徐小钰,朱记伟,解建仓,等.陕西省1470—2012年旱涝灾害时空分布特征及演变趋势分析[J].西安理工大学学报,2015,31(2):231-237.
[20]陕西省地情网统计数据:http://www.sxsdq.cn/whsy/dfzwh/.
[21]崔兆韵,黄华,王玉荣,等.岱岳区干旱风险评价及区划分析[J].山西农业科学,2012,40(6):669-674.
[22]黄崇福.自然灾害动态风险分析基本原理的探讨[J].灾害学,2015,30(2):1-7.
[23]李树军,袁静,何永健,等.基于GIS的潍坊市暴雨洪涝灾害风险区划[J].中国农学通报,2012,28(20):295-301.
[24]董四辉,宿博.层次分析法的改进方法在煤矿安全评价中的应用[J].辽宁工程技术大学学报:自然科学版,2012,31(5):690-694.
[25]邹旭恺,张强.近半个世纪我国干旱变化的初步研究[J].应用气象学报,2008,19(6):679-687.
[26]刘晓梅,李晶,吕志红,等.近50年辽宁省干旱综合指数的动态变化[J].生态学杂志,2009,28(5):938-942.
[27]张刚,杨昕,汤国安.GIS软件的空间分析功能比较[J].南京师范大学学报:工程技术版,2013,13(2):41-47.
[28]李晓军.GIS空间分析方法研究[D].杭州:浙江大学,2007.
[29]邹敏.基于GIS技术的黄水河流域山洪灾害风险区划研究[D].济南:山东师范大学,2007.