基于云-GIS模型的洪灾自然环境危险性评估研究——以神农架林区为例
|
摘要
针对中国山区村镇的洪灾特点,从致灾因子和孕灾环境两个方面,研究了极限降雨水平、汛期降雨水平、坡度、泥石流等10余项指标对洪灾自然环境危险性的影响,建立了基于云模型的洪灾自然环境危险性综合评价模型。同时,利用GIS系统对空间指标数据和属性指标数据予以度量并进行可视化表达,建立了洪灾的自然环境危险度评估模型,为政府构建预警应灾体系提供了依据。以神农架林区为例,运用云-GIS模型进行了洪灾的自然环境危险性评估。结果表明,神农架林区木鱼镇洪灾自然环境危险性最高。阳日镇、大九湖镇南部以及松柏镇东南部危险性较高,需重点防范。其他乡镇洪灾自然环境危险度相对较低,新华乡南部、松柏镇西北部和下谷坪乡危险性最低。
According to the characteristics of flood villages in mountainous areas in China, from two aspects of the disaster causing factors and the environment of pregnancy, this paper studies the impact of the limit rainfall level, the rainfall level in the flood season, the slope, the debris flow and so on on the natural environment hazard of the flood disaster, and establishes a comprehensive evaluation model of the natural environment hazard based on the cloud model. At the same time, the GIS system is used to measure and visualize the spatial index data and attribute data, and the hazard assessment model of the natural environment of flood is established, which provides the basis for the government to construct the early warning and disaster response system.Taking Shennongjia forest region as an example, we use cloud-GIS model to evaluate the natural environment risk of flood. The analysis results show that the most dangerous natural environment of flood disaster in Shennongjia forest region is Muyu town. There is a high risk in Yangri Town, the southern part of Dajiuhu Town and the southeastern part of Songbai Town, and we need to guard against them. The risk of natural disasters in other towns is relatively low. The southern part of Xinhua Township, the northwestern part of Songbai Town and Xiaguping Township are the least dangerous.
According to the characteristics of flood villages in mountainous areas in China, from two aspects of the disaster causing factors and the environment of pregnancy, this paper studies the impact of the limit rainfall level, the rainfall level in the flood season, the slope, the debris flow and so on on the natural environment hazard of the flood disaster, and establishes a comprehensive evaluation model of the natural environment hazard based on the cloud model. At the same time, the GIS system is used to measure and visualize the spatial index data and attribute data, and the hazard assessment model of the natural environment of flood is established, which provides the basis for the government to construct the early warning and disaster response system.Taking Shennongjia forest region as an example, we use cloud-GIS model to evaluate the natural environment risk of flood. The analysis results show that the most dangerous natural environment of flood disaster in Shennongjia forest region is Muyu town. There is a high risk in Yangri Town, the southern part of Dajiuhu Town and the southeastern part of Songbai Town, and we need to guard against them. The risk of natural disasters in other towns is relatively low. The southern part of Xinhua Township, the northwestern part of Songbai Town and Xiaguping Township are the least dangerous.
引文
[1]ISLAM M M,SADO K.Development of flood hazard maps of Bangla-desk using NOAA-AVHRR images with GIS[J].Hydrological Sciences Journal,2000,45(3):337-355.
[2]程先富,戴梦琴,郝丹丹.区域洪淀灾害风险评价研究进展[J].安徽师范大学学报(自然科学版),2015(1):74-79.
[3]FEDERAL EMERGENCY MANAGEMENT AGENCY(FEMA).Guidelines and Specifications for Flood Hazard Mapping Partners[M].Washington:Federal Emergency Management Agency,2003.
[4]RHOADS B L.Flood hazard assessment for land-use planning near desert mountains[J].Environmental Management,1986,10(10):97-106.
[5]OKODUWA A I.An Application of GIS to Flood Prediction;ACase Study of Benin City,Nigeria[D].Benin:University of Benin,1999.
[6]赵士鹏.山洪灾情评估的系统集成方法研究[D].北京:中国科学院地理研究所,1995.
[7]张行南,罗健,陈雷,等.中国洪水灾害危险程度区划[J].水利学报,2000(3):1-7.
[8]常秀峰.神农架林区洪灾风险评价[D].武汉:武汉大学,2017.
[9]何报寅,张海林,张穗,等.基于GIS的湖北省洪水灾害危险性评价[[J].自然灾害学报,2002(4):84-89.
[10]汪婷,何亚伯,常秀峰.基于云模型和GIS的神农架林区洪灾风险评价[J].湖北农业科学,2018,57(13):84-89.
[11]谭徐明,张伟兵,马建明,等.全国区域洪水风险评价与区划图绘制研究[J].中国水利水电科学研究院学报,2004,2(1):50-60.
[12]万君,周月华,王迎迎.基于GIS的湖北省区域洪涝灾害风险评估方法研究[J].暴雨灾害,2007,26(4):328-333.
[13]葛全胜.中国自然灾害风险综合评估初步研究[M].北京:科学出版社,2008.
[14]李德毅,杜鹢.不确定性人工智能[M].北京:国防工业出版社,2014.
[15]孙鸿鹄,程先富,倪玲,等.基于云模型和熵权法的巢湖流域防洪减灾能力评估[J].灾害学,2015,30(1):222-227.
[16]王望珍,张可欣,陈瑶.基于GIS的神农架林区多灾种耦合综合风险评估[J].湖北农业科学,2018,57(5):49-54.
[17]王贺,刘高峰,王慧敏.基于云模型的城市极端雨洪灾害风险评价[J].水利经济,2014,32(2):15-18.
[18]何亚伯,常秀峰,徐冰.山区村镇洪灾承灾能力评估——以神农架林区为例[J].中国安全生产科学技术,2016,12(6):94-99.
[2]程先富,戴梦琴,郝丹丹.区域洪淀灾害风险评价研究进展[J].安徽师范大学学报(自然科学版),2015(1):74-79.
[3]FEDERAL EMERGENCY MANAGEMENT AGENCY(FEMA).Guidelines and Specifications for Flood Hazard Mapping Partners[M].Washington:Federal Emergency Management Agency,2003.
[4]RHOADS B L.Flood hazard assessment for land-use planning near desert mountains[J].Environmental Management,1986,10(10):97-106.
[5]OKODUWA A I.An Application of GIS to Flood Prediction;ACase Study of Benin City,Nigeria[D].Benin:University of Benin,1999.
[6]赵士鹏.山洪灾情评估的系统集成方法研究[D].北京:中国科学院地理研究所,1995.
[7]张行南,罗健,陈雷,等.中国洪水灾害危险程度区划[J].水利学报,2000(3):1-7.
[8]常秀峰.神农架林区洪灾风险评价[D].武汉:武汉大学,2017.
[9]何报寅,张海林,张穗,等.基于GIS的湖北省洪水灾害危险性评价[[J].自然灾害学报,2002(4):84-89.
[10]汪婷,何亚伯,常秀峰.基于云模型和GIS的神农架林区洪灾风险评价[J].湖北农业科学,2018,57(13):84-89.
[11]谭徐明,张伟兵,马建明,等.全国区域洪水风险评价与区划图绘制研究[J].中国水利水电科学研究院学报,2004,2(1):50-60.
[12]万君,周月华,王迎迎.基于GIS的湖北省区域洪涝灾害风险评估方法研究[J].暴雨灾害,2007,26(4):328-333.
[13]葛全胜.中国自然灾害风险综合评估初步研究[M].北京:科学出版社,2008.
[14]李德毅,杜鹢.不确定性人工智能[M].北京:国防工业出版社,2014.
[15]孙鸿鹄,程先富,倪玲,等.基于云模型和熵权法的巢湖流域防洪减灾能力评估[J].灾害学,2015,30(1):222-227.
[16]王望珍,张可欣,陈瑶.基于GIS的神农架林区多灾种耦合综合风险评估[J].湖北农业科学,2018,57(5):49-54.
[17]王贺,刘高峰,王慧敏.基于云模型的城市极端雨洪灾害风险评价[J].水利经济,2014,32(2):15-18.
[18]何亚伯,常秀峰,徐冰.山区村镇洪灾承灾能力评估——以神农架林区为例[J].中国安全生产科学技术,2016,12(6):94-99.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |