[1]王东升,袁树堂.云南省1980-2017年洪涝灾害分析及模拟[J].山地学报,2018,(06):898-906.[doi:10.16089/j.cnki.1008-2786.000385]
　WANG Dongsheng,YUAN Shutang.Analysis and Simulation of 1980-2017 Flood Disasters in Yunnan Province, China[J].Mountain Research,2018,(06):898-906.[doi:10.16089/j.cnki.1008-2786.000385]
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云南省1980-2017年洪涝灾害分析及模拟()
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《山地学报》[ISSN:1008-2186/CN:51-1516]

卷:
期数:
2018年06期
页码:
898-906
栏目:
山地灾害
出版日期:
2018-11-30

文章信息/Info

Title:
Analysis and Simulation of 1980-2017 Flood Disasters in Yunnan Province, China
文章编号:
1008-2786-(2018)6-898-09
作者:
王东升; 袁树堂
云南省水文水资源局,昆明 650106
Author(s):
WANG Dongsheng; YUAN Shutang
Yunnan Provincial Bureau of Hydrology and Water Resources, Kunming 650106, China
关键词:
洪涝灾情评估;  社会经济指标;  相关分析;  预报因子;  预报模型;  云南省
Keywords:
flood disaster assessment;  socio-economic indicators;  correlation analysis;  predictive factors;  flood disaster forecasting model;  Yunnan province
分类号:
X43
DOI:
10.16089/j.cnki.1008-2786.000385
文献标志码:
A
摘要:
洪涝灾害是云南省主要自然灾害,开展洪涝灾害评估、影响因素及预测模型研究对提高云南省防灾减灾能力具有重要意义。本文基于1980-2017年资料,对云南省洪涝灾情进行了评估,使用Pearson法分析了洪涝灾害6个主要灾种、灾害与降水、社会经济指标相关关系,优选预报因子,建立了云南省洪涝灾情预报模型。结果表明:(1)1980—2017年,云南省有2 a为特别重大洪涝灾害年,占5.3%,11 a为重大洪涝灾害年,占28.9%,7 a为较大洪涝灾害年,占18.4%,18 a为一般洪涝灾害年,占47.4%。(2)年度、汛期降水量对洪涝灾害各灾种灾损影响无明显区别,但汛期降水量对房屋倒塌数量影响更为突出; GDP增长、人口的增加、城镇化的增长促进了水利及基础设施的投资,因洪涝灾害水利设施和直接经济损失同步增长,投资大幅增强了防灾减灾能力,云南省因灾死亡人数、直接经济损失占上一年度GDP比例及年度洪涝灾害水平反向大幅降低。(3)根据相关分析结果,优选汛期降水量、云南省地区生产总值、中国城镇化率作为年度洪涝灾情模拟预报因子构建预报模型,经模拟检验,洪涝灾情评估值模拟合格率68.4%,年度洪涝灾情等级模拟合格率71.1%,达乙级精度,以之预测云南省2018年洪涝灾情,评估值为16.6,为一般洪涝灾害年。
Abstract:
Flood disaster is the main natural disaster in Yunnan Province. Conducting flood disaster assessment, influencing factors and predictive model research is of great significance for improving disaster prevention and mitigation capabilities. Based on the data of 1980-2017, this paper evaluated flood disasters in Yunnan Province. The Pearson method was used to analyze the correlation between the six types of disaster data, disasters and precipitation, and socio-economic indicators. Forecasting factors were carefully selected and a flood disaster forecast model for Yunnan Province was established. Results found:(1)During 1980-2017, it occurred 2 years of severely great flood disasters, accounting for 5.3% of the total 38 years; 11 years of great flood disasters, accounting for 28.9%; 7 years of relatively great flood disasters, accounting for 18.4% and 18 years of regular floods, accounting for 47.4%.(2)There was no significant difference in the impact of annual precipitation and flood season precipitation on disaster damage, but the precipitation in flood season had a more prominent impact on the number of house collapses; The growth of GDP, the increase of population, and the growth of urbanization had promoted investments in water conservancy and infrastructure. As a result of floods, water conservancy facilities and direct economic losses had grown simultaneously. Investment had greatly enhanced the capacity of disaster prevention and mitigation. The number of deaths due to disasters, the proportion of direct economic losses to GDP in the previous year and the level of flood disasters in Yunnan Province had decreased significantly.(3)According to the relevant analysis results, the precipitation in flood season, the regional GDP in Yunnan Province and the urbanization rate in China were selected as the annual flood disaster forecasting factors to build a predication model. Through simulation tests, the qualified rate of flood disaster evaluation simulation was 68.4%, and the qualified rate of the annual flood disaster level simulation was 71.1%, reaching Grade B accuracy. As for assessment of flood disaster in 2018 in Yunnan Province, it came to be 16.6, suggesting a regular year of flood disaster.

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备注/Memo

备注/Memo:
收稿日期(Received date):2018-08-11; 改回日期(Accepted date):2018-12-27
基金项目(Foundation item):国家自然科学基金重点项目(91547205)。[Key Program of National Natural Science Foundation of China(91547205)]
作者简介(Biography):王东升(1981-),男,汉族,湖南隆回人,高级工程师,工程硕士,主要研究方向:水文情报预报,山洪灾害预警研究。[WANG Dongsheng(1981-),male, senior engineer,M.Eng.,research on hydrological forecast and mountain flood disaster warning] E-mail:116955105@qq.com。
更新日期/Last Update: 2018-11-30