2001—2020年中国洪涝灾害损失与致灾危险性研究

doi:10.12006/j.issn.1673-1719.2021.196

摘要/Abstract

摘要：

利用最新的全国洪涝灾害损失资料以及气象站点降水观测资料,研究了2001—2020年中国洪涝灾害损失的演变特征及其与降水的关系。结果表明：2001—2020年,我国洪涝灾害造成的年均受灾人口超过1亿人次,直接经济损失1678.6亿元。尽管洪涝灾害造成的全国直接经济损失有增加趋势,但全国农作物受灾面积、受灾人口、死亡人口、损坏房屋以及直接经济损失占国内生产总值的比例均呈减少趋势。从空间分布来看,长江流域上中游地区及黑龙江、河北、甘肃、广西等地是洪涝灾害损失较为严重的地区。全国大部分地区死亡人口和损坏房屋呈减少趋势,直接经济损失呈增加趋势,而受灾人口和农作物受灾面积呈北增南减的变化趋势。近10年,我国北方大部分地区除了死亡人口外其余各项损失均较上个10年增加,其中黑龙江和河北增加幅度较大。同时,近10年我国北方大部分地区降水量增加,尤其是黑龙江、河北等地暴雨量和暴雨日数增加幅度较大,加剧了相对脆弱的北方地区的洪涝灾害风险。

关键词: 洪涝灾害, 灾害损失, 降水, 气候变化

Abstract:

Based on the latest provincial flood disaster loss data and observational precipitation data of meteorological stations in China, the spatial-temporal characteristics of flood disaster losses and the related hazards from 2001 to 2020 were studied. During 2001-2020, floods have caused an annual average of more than 100 million affected population, with direct economic losses of CNY 167.86 billion yuan. Despite the increasing trend of direct economic losses, the affected population and crop area, fatalities, damaged houses and proportion of direct economic losses to gross domestic product all show decreasing trend in the recent 20 years. The areas are more seriously affected by floods in the upper and middle reaches of the Yangtze River basin, Heilongjiang, Hebei, Gansu, and Guangxi provinces. The fatalities and damaged houses are decreasing while the direct economic losses are increasing in most of China. However, the affected population and crop area show different trend distribution, increasing in northern China while decreasing in southern China. In the past decade, flood losses except fatalities have increased compared to the previous decade in most parts of northern China, especially in Hebei and Heilongjiang provinces. At the same time, total precipitation increases in most parts of northern China, and the amount of heavy rainfall and rainstorm days increase greatly in Heilongjiang and Hebei provinces, which further increases the risk of floods in the relatively vulnerable northern China.

Key words: Flood disaster, Disaster loss, Precipitation, Climate change

李莹, 赵珊珊. 2001—2020年中国洪涝灾害损失与致灾危险性研究[J]. 气候变化研究进展, 2022, 18(2): 154-165.

LI Ying, ZHAO Shan-Shan. Floods losses and hazards in China from 2001 to 2020[J]. Climate Change Research, 2022, 18(2): 154-165.

图/表 6

图1 2001—2020年全国洪涝灾害造成的损失

Fig. 1 Annual variation of flood losses from 2001 to 2020. (a) Affected population, (b) fatalities and damaged houses,(c) affected crop area, (d) direct economic losses

图2 2001—2020年全国洪涝灾害造成的损失及前后10年的差值

Fig. 2 Spatial distribution of flood losses in China from 2001 to 2020 (left) and the difference (right) between 2011-2020 and 2001-2010. (a) (b) Affected population, (c) (d) fatalities, (e) (f) affected crop area, (g) (h) damaged houses, (i) (j) direct economic losses

图3 2001—2020年全国平均降水量和暴雨量(a)及降水日数和暴雨日数(b)历年变化

Fig. 3 Annual variation of the amount of precipitation and heavy rainfall (a), precipitation days and rainstorm days (b) in China from 2001 to 2020

图4 2001—2020年降水要素的平均值、变化趋势以及近10年与上个10年的差值注：黑点表示变化趋势显著。

Fig. 4 Spatial distribution of the annual averages, long-term trends for 2001?2020, and differences between the last decade (2011-2020) and the previous decade (2001-2010). (a) (b) (c) Total rainfall, (d) (e) (f) heavy rainfall, (g) (h) (i) rainstorm days. (Black dot denotes that trend is significant at a significance level of 0.05)

表1 降水与洪涝灾害损失的相关系数

Table 1 Correlation coefficients of precipitation and flood losses

图5 全国降水量、暴雨量和暴雨日数与洪涝灾害损失相关系数注：点线为通过0.05的显著性检验对应的相关系数阈值;由于数据原因,不包括港、澳、台地区。

Fig. 5 Correlation coefficients between flood losses and total rainfall, heavy rainfall, and rainstorm days at provincial level in China. (a) Affected crop area, (b) affected population, (c) fatalities, (d) damaged houses, (e) direct economic losses. (The dotted line is the correlation coefficient threshold corresponding to the 0.05 significance level)

参考文献 36

[1]	夏军, 王惠筠, 甘瑶瑶, 等. 中国暴雨洪涝预报方法的研究进展[J]. 暴雨灾害, 2019, 38(5):416-421.
	Xia J, Wang H Y, Gan Y Y, et al. Research progress in forecasting methods of rainstorm and flood disaster in China[J]. Torrential Rain and Disasters, 2019, 38(5):416-421 (in Chinese)
[2]	丁一汇. 中国暴雨理论的发展历程与重要进展[J]. 暴雨灾害, 2019, 38(5):395-406.
	Ding Y H. The major advances and development process of the theory of heavy rainfalls in China[J]. Torrential Rain and Disasters, 2019, 38(5):395-406 (in Chinese)
[3]	孔锋, 方建, 吕丽莉. 1961—2015年中国暴雨变化诊断及其与多种气候因子的关联性研究[J]. 热带气象学报, 2018, 34(1):34-47.
	Kong F, Fang J, Lu L L. The diagnosis of heave rainfall in China and correlation of heavy rainfall with multiple climatic factors in China from 1961 to 2015[J]. Journal of Tropical Meteorology, 2018, 34(1):34-47 (in Chinese)
[4]	Tellman B, Sullivan J A, Kuhn C, et al. Satellite imaging reveals increased proportion of population exposed to floods[J]. Nature, 2021, 596:80-86 doi: 10.1038/s41586-021-03695-w URL
[5]	王珏, 聂文东, 王静爱. 中国大都市群地区的水灾风险与应急管理研究[J]. 自然灾害学报, 2005, 14(6):59-64.
	Wang J, Nie W D, Wang J A. Flood risk assessment and emergency management in metropolises of China[J]. Journal of Natural Disasters, 2005, 14(6):59-64 (in Chinese)
[6]	方建, 杜鹃, 徐伟, 等. 气候变化对洪水灾害影响研究进展[J]. 地球科学进展, 2014, 29(9):1085-1093.
	Fang J, Du J, Xu W, et al. Advances in the study of climate change impacts on flood disaster[J]. Advance in Earth Science, 2014, 29(9):1085-1093 (in Chinese)
[7]	於琍, 徐影, 张永香. 近25 a中国暴雨及其引发的暴雨洪涝灾害影响的时空变化特征[J]. 暴雨灾害, 2018, 37(1):67-72.
	Yu L, Xu Y, Zhang Y X. Temporal and spatial variation of rainstorms and the impact of flood disasters due to rainstorms in China in the past 25 years[J]. Torrential Rain and Disasters, 2018, 37(1):67-72 (in Chinese)
[8]	赵珊珊, 高歌, 黄大鹏, 等. 2004—2013年中国气象灾害损失特征分析[J]. 气象与环境学报, 2017, 33(1):101-107.
	Zhao S S, Gao G, Huang D P, et al. Characteristics of meteorological disaster losses in China from 2004 to 2013[J]. Journal of Meteorology and Environment, 2017, 33(1):101-107 (in Chinese)
[9]	闵爱荣, 廖移山, 邓雯. 2008—2013年我国暴雨分布情况及变化趋势分析[J]. 暴雨灾害, 2016, 35(6):576-584.
	Min A R, Liao Y S, Deng W. The analysis of the distribution and trend for heavy rainfall based on the precipitation data from 2008 to 2013 in China[J]. Torrential Rain and Disasters, 2016, 35(6):576-584 (in Chinese)
[10]	Trenberth K E, Fasullo J, Simth L. Trends and variability in column-integrated atmospheric water vapor[J]. Climate Dynamic, 2005, 24(7-8):741-758 doi: 10.1007/s00382-005-0017-4 URL
[11]	Wentz F J, Ricciardulli L, Hilburn K, et al. How much more rain will global warming bring[J]. Science, 2007, 317(5835):233-235 doi: 10.1126/science.1140746 URL
[12]	Zhao P, Yang S, Yu R C. Long-term changes in rainfall over eastern China and large-scale atmospheric circulation associated with recent global warming[J]. Journal of Climate, 2010, 23(6):1544-1562 doi: 10.1175/2009JCLI2660.1 URL
[13]	王大钧, 陈列, 丁裕国. 近40年来中国降水量、雨日变化趋势及与全球温度变化的关系[J]. 热带气象学报, 2006, 22(3):283-289.
	Wang D J, Chen L, Ding Y G. The change trend in rainfall, wet days of China in recent 40 years and the correlation between the change trend and the change of globe temperature[J]. Journal of Tropical Meteorology, 2006, 22(3):283-289 (in Chinese)
[14]	翟盘茂, 任福民, 张强. 中国降水极值变化趋势检测[J]. 气象学报, 1999, 57(2):208-216.
	Zhai P M, Ren F M, Zhang Q. Detection of trends in China's precipitation extremes[J]. Journal of Meteorological Research, 1999, 57(2):208-216 (in Chinese)
[15]	中国气象局. 中国极端天气和灾害风险管理评估报告[D]. 北京: 科学出版社, 2015.
	China Meteorological Administration. Assessment report on extreme weather and disaster risk management in China[D]. Beijing: Science Press, 2015 (in Chinese)
[16]	IPCC. Climate change 2021: the physical science basis [M]. Cambridge: Cambridge University Press, 2021
[17]	Zhang W X, Furtado K, Wu P L, et al. Increasing precipitation variability on daily-to-multiyear timescales in a warmer world[J]. Science Advances, 2021. DOI: 10.1126/sciadv.abf8021 doi: 10.1126/sciadv.abf8021
[18]	孔锋, 刘凡, 王一飞, 等. 中国气候变化与水灾发生频次的时空关系研究 (1961—2010)[J]. 灾害学, 2017, 32(4):35-42.
	Kong F, Liu F, Wang Y F, et al. Spatial relationship between flooding frequency and climate change based on climate change regionalization in China from 1961 to 2010[J]. Journal of Catastrophology, 2017, 32(4):35-42 (in Chinese)
[19]	万金红, 张葆蔚, 刘建刚, 等. 1950—2013年我国洪涝灾情时空特征分析[J]. 灾害学, 2016, 31(2):63-68.
	Wan J H, Zhang B W, Liu J G, et al. The distribution of flood disaster loss during 1950-2013[J]. Journal of Catastrophology, 2016, 31(2):63-68 (in Chinese)
[20]	邱海军. 1950—2010年中国洪涝灾情的频率规模关系[J]. 自然灾害学报, 2013, 22(4):114-118.
	Qiu H J. The relationship between the frequency and the scale of flood situation in China from 1950 to 2010[J]. Journal of Natural Disasters, 2013, 22(4):114-118 (in Chinese)
[21]	朱思诚, 任希岩. 关于城市内涝问题的思考[J]. 行政管理改革, 2011, 11:62-66.
	Zhu S C, Ren X Y. Reflections on urban flooding[J]. Administration Reform, 2011, 11:62-66 (in Chinese)
[22]	He B, Huang X, Ma M, et al. Analysis of flash flood disaster characteristics in China from 2011 to 2015[J]. Natural Hazards, 2018, 90:407-420 doi: 10.1007/s11069-017-3052-7 URL
[23]	Wu J, Li Y, Ye T, et al. Changes in mortality and economic vulnerability to climatic hazards under economic development at the provincial level in China[J]. Regional Environmental Change, 2018, 19:1-12 doi: 10.1007/s10113-018-1406-7 URL
[24]	张建云, 王银堂, 胡庆芳, 等. 海绵城市建设有关问题讨论[J]. 水科学进展, 2016, 27(6):793-799.
	Zhang J Y, Wang Y T, Hu Q F, et al. Discussion and views on some issues of the sponge city construction in China[J]. Advances in Water Science, 2016, 27(6):793-799 (in Chinese)
[25]	高歌, 黄大鹏, 赵珊珊. 基于信息扩散方法的中国台风灾害年月尺度风险评估[J]. 气象, 2019, 45(11):1600-1610.
	Gao G, Huang D P, Zhao S S. Annual and monthly risk assessment of typhoon disasters in China based on the information diffusion method[J]. Meteorological Monthly, 2019, 45(11):1600-1610 (in Chinese)
[26]	曹丽娟, 严中伟. 地面气候资料均一性研究进展[J]. 气候变化研究进展, 2011, 7(2):129-135.
	Cao L J, Yan Z W. Progresses in research of homogenization of climate data[J]. Climate Change Research, 2011, 7(2):129-135 (in Chinese)
[27]	Ren F, Wu G, Dong W, et al. Changes in tropical cyclone precipitation over China[J]. Geophysical Research Letters, 2006, 33, L20702 doi: 10.1029/2006GL027951 URL
[28]	Luo Y L, Wu M W, Ren F M, et al. Synoptic situations of extreme hourly precipitation over China[J]. Journal of Climate, 2016, 29:8703-8719 doi: 10.1175/JCLI-D-16-0057.1 URL
[29]	魏凤英. 现代气候统计诊断与预测技术[M]. 北京: 气象出版社, 2007: 18-19.
	Wei F Y. The modern climate statistical diagnosis and prediction technology [M]. Beijing: China Meteorology Press, 2007: 18-19 (in Chinese)
[30]	Wu J D, Han G Y, Zhou H J, et al. Economic development and declining vulnerability to climate-related disasters in China[J]. Environment Research Letter, 2018, 13:034013 doi: 10.1088/1748-9326/aaabd7 URL
[31]	Zhou Y, Li N, Wu W X, et al. Exploring the characteristics of major natural disasters in China and their impacts during the past decades[J]. Natural Hazards, 2013, 69(1):829-843 doi: 10.1007/s11069-013-0738-3 URL
[32]	国家统计局. 人民生活实现历史性跨越阔步迈向全面小康: 新中国成立70周年经济社会发展成就系列报告之十四[EB/OL]. 2019 [2019-08-09]. http://www.stats.gov.cn/tjsj/zxfb/201908/t20190809_1690098.html.
	National Bureau of Statistics. People's life achieves historic leaps and strides toward comprehensive prosperity: a series of reports on the achievements of economic and social development in the 70th anniversary of the founding of new China No. 14 [EB/OL]. 2019 [2019-08-09]. http://www.stats.gov.cn/tjsj/zxfb/201908/t20190809_1690098.html (in Chinese)
[33]	樊高峰, 何月, 顾俊强. 基于GIS的浙江省暴雨灾害及其危险性评价[J]. 中国农学通报, 2012, 28(32):293-299.
	Fan G F, He Y, Gu J Q. The rainstorm disaster and its risk assessment based on GIS in Zhejiang province[J]. Chinese Agricultural Science Bulletin, 2012, 28(32):293-299 (in Chinese)
[34]	沈澄, 孙燕, 尹东屏, 等. 江苏省暴雨洪涝灾害特征分析[J]. 自然灾害学报, 2015, 24(2):203-212.
	Shen C, Sun Y, Yin D P, et al. Characteristic analysis of rainstorm-induced flood disaster in Jiangsu province[J]. Journal of Natural Disasters, 2015, 24(2):203-212 (in Chinese)
[35]	Kong F, Sun S, Lei T. Understanding China's urban rainstorm waterlogging and its potential governance[J]. Water, 2021, 13(7):891 doi: 10.3390/w13070891 URL
[36]	郑艳, 翟建青, 武占云, 等. 基于适应性周期的韧性城市分类评价: 以我国海绵城市与气候适应型城市试点为例[J]. 中国人口∙资源与环境, 2018, 28(3):31-38.
	Zheng Y, Zhai J Q, Wu Z Y, et al. A typology analysis on resilient cities based on adaptive cycle: taking cases of Chinese sponge cities and climate resilient cites pilot projects[J]. China Population Resources and Environment, 2018, 28(3):31-38 (in Chinese)