基于历史暴雨洪涝灾情数据的城市脆弱性定量研究——以北京市为例

doi:10.13249/j.cnki.sgs.2016.05.011

摘要/Abstract

摘要：

基于历史暴雨洪涝灾情数据构建脆弱性曲线,定量研究北京市在不同降雨量下的宏观脆弱性。分析显示,在现有的抗灾能力下,相同降雨量所导致的农作物受灾率值最高,死亡失踪率值最低;随着最大2 d降雨量增大,承灾体的损失率增加明显,当最大2 d降雨量重现周期达到百年一遇时,在现有的社会经济暴露状况下,受灾人口数将达到147.4万人,死亡失踪人数也将有可能达到50人左右,农作物受灾面积有可能达到7万hm²,倒塌和损坏房屋将可能达到60万间,直接经济损失可能超过400亿元。北京市的洪涝灾害风险管理力度还有待加强。

关键词: 暴雨洪涝, 脆弱性曲线, 北京市

Abstract:

Based on the historical loss data, the study builds vulnerability curves and carries out qualitative research on the general vulnerability of Beijing to rainstorms and floods under different rainfall scenarios. The results show that: 1) There is a high correlation between the maximum 2-day rainfall and the loss rates, the established vulnerability curves can express the relation and be used for loss estimation; 2) According to the P-III fitting curves, the once-in-5-year maximum 2-day rainfall in Beijing is 110.5 mm, and the figures for once-in-10-year, once-in-20-year, once-in-50-year and once-in-100-year occasions are 134.8 mm, 159.0 mm, 190.8 mm and 214.8 mm, respectively; 3) With the current ability to resist disasters, under the same rainfall scenario, the crops loss rate is the highest, followed by population affected rate, buildings damaged rate, direct economic loss rate and buildings collapse rate, death or missing rate is the lowest; 4) The loss rate rises dramatically with the increase of maximum 2-day rainfalls. With current social and economic exposure, when the maximum 2-day rainfall recurrence period reached once-in-5-year, population affected may be 6.2×10⁴ and the number of death or missing may be 4 people, the area of crops affected may be 2×10³ hm², the number of buildings damaged or collapse may be 3.5×10³, and direct economic loss may be 3×10⁸. When the maximum 2-day rainfall recurrence period reached once-in-100-year, population affected may reach 1.474×10⁶ and the number of death or missing may reach about 50 people, the area of crops affected may reach 7×10⁴ hm², the number of buildings damaged or collapse may reach 6×10⁵, and direct economic loss may exceed 4×10¹⁰ yuan(RMB). So Beijing still needs to give high importance to flood problems and strengthen its flood risk management in this regard.

Key words: rainstorms and floods, vulnerability curve, Beijing

中图分类号:

S422

杨佩国, 靳京, 赵东升, 李静. 基于历史暴雨洪涝灾情数据的城市脆弱性定量研究——以北京市为例[J]. 地理科学, 2016, 36(5): 733-741.

Peiguo Yang, Jing Jin, Dongsheng Zhao, Jing Li. An Urban Vulnerability Study Based on Historical Flood Data: A Case Study of Beijing[J]. SCIENTIA GEOGRAPHICA SINICA, 2016, 36(5): 733-741.

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损失率	最大1 d 降雨量	最大2 d 降雨量	最大3 d 降雨量	最大4 d 降雨量	最大5 d 降雨量	最大6 d 降雨量	最大7 d 降雨量	6~8月降雨总量
人口受灾率	0.857**	0.902**	0.898**	0.872**	0.821*	0.719*	0.641	0.603
死亡失踪率	0.580	0.598	0.582	0.535	0.503	0.330	0.144	0.190
农作物受灾率	0.667**	0.906**	0.861**	0.880**	0.849**	0.895**	0.894**	0.772**
农作物绝收率	0.484	0.553	0.502	0.517	0.470	0.515	0.436	0.382
房屋倒塌率	0.856*	0.916**	0.943**	0.941**	0.946**	0.836**	0.801*	0.707*
房屋损坏率	0.921**	0.858*	0.868*	0.817*	0.820*	0.651	0.541	0.542
直接经济损失率	0.525	0.600*	0.552	0.518	0.465	0.334	0.226	0.184
人口紧急转移安置率	0.929**	0.878**	0.867**	0.832**	0.819**	0.669*	0.580	0.577

自变量（X）	因变量（Y）	R²	显著性	脆弱性曲线拟合方程
最大2 d降雨量	人口受灾率	0.774	0.004	Y=1/(0.01+102.662 0×0.996 9^x)
	死亡失踪率	0.773	0.009	Y=1/(0.01+949 913.103 3×0.997 4^x)
	农作物受灾率	0.813	0.000	Y=-1.624 3-8.144 0×10^-4x+7.565 7×10^-6×x²
	房屋倒塌率	0.961	0.000	Y=1/(0.01+61 328.418 2×0.995 5^x)
	房屋损坏率	0.960	0.001	Y=1/(0.01+3 939.654 6×0.995 5^x)
	直接经济损失率	0.709	0.001	Y=1/(0.01+13 121.874 0×0.995 2^x)

最大2 d降雨量（mm）	人口受灾率（%）	死亡失踪率（%）	农作物受灾率（%）	房屋倒塌率（%）	房屋损坏率（%）	直接经济损失率（%）
110.5	3.00×10^-1	1.87×10^-5	7.52	2.38×10^-3	3.70×10^-2	1.55×10^-2
134.8	6.36×10^-1	3.52×10^-5	1.20×10	7.12×10^-3	1.11×10^-1	5.00×10^-2
159.0	1.34	6.61×10^-5	1.74×10	2.12×10^-2	3.29×10^-1	1.60×10^-1
190.8	3.51	1.51×10^-4	2.58×10	8.90×10^-2	1.37	7.34×10^-1
214.8	7.13	2.82×10^-4	3.31×10	2.62×10^-1	3.93	2.29

最大2 d降雨量（mm）	受灾人口数（万人）	死亡失踪人数（人）	农作物受灾面积（万hm²）	房屋倒塌间数（万间）	房屋损坏间数（万间）	直接经济损失（亿元）
110.5	6.2	4	0.2	0.03	0.5	3
134.8	13.2	7	2.7	0.1	1.6	9
159.0	27.7	14	3.8	0.3	4.7	29
190.8	72.7	31	5.7	1.2	19.5	131
214.8	147.4	58	7.3	3.7	56.0	410

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