海岸侵蚀脆弱性及驱动因子分析——以江苏中部海岸为例

doi:10.3969/j.issn.1001-909X.2023.04.007

摘要/Abstract

摘要：

海岸侵蚀导致土地流失,严重威胁人民生命财产安全,识别海岸侵蚀脆弱性对于防灾减灾意义重大。从海岸动力、海岸形态和社会经济三个方面构建评价指标体系,利用数字化海岸线分析系统(digital shoreline analysis system,DSAS)和遥感数据,采用断面法将海岸离散为等间距的评价单元,基于熵权法确定评价指标权重、等级并计算海岸侵蚀脆弱性,利用地理探测器识别海岸侵蚀脆弱性的空间分异和影响因素。结果表明:江苏中部海岸侵蚀脆弱性为极高脆弱、高脆弱、中脆弱、低脆弱和极低脆弱的比例分别为5.60%、15.80%、30.93%、24.21%和23.46%,海岸侵蚀脆弱性总体呈现北高南低的分布趋势,其中为极脆弱的区域主要位于中山河口—射阳河口之间的海岸区域。江苏中部海岸侵蚀脆弱性的空间分异是海岸动力、海岸形态、社会经济多重因素协同作用的结果,其中潮滩坡度、地表覆盖类型、平均潮差、海岸线变化速率是海岸侵蚀脆弱性空间分异的主导因子。

关键词: 海岸侵蚀, 脆弱性, DSAS, 地理探测器, 驱动因子

Abstract:

Coastal erosion leads to land loss and seriously threatens people’s life and property safety. It is great significant to identify coastal erosion vulnerability for disaster prevention and mitigation. The evaluation index system was constructed from three aspects: coastal dynamics, coastal morphology and social economy. Using the DSAS model and remote sensing data, the coast was discretized into equally spaced units based on section method, the weight and grade of the evaluation index were determined based on the entropy weight method, the coastal erosion vulnerability in the study area was calculated, and the spatial differentiation and influencing factors of coastal erosion vulnerability were identified by geographic detector. The results showed that the proportions of coastal erosion vulnerability for extremely high vulnerability, high vulnerability, medium vulnerability, low vulnerability and extremely low vulnerability in central coast of Jiangsu were 5.60%, 15.80%, 30.93%, 24.21%, and 23.46%, respectively, that showed a decreasing trend from north to south. The extremely vulnerable areas of coastal erosion were mainly located in the coastal area between the Zhongshan Estuary and the Sheyang Estuary. The spatial differentiation of coastal erosion vulnerability in central Jiangsu was the result of the synergistic effect of multiple factors such as coastal dynamics, coastal morphology, and economic and social activities. Among them, tidal slope, land cover, average tidal range, and coastline change rate were the dominant factors for the spatial differentiation of coastal erosion vulnerability.

Key words: coastal erosion, vulnerability, DSAS, geographical detector, driving factor

中图分类号:

P737.1

章志, 刘宪光, 周凯, 林伟波, 冒士凤, 李兰满. 海岸侵蚀脆弱性及驱动因子分析——以江苏中部海岸为例[J]. 海洋学研究, 2023, 41(4): 70-83.

ZHANG Zhi, LIU Xianguang, ZHOU Kai, LIN Weibo, MAO Shifeng, LI Lanman. Vulnerability and driving factors of coastal erosion: A case study of the central coast of Jiangsu[J]. Journal of Marine Sciences, 2023, 41(4): 70-83.

图/表 9

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指标类型	指标	指标编号	权重	指标等级
指标类型	指标	指标编号	权重	极高脆弱	高脆弱	中脆弱	低脆弱	极低脆弱
海岸动力	平均潮差/mm	C₁	0.063	[0.00,274.87]	(274.87~282.98]	(282.98~310.32]	(310.32~475.52]	(475.52~549.27]
	平均有效波高/m	C₂	0.061	(0.53,0.55]	(0.50,0.53]	(0.45,0.50]	(0.38,0.45]	[0.33,0.38]
	海水含沙量/(g·L^-1)	C₃	0.010	[0.20,0.22]	(0.22,0.23]	(0.23,0.26]	(0.26,0.33]	(0.33,0.38]
海岸形态	海岸高程/m	C₄	0.065	[0.00~2.00]	(2.00~6.00]	(6.00~10.00]	(10.00~14.00]	(14.00~22.00]
	海岸线变化速率/(m·a^-1)	C₅	0.036	[-86.56,0.00]	(0.00,137.00]	(137.00,253.94]	(253.94,344.45]	(344.45,539.33]
	等深线变化速率/(m·a^-1)	C₆	0.006	[-169.40, -93.43]	(-93.43, -24.77]	(-24.77, 23.08]	(23.08,111.60]	(111.60,294.70]
	潮滩坡度/%	C₇	0.334	[0.00,1.00]	(1.00~3.00]	(3.00~12.00]	(12.00~35.00]	(35.00~100.00]
	潮滩宽度/km	C₈	0.051	[0.00,3.35]	(3.35,5.85]	(5.85,10.60]	(10.60,19.37]	(19.37,33.63]
社会经济	人口密度/(人·km^-2)	C₉	0.223	(896.75,2 130.39]	(518.31,896.75]	(257.88,518.31]	(93.04,257.88]	[0.00,93.04]
	地表覆盖类型	C₁₀	0.058	人造地表	耕地	裸地	草地、灌木地	湿地、水体
	GDP/(万元·km^-2)	C₁₁	0.028	(3 629.00, 9 194.00]	(2 832.00, 3 629.00]	(2 245.00, 2 832.00]	(1 668.00, 2 245.00]	[1 254.00, 1 668.00]
	人均GDP/万元	C₁₂	0.040	[0.00,5.34]	(5.34,6.55]	(6.55,7.44]	(7.44,9.69]	(9.69,10.64]
	一般公共预算支出/亿元	C₁₃	0.025	[0.00,64.47]	(64.47,81.30]	(81.30,91.68]	(91.68,96.07]	(96.07,108.70]

指标类型	指标	指标编号	权重	指标等级
指标类型	指标	指标编号	权重	极高脆弱	高脆弱	中脆弱	低脆弱	极低脆弱
海岸动力	平均潮差/mm	C₁	0.063	[0.00,274.87]	(274.87~282.98]	(282.98~310.32]	(310.32~475.52]	(475.52~549.27]
	平均有效波高/m	C₂	0.061	(0.53,0.55]	(0.50,0.53]	(0.45,0.50]	(0.38,0.45]	[0.33,0.38]
	海水含沙量/(g·L^-1)	C₃	0.010	[0.20,0.22]	(0.22,0.23]	(0.23,0.26]	(0.26,0.33]	(0.33,0.38]
海岸形态	海岸高程/m	C₄	0.065	[0.00~2.00]	(2.00~6.00]	(6.00~10.00]	(10.00~14.00]	(14.00~22.00]
	海岸线变化速率/(m·a^-1)	C₅	0.036	[-86.56,0.00]	(0.00,137.00]	(137.00,253.94]	(253.94,344.45]	(344.45,539.33]
	等深线变化速率/(m·a^-1)	C₆	0.006	[-169.40, -93.43]	(-93.43, -24.77]	(-24.77, 23.08]	(23.08,111.60]	(111.60,294.70]
	潮滩坡度/%	C₇	0.334	[0.00,1.00]	(1.00~3.00]	(3.00~12.00]	(12.00~35.00]	(35.00~100.00]
	潮滩宽度/km	C₈	0.051	[0.00,3.35]	(3.35,5.85]	(5.85,10.60]	(10.60,19.37]	(19.37,33.63]
社会经济	人口密度/(人·km^-2)	C₉	0.223	(896.75,2 130.39]	(518.31,896.75]	(257.88,518.31]	(93.04,257.88]	[0.00,93.04]
	地表覆盖类型	C₁₀	0.058	人造地表	耕地	裸地	草地、灌木地	湿地、水体
	GDP/(万元·km^-2)	C₁₁	0.028	(3 629.00, 9 194.00]	(2 832.00, 3 629.00]	(2 245.00, 2 832.00]	(1 668.00, 2 245.00]	[1 254.00, 1 668.00]
	人均GDP/万元	C₁₂	0.040	[0.00,5.34]	(5.34,6.55]	(6.55,7.44]	(7.44,9.69]	(9.69,10.64]
	一般公共预算支出/亿元	C₁₃	0.025	[0.00,64.47]	(64.47,81.30]	(81.30,91.68]	(91.68,96.07]	(96.07,108.70]

序号	岸段	验潮站	平均高潮位/cm	平均低潮位/cm	平均潮差/cm
1	灌河口—中山河口	燕尾	445.71	107.13	338.58
2	中山河口—扁担港	滨海港	282.98	51.16	231.82
3	扁担港—射阳河口	射阳河口	274.87	51.94	222.93
4	射阳河口—新洋港	新洋港	310.31	98.55	211.76
5	新洋港—斗龙港	新洋港	310.31	98.55	211.76
6	斗龙港—川东港	大丰港	475.52	89.35	386.17
7	川东港—方塘河口南侧	弶港	549.27	104.89	444.38

序号	岸段	验潮站	平均高潮位/cm	平均低潮位/cm	平均潮差/cm
1	灌河口—中山河口	燕尾	445.71	107.13	338.58
2	中山河口—扁担港	滨海港	282.98	51.16	231.82
3	扁担港—射阳河口	射阳河口	274.87	51.94	222.93
4	射阳河口—新洋港	新洋港	310.31	98.55	211.76
5	新洋港—斗龙港	新洋港	310.31	98.55	211.76
6	斗龙港—川东港	大丰港	475.52	89.35	386.17
7	川东港—方塘河口南侧	弶港	549.27	104.89	444.38

成像时间	行号	列号	传感器	分辨率/m	备注
1997-06-05 T 09:59	119	37	TM	30	计算海岸线变化速率
1997-10-18 T 10:09	120	36	TM	30	计算海岸线变化速率
2017-03-08 T 10:30	119	37	OLI_TIRS	30	计算海岸线变化速率
2017-08-06 T 10:36	120	36	OLI_TIRS	30	计算海岸线变化速率
2021-02-26 T 10:36	120	36	OLI_TIRS	30	计算潮滩坡度
2021-03-03 T 10:31	119	37	OLI_TIRS	30	计算潮滩坡度
2021-03-26 T 10:36	120	36	OLI_TIRS	30	计算潮滩坡度
2021-11-14 T 10:31	119	37	OLI_TIRS	30	计算潮滩坡度