地球科学进展 ›› 2023, Vol. 38 ›› Issue (3): 296 -308. doi: 10.11867/j.issn.1001-8166.2023.006

研究论文 上一篇    下一篇

黄河三角洲的地面沉降分析以及海水淹没预估
宁荣荣 1 , 2( ), 王德 2( ), 田信鹏 2, 张永伟 3 , 4, 周自翔 1, 罗富彬 1   
  1. 1.西安科技大学测绘科学与技术学院,陕西 西安 710054
    2.中国科学院烟台海岸带研究所,山东 烟台 264003
    3.山东省国土空间生态修复中心,山东 济南 250014
    4.自然资源部 黄河三角洲土地利用安全野外科学观测研究站,山东 滨洲 251900
  • 收稿日期:2022-08-13 修回日期:2022-12-09 出版日期:2023-03-10
  • 通讯作者: 王德 E-mail:1270670724@qq.com;dwang@yic.ac.cn
  • 基金资助:
    国家自然科学基金面上项目“黄河三角洲滨海湿地灌丛化过程及其水、盐作用机制”(31870468);山东省自然科学基金面上项目“滨海湿地盐地碱蓬多源遥感监测与空间分异研究”(ZR2020MD013)

Analysis of Ground Settlement in the Yellow River Delta and Projection of Seawater Inundation

Rongrong NING 1 , 2( ), De WANG 2( ), Xinpeng TIAN 2, Yongwei ZHANG 3 , 4, Zixiang ZHOU 1, Fubin LUO 1   

  1. 1.College of Geomatics Science and Technology, Xi’an University of Science and Technology, Xi’an 710054, China
    2.Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai Shandong 264003, China
    3.Shandong Provincial Territorial Spatial Ecological Restoration Center, Jinan 250014, China
    4.Observation and Research Station of Land Use Security in the Yellow River Delta, Ministry of Natural Resources, Binzhou Shandong 251900, China
  • Received:2022-08-13 Revised:2022-12-09 Online:2023-03-10 Published:2023-03-21
  • Contact: De WANG E-mail:1270670724@qq.com;dwang@yic.ac.cn
  • About author:NING Rongrong (1997-), female, Enshi City, Hubei Province, Master student. Research area includes geographic information applications. E-mail: 1270670724@qq.com
  • Supported by:
    the National Natural Science Foundation of China “The process of scrubbing in coastal wetlands of the Yellow River Delta and its mechanism of water and salt action”(31870468);The Natural Science Foundation of Shandong Provincial “Multi-source remote sensing monitoring and spatial differentiation of saline alkaline canopy in coastal wetlands”(ZR2020MD013)

在全球气候变化背景下,不断上升的海平面和地面沉降使黄河三角洲面临着严峻的海水淹没风险,对未来黄河三角洲的可持续发展造成威胁。预估黄河三角洲由于地面沉降而造成的相对海平面变化有助于深入认识当前海水淹没风险,并可以及时采取措施应对。首先,基于小基线集干涉测量技术得到2016年2月至2019年9月的平均沉降速率,利用水准数据进一步提高InSAR结果精度,补偿后最大平均沉降速率达-357 mm/a,结合高分影像的目视解译发现地面沉降的主要原因为地下卤水和油气的开采。其次,结合沉降点分布发现自然沉积作用对沿岸沉降影响还在继续。最后,使用有源算法,结合地面沉降结果和IPCC AR6中SSP2-4.5情景下海平面上升高度的置信区间建立海水淹没模型。模型结果表明:以当前沉降速率,到2030年、2050年和2100年,海水淹没面积占比分别为6.76%~6.84%、10.81%~11.11%和28.71%~30.92%;当沉降速率降至当前速率的50%和25%时,海水淹没面积占比分别为5.84%~5.91%、8.20%~8.40%、19.05%~21.51%和5.34%、6.60%~6.69%、9.89%~11.62%。与绝对海平面上升所带来的威胁相比,对沉降速率的遏制,将会大幅度降低海水淹没风险。海水淹没的土地类型主要为建筑用地、耕地、水体和盐田,随着时间推移,建设用地、耕地和水体的海水淹没速率将不断加快。研究结果可为相关部门用于治理黄河三角洲水土资源开发与灾害防治提供参考。

In the context of global climate change, rising sea levels and ground subsidence are putting the Yellow River Delta at serious risk of seawater inundation, posing a threat to the future sustainable development of the Yellow River Delta. Projecting the relative sea level change in the Yellow River Delta due to ground subsidence can help to gain insight into the current seawater inundation risk and take timely measures to address it. First, the average subsidence rate from February 2016 to September 2019 was obtained based on SBAS-InSAR technology, and the accuracy of the InSAR results was further improved by using level data, with the maximum average subsidence rate reaching -357 mm/a after compensation. Combined with high-resolution imagery, it was found that the main cause of ground subsidence is the extraction of underground brine, oil, and gas. Second, combined with the distribution of subsidence sites, it was found that natural sedimentation continued to influence coastal subsidence. Finally, a seawater inundation model was developed using an active algorithm that combines the results of surface subsidence with confidence intervals for sea level rise under the SSP2-4.5 scenario in the IPCC AR6. The model results show that by 2030, 2050, and 2100, the percentage of seawater inundation area will be 6.76%~6.84%, 10.81%~11.11%, and 28.71%~30.92%, respectively, at the current subsidence rate. When the subsidence rate decreases to 50% and 25% of the current rate, the percentage of seawater inundation area is 5.84%~5.91%, 8.20%~8.40%, and 19.05%~21.51%, and 5.34%, 6.60%~6.69%, and 9.89%~11.62%, respectively. Compared to the threat of absolute sea level rise, the containment of subsidence rates will substantially reduce the risk of seawater inundation. The main types of land inundated by seawater are construction land, arable land, water bodies, and salt flats. The rate of seawater inundation of construction land, arable land, and water bodies will continue to accelerate over time. The results of this study can be used as a reference by relevant authorities to manage the development of soil and water resources as well as for disaster prevention in the Yellow River Delta.

中图分类号: 

图1 Sentinel-1A影像和黄河三角洲位置
Fig. 1 Sentinel-1A image and location of the Yellow River Delta
表1 数据源信息
Table 1 Data source information
表2 数据处理过程
Table 2 Data processing process
图2 线性回归模型结果
Fig. 2 Results of linear regression model
图3 水准点对InSAR结果补偿前后对比
Fig. 3 Comparison of before and after compensation of InSAR results by level points
图4 补偿后黄河三角洲20162019年平均垂直形变速率
A~E代表5个典型研究区域
Fig. 4 Average vertical deformation rate of the Yellow River Delta from 2016-2019 after compensation
A~E represent five typical study areas
图5 黄河三角洲5个典型研究区的累计沉降量时序分析图
Fig. 5 Time series analysis of cumulative subsidence in five typical study areas in the Yellow River Delta
图6 黄河三角洲的盐田分布及其卫星图
Fig. 6 Distribution of salt fields in the Yellow River Delta and its satellite map
图7 黄河三角洲土壤质地图
Fig. 7 Soil texture of the Yellow River Delta
图8 黄河三角洲的沉降点分布
Fig. 8 Distribution of subsidence points in the Yellow River Delta
图9 黄河三角洲插值后的平均形变速率图
Fig. 9 Interpolated average deformation rate map of the Yellow River Delta
表3 不同情景下的海水淹没统计表
Table 3 Seawater inundation statistics for different scenarios
图10 不同沉降速率情景下黄河三角洲的海水淹没区分布
Fig. 10 Distribution of seawater inundation areas in the Yellow River Delta under different sedimentation rate scenarios
图11 黄河三角洲的土地利用与海水淹没关系图
(a)土地利用类型;(b)不同土地利用类型淹没面积,横坐标表示在2030年、2050年和2100年的地面沉降速率不变,速率降至当前的50%和25%时的土地类型淹没类型变化
Fig. 11 The relationship between land use and seawater inundation in the Yellow River Delta
(a) Type of land use;(b) Area inundated by different land use types,the horizontal coordinates in Figure 11(b) indicate the change in land type inundation type for constant ground subsidence rate, rate reduction to 50% of current and rate reduction to 25% of current in 2030, 2050 and 2100
图12 19502021年利津水文站水沙量统计
Fig. 12 Water and sediment volume statistics of Lijin hydrological station from 1950 to 2021
1 QIN Tongchun, CHENG Guoming, WANG Haigang. The latest progress of research on land subsidence abroad and its inspiration to China[J]. Geological Bulletin of China, 2018, 37(): 503-509.
秦同春, 程国明, 王海刚. 国际地面沉降研究进展的启示[J]. 地质通报, 2018, 37(): 503-509.
2 LIU Y L, LIU J Q, XIA X F, et al. Land subsidence of the Yellow River Delta in China driven by river sediment compaction[J]. Science of the Total Environment, 2021, 750. DOI:10.1016/j.scitotenv.2020.142165 .
3 CAVALIÉ O, SLADEN A, KELNER M. Detailed quantification of delta subsidence, compaction and interaction with man-made structures: the case of the NCA airport, France[J]. Natural Hazards and Earth System Sciences, 2015, 15(9): 1 973-1 984.
4 HIGGINS S A, OVEREEM I, STECKLER M S, et al. InSAR measurements of compaction and subsidence in the Ganges-Brahmaputra Delta, Bangladesh[J]. Journal of Geophysical Research: Earth Surface, 2014, 119(8): 1 768-1 781.
5 MEEHL G A, WASHINGTON W M, COLLINS W D, et al. How much more global warming and sea level rise? [J]. Science, 2005, 307(5 716): 1 769-1 772.
6 ERICSON J P, VÖRÖSMARTY C J, LAWRENCE D S, et al. Effective sea-level rise and deltas: causes of change and human dimension implications[J]. Global and Planetary Change, 2006, 50(1/2): 63-82.
7 WANG G Y, LI P, LI Z H, et al. Coastal dam inundation assessment for the Yellow River Delta: measurements, analysis and scenario[J]. Remote Sensing, 2020, 12(21). DOI:10.3390/rs12213658 .
8 PAOLA C, TWILLEY R R, EDMONDS D A, et al. Natural processes in delta restoration: application to the Mississippi Delta[J]. Annual Review of Marine Science, 2011, 3: 67-91.
9 XIAO Hongfei, WANG Dong, BIAN Zhigang. Study on the characteristics of sea level change in the Bohai and Yellow Seas based on ERA5 dataset[J]. Transactions of Oceanology and Limnology, 2020(5): 9-15.
肖鸿飞, 王冬, 边志刚. 基于ERA5数据集的黄渤海海平面变化特征研究[J]. 海洋湖沼通报, 2020(5): 9-15.
10 YU Yifa. Advance of the researches on the variations of Mean-Sea-Level (MSL) in the coastal waters of China[J]. Journal of Ocean University of Qingdao, 2004, 34(5): 713-719.
于宜法. 中国近海海平面变化研究进展[J]. 中国海洋大学学报(自然科学版), 2004, 34(5): 713-719.
11 ZHANG Jie. Sea level change in coastal China Seas during the 21st based on SSPs scenarios[D]. Zhoushan: Zhejiang Ocean University, 2022.
张洁. 基于SSPs情景下21世纪中国近海海平面变化[D]. 舟山: 浙江海洋大学, 2022.
12 HU Zhibo, GUO Jinyun, TAN Zhengguang, et al. Sea level variation in Hong Kong determined with TOPEX/Poseidon and tide gauge[J]. Journal of Geodesy and Geodynamics, 2014, 34(4): 56-59.
胡志博, 郭金运, 谭争光, 等. 由TOPEX/Poseidon和验潮站监测香港海平面变化[J]. 大地测量与地球动力学, 2014, 34(4): 56-59.
13 MU D P, XU T H, XU G C. Detecting coastal ocean mass variations with GRACE mascons[J]. Geophysical Journal International, 2019, 217(3): 2 071-2 080.
14 XU Tianhe, YANG Yuanyuan, MU Dapeng, et al. Causes of coastal sea level change[J]. Geomatics and Information Science of Wuhan University, 2022, 47(10): 1 750-1 757.
徐天河, 杨元元, 穆大鹏, 等. 近海海平面变化成因分析[J]. 武汉大学学报(信息科学版), 2022, 47(10): 1 750-1 757.
15 XU Tianhe, MU Dapeng, YAN Haoming, et al. The causes of contemporary sea level rise over recent two decades:progress and challenge[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(7):1 294-1 305.
徐天河, 穆大鹏, 闫昊明, 等. 近 20 年海平面变化成因研究进展及挑战 [J].测绘学报, 51(7): 1 294-1 305.
16 ZHANG Tong, YU Yongqiang, XIAO Cunde, et al. Interpretation of IPCC AR6 report: monitoring and projections of global and regional sea level change[J]. Climate Change Research, 2022, 18 (1): 12-18.
张通, 俞永强, 效存德, 等. IPCC AR6解读:全球和区域海平面变化的监测和预估[J]. 气候变化研究进展, 2022, 18 (1): 12-18.
17 de WIT K, LEXMOND B R, STOUTHAMER E, et al. Identifying causes of urban differential subsidence in the Vietnamese Mekong delta by combining InSAR and field observations[J]. Remote Sensing, 2021, 13(2). DOI:10.3390/rs13020189 .
18 XU B, FENG G C, LI Z W, et al. Coastal subsidence monitoring associated with land reclamation using the point target based SBAS-InSAR method: a case study of Shenzhen, China[J]. Remote Sensing, 2016, 8(8). DOI:10.3390/rs8080652 .
19 ERBAN L E, GORELICK S M, ZEBKER H A. Groundwater extraction, land subsidence, and sea-level rise in the Mekong Delta, Vietnam[J]. Environmental Research Letters, 2014, 9(8). DOI:10.1088/1748-9326/9/8/084010 .
20 HIGGINS S A. Review: advances in delta-subsidence research using satellite methods[J]. Hydrogeology Journal, 2016, 24(3): 587-600.
21 HUSSAIN M A, CHEN Z L, SHOAIB M, et al. Sentinel-1A for monitoring land subsidence of coastal city of Pakistan using Persistent Scatterers In-SAR technique[J]. Scientific Reports, 2022, 12. DOI:10.1038/s41598-022-09359-7 .
22 GEBREMICHAEL E, SULTAN M, BECKER R, et al. Assessing land deformation and sea encroachment in the Nile delta: a radar interferometric and inundation modeling approach[J]. Journal of Geophysical Research: Solid Earth, 2018, 123(4): 3 208-3 224.
23 YAO Wenyi, GAO Yajun, ZHANG Xiaohua. Relationship evolution between runoff and sediment transport in the Yellow River and related scientific issues[J]. Science of Soil and Water Conservation, 2020, 18(4): 1-11.
姚文艺, 高亚军, 张晓华. 黄河径流与输沙关系演变及其相关科学问题[J]. 中国水土保持科学, 2020, 18(4): 1-11.
24 CHENG Xia, ZHANG Yonghong, DENG Min, et al. Analysis of recent surface deformation of the Yellow River Delta based on Sentinel-1A satellite[J]. Science of Surveying and Mapping, 2020, 45(2): 43-51.
程霞, 张永红, 邓敏, 等. Sentinel-1A卫星的黄河三角洲近期地表形变分析[J]. 测绘科学, 2020, 45(2): 43-51.
25 WANG H J, WU X, BI N S, et al. Impacts of the dam-orientated water-sediment regulation scheme on the lower reaches and delta of the Yellow River (Huanghe): a review[J]. Global and Planetary Change, 2017, 157: 93-113.
26 WANG S, FU B J, PIAO S L, et al. Reduced sediment transport in the Yellow River due to anthropogenic changes[J]. Nature Geoscience, 2016, 9(1): 38-41.
27 LIU Y, HUANG H J. Characterization and mechanism of regional land subsidence in the Yellow River Delta, China[J]. Natural Hazards, 2013, 68(2): 687-709.
28 ZHANG Y, LIU Y L, ZHANG X Y, et al. Correlation analysis between land-use/cover change and coastal subsidence in the Yellow River Delta, China: reviewing the past and prospecting the future[J]. Remote Sensing, 2021, 13(22). DOI:10.3390/rs13224563 .
29 WANG S Y, ZHANG G, CHEN Z W, et al. Surface deformation extraction from small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) using coherence-optimized baseline combinations[J]. GIScience & Remote Sensing, 2022, 59(1): 295-309.
30 BERARDINO P, FORNARO G, LANARI R, et al. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11): 2 375-2 383.
31 ZHAO Xiuying, WANG Yaoqiang, LI Hongyu, et al. Design and implementation of seed spread algorithm for calculations of source flood submerge area based on DEM[J]. Science & Technology Review, 2012, 30(8): 61-64.
赵秀英, 王耀强, 李洪玉, 等. 基于DEM的有源淹没算法设计与实现: 以种子蔓延法为例[J]. 科技导报, 2012, 30(8): 61-64.
32 FOX-KEMPER B, HEWITT H T, XIAO C, et al. Ocean, cryosphere and sea level change [M]// IPCC. Climate change 2021: the physical science basis. Cambridge: Cambridge University Press, 2021.
33 YANG Jie, HUANG Xin. The 30 m annual land cover and its dynamics in China from 1990 to 2019[J]. Earth System Science Data, 2021, 13: 3 907-3 925.
34 GE Daqing. Research on key technology of InSAR monitoring of regional land subsidence[D]. Beijing: China University of Geosciences (Beijing), 2013.
葛大庆. 区域性地面沉降InSAR监测关键技术研究[D]. 北京: 中国地质大学(北京), 2013.
35 HOU Zhandong. Comparison and analysis of the spatial interpolation methods of the urban ground subsidence monitoring data[J]. Geospatial Information, 2020, 18(8): 106-109.
侯占东. 城市地面沉降监测数据的插值方法对比分析[J]. 地理空间信息, 2020, 18(8): 106-109.
36 DAWSON R, HALL J, SAYERS P, et al. Sampling-based flood risk analysis for fluvial dike systems[J]. Stochastic Environmental Research and Risk Assessment, 2005, 19(6): 388-402.
37 LIU Xiaoshuai, TAO Qiuxiang, NIU Chong, et al. Comparative analysis and verification of DInSAR and SBAS InSAR in mining subsidence monitoring[J]. Progress in Geophysics, 2022, 37(5): 1 825-1 833.
刘晓帅, 陶秋香, 牛冲, 等. DInSAR与SBAS InSAR矿区地面沉降监测能力对比分析与验证[J]. 地球物理学进展, 2022, 37(5): 1 825-1 833.
38 ZHANG Yi. Spatial-temporal variations and distribution characteristics in subsidence due to the natural consolidation and compaction of sediment in the Yellow River Delta, China[D]. Qingdao: Institute of Oceanology, Chinese Academy of Sciences, 2018.
张翼. 黄河三角洲浅层沉积物固结压实的时空变化及分布特征[D]. 青岛:中国科学院海洋研究所, 2018.
39 HIGGINS S, OVEREEM I, TANAKA A, et al. Land subsidence at aquaculture facilities in the Yellow River Delta, China[J]. Geophysical Research Letters, 2013, 40(15): 3 898-3 902.
40 HERRERA-GARCÍA G, EZQUERRO P, TOMÁS R, et al. Mapping the global threat of land subsidence[J]. Science, 2021, 371(6 524): 34-36.
41 WANG H J, BI N S, SAITO Y, et al. Recent changes in sediment delivery by the Huanghe (Yellow River) to the sea: causes and environmental implications in its estuary[J]. Journal of Hydrology, 2010, 391(3/4): 302-313.
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