融合卫星与地面数据研究京津冀地区弹性骨架储水系数

doi:10.11947/j.AGCS.2023.20210454

摘要/Abstract

摘要： 地下水的过量开采已经对京津冀平原地区的土层结构造成严重的破坏。本文旨在了解京津冀地区目前土层结构的健康状况,并对地下水的适宜取水位置提出建议。首先,利用GRACE-FO数据与MCTSB-InSAR技术,分别提取了2017—2019年的京津冀地区的地下水变化时序和沉降变化时序。然后,利用邻域平均方法,使得二者数据空间分辨率一致,并首次获得了京津冀地区2017、2018和2019年的弹性骨架储水系数图。最后,结合京津冀地区的地形地貌、土壤类型及各年内降雨和温度情况,对弹性骨架储水系数图进行了时空维度对比分析。研究发现,京津冀地区土层结构的平均情况正在逐渐变好,但是该地区东南方向土层结构还在继续恶化;京津冀西北地区的土层结构相对于东南地区更适合开采地下水。

关键词: GRACE-FO, 地下水, 地面沉降, InSAR, 弹性骨架储水系数

Abstract: Due to over-exploitation of groundwater, the soil structure in the Beijing-Tianjin-Hebei Plain has been severely damaged.This study was taken to understand the health status of the current soil structure and give suggestion to the location that suitable for obtaining groundwater in the Beijing-Tianjin-Hebei area. First of all, based on GRACE-FO data and MCTSB-InSAR technology, the groundwater change sequence and subsidence change sequence of the Beijing-Tianjin-Hebei region from 2017 to 2019 are extracted respectively. Then, the neighborhood averaging method was used to achieve the same spatial resolution of the two data,and the elastic skeleton water storage coefficient maps of the Beijing-Tianjin-Hebei region in 2017, 2018 and 2019 were obtained for the first time. Finally, combined with the topography, soil types, rainfall and temperature conditions in each year in the Beijing-Tianjin-Hebei region, a comparative analysis of the spatial and temporal dimensions of the elastic skeleton water storage coefficient map is carried out. The study found that the average soil structure in the Beijing-Tianjin-Hebei region is gradually getting better, but the soil structure in the southeast of the region continues to deteriorate; the soil structure in the northwest of the Beijing-Tianjin-Hebei region is more suitable for exploiting groundwater than the southeast region.

Key words: GRACE-FO, groundwater, land subsidence, InSAR, elastic skeleton storage coefficient

中图分类号:

P237

张玉鹏, 张永红, 吴宏安, 刘青豪, 魏钜杰, 康永辉. 融合卫星与地面数据研究京津冀地区弹性骨架储水系数[J]. 测绘学报, 2023, 52(4): 660-669.

ZHANG Yupeng, ZHANG Yonghong, WU Hongan, LIU Qinghao, WEI Jujie, KANG Yonghui. Study on elastic skeleton storage coefficient in Beijing-Tianjin-Hebei region combining satellite and ground data[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(4): 660-669.

参考文献

[1] 于海若, 宫辉力, 陈蓓蓓, 等. 京津冀地区地面沉降研究进展与思考[J]. 测绘科学, 2020, 45(4): 125-133, 141. YU Hairuo, GONG Huili, CHEN Beibei, et al. The advance and consideration of land subsidence in Beijing-Tianjin-Hebei region[J]. Science of Surveying and Mapping, 2020, 45(4): 125-133, 141.
[2] 宁晓刚, 王浩, 林祥国, 等. 京津冀城市群1990—2015年城区时空扩展监测与分析[J]. 测绘学报, 2018, 47(9): 1207-1215.DOI: 10.11947/j.AGCS.2018.20170414. NING Xiaogang, WANG Hao, LIN Xiangguo, et al. Spatio-temporal urban sprawl monitoring and analysis over Beijing-Tianjin-Hebei urban agglomeration during 1990—2015[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(9): 1207-1215.DOI: 10.11947/j.AGCS.2018.20170414.
[3] RILEY F S. Analysis of borehole extensometer data from central California[C]//Proceedings of 1969 Tokyo Symposium. Tokyo, Japan: IAHS, 1969.
[4] 刘欣, 商安荣, 贾勇帅, 等. PS-InSAR和SBAS-InSAR在城市地表沉降监测中的应用对比[J]. 全球定位系统, 2016, 41(2): 101-105. LIU Xin, SHANG Anrong, JIA Yongshuai, et al. Application contrast of PS-InSAR and SBAS-InSAR in urban surface subsidence monitoring[J]. GNSS World of China, 2016, 41(2): 101-105.
[5] LIU Yong, HUANG Haijun. Characterization and mechanism of regional land subsidence in the Yellow River Delta, China[J]. Natural Hazards, 2013, 68(2): 687-709.
[6] MILLER M M, SHIRZAEI M. Spatiotemporal characterization of land subsidence and uplift in Phoenix using InSAR time series and wavelet transforms[J]. Journal of Geophysical Research: Solid Earth, 2015, 120(8): 5822-5842.
[7] 朱建军, 李志伟, 胡俊. InSAR变形监测方法与研究进展[J]. 测绘学报, 2017, 46(10): 1717-1733. DOI: 10.11947/j.AGCS.2017.20170350. ZHU Jianjun, LI Zhiwei, HU Jun. Research progressand methods of InSAR for deformation monitoring[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(10): 1717-1733.DOI: 10.11947/j.AGCS.2017.20170350.
[8] 陆燕燕. 基于多源SAR数据的苏锡常地区地面沉降监测与影响因素分析[J]. 测绘学报, 2019, 48(7): 938.DOI: 10.11947/j.AGCS.2019.20180345. LU Yanyan. Land subsidence monitoring and influencing factors analysis in Suzhou, Wuxi and Changzhou based on multi-source SAR data[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(7): 938.DOI: 10.11947/j.AGCS.2019.20180345.
[9] 刘媛媛. 不同尺度综合地表形变InSAR时序监测与机理分析[J]. 测绘学报, 2020, 49(7): 935.DOI: 10.11947/j.AGCS.2020.20190339. LIU Yuanyuan. InSAR time series monitoring and mechanism analysis of comprehensive surface deformation at different scales[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(7): 935.DOI: 10.11947/j.AGCS.2020.20190339.
[10] 何秀凤, 高壮, 肖儒雅, 等. 多时相Sentinel-1A InSAR的连盐高铁沉降监测分析[J]. 测绘学报, 2021, 50(5): 600-611.DOI: 10.11947/j.AGCS.2021.20200226. HE Xiufeng, GAO Zhuang, XIAO Ruya, et al. Monitoring and analysis of subsidence along Lian-Yan railway using multi-temporal Sentinel-1A InSAR[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(5): 600-611.DOI: 10.11947/j.AGCS.2021.20200226.
[11] 刘青豪, 张永红, 邓敏, 等. 大范围地表沉降时序深度学习预测法[J]. 测绘学报, 2021, 50(3): 396-404.DOI: 10.11947/j.AGCS.2021.20200038. LIU Qinghao, ZHANG Yonghong, DENG Min, et al. Time series prediction method of large-scale surface subsidence based on deep learning[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(3): 396-404.DOI: 10.11947/j.AGCS.2021.20200038.
[12] 俞晓莹. 改进的SBAS地表形变监测及地下水应用研究[D]. 长沙: 中南大学, 2012. YU Xiaoying. Improved SBAS surface deformation monitoring and groundwater application research[D].Changsha: Central South University, 2012.
[13] CHEN M, TOMÁS R, LI Z, et al. Imaging land subsidence induced by groundwater extraction in Beijing (China) using satellite radar interferometry[J]. Remote Sensing, 2016, 8(6): 468.
[14] 张子文. 时序InSAR地面沉降监测与地下水-地面沉降预测模型参数反演[D]. 阜新: 辽宁工程技术大学, 2017. ZHANG Ziwen. Time series InSAR land subsidence monitoring and parameter inversion of groundwater-land subsidence prediction model[D].Fuxin: Liaoning Technical University, 2017.
[15] 冯伟, Jean-Michel LEMOINE, 钟敏, 等. 利用重力卫星GRACE监测亚马逊流域2002—2010年的陆地水变化[J]. 地球物理学报, 2012, 55(3): 814-821. FENG Wei, LEMOINE J M, ZHONG Min, et al. Terrestrial water storage changes in the Amazon Basin measured by GRACE during 2002—2010[J]. Chinese Journal of Geophysics, 2012, 55(3): 814-821.
[16] 郭飞霄, 孙中苗, 任飞龙, 等. GRACE时变重力场各向异性高斯组合滤波方法[J]. 测绘学报, 2019, 48(7): 898-907.DOI: 10.11947/j.AGCS.2019.20180365. GUO Feixiao, SUN Zhongmiao, REN Feilong, et al. Non-isotropic Gaussian combination filtering method of GRACE time-variable gravity[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(7): 898-907.DOI: 10.11947/j.AGCS.2019.20180365.
[17] LIU Zhen, LIU Pangwei, MASSOUD E, et al. Monitoring groundwater change in California's central valley using sentinel-1 and GRACE observations[J]. Geosciences, 2019, 9(10): 436.
[18] 吴红波. 基于ICESat-GLAS和GRACE卫星遥感资料的高亚洲冰川物质平衡变化研究[J]. 测绘学报, 2020, 49(4): 534.DOI: 10.11947/j.AGCS.2020.20190187. WU Hongbo. Study on the change of mass balance of glaciers in high Asia based on ICESat-GLAS and GRACE satellite remote sensing data[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(4): 534.DOI: 10.11947/j.AGCS.2020.20190187.
[19] 秦毅坤, 王泽根, 范东明. 青藏高原区域水储量变化的GRACE RL06和TRMM联合反演[J]. 测绘学报, 2020, 49(10): 1285-1294.DOI: 10.11947/j.AGCS.2020.20200026. QIN Yikun, WANG Zegen, FAN Dongming. The joint inversion of regional water reserve changes in the Qinghai-Tibet Plateau based on GRACE RL06 and TRMM data[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(10): 1285-1294.DOI: 10.11947/j.AGCS.2020.20200026.
[20] SUN Zhangli, LONG Di, YANG Wenting, et al. Reconstruction of GRACE data on changes in total water storage over the global land surface and 60 basins[J]. Water Resources Research, 2020, 56(4): e2019WR026250.
[21] HUSSAIN D, KHAN A A, HASSAN S N U, et al. A time series assessment of terrestrial water storage and its relationship with hydro-meteorological factors in Gilgit-Baltistan region using GRACE observation and GLDAS-Noah model[J]. SN Applied Sciences, 2021, 3(5): 533.
[22] 马震, 谢海澜, 林良俊, 等. 京津冀地区国土资源环境地质条件分析[J]. 中国地质, 2017, 44(5): 857-873. MA Zhen, XIE Hailan, LIN Liangjun, et al. The environmental geological conditions of Land resources in the Beijing-Tianjin-Hebei region[J]. Geology in China, 2017, 44(5): 857-873.
[23] WATKINS M M, WIESE D N, YUAN D N, et al. Improved methods for observing Earth's time variable mass distribution with GRACE using spherical cap mascons[J]. Journal of Geophysical Research: Solid Earth, 2015, 120(4): 2648-2671.
[24] 郭飞霄, 孙中苗, 任飞龙, 等. 不同Mascon模型解比较分析[J]. 大地测量与地球动力学, 2019, 39(10): 1022-1026. GUO Feixiao, SUN Zhongmiao, REN Feilong, et al. Comparison and analysis of different mascon model results[J]. Journal of Geodesy and Geodynamics, 2019, 39(10): 1022-1026.
[25] WIESEDN, LANDERERFW, WATKINS M M. Quantifying and reducing leakage errors in the JPL RL05M GRACE mascon solution[J]. Water Resources Research, 2016, 52(9): 7490-7502.
[26] WANG R, LUO Y, YANG Y, et al. Characterization of land subsidence induced by groundwater withdrawals in Wenyu River alluvial fan, Beijing, China[J]. Proceedings of the International Association of Hydrological Sciences, 2015, 372: 481-484.
[27] 李晓龙. MCTSB-InSAR沉降监测技术及其应用[D]. 阜新: 辽宁工程技术大学, 2017. LI Xiaolong. MCTSB-InSAR settlement monitoring technology and its application[D]. Fuxin: Liaoning Technical University, 2017.
[28] HOFFMANN J, ZEBKER H A. The application of satellite radar interferometry to the study of land subsidence over developed aquifer systems[M].Stanford:Stanford University, 2003.