Terrestrial Water Storage and Crustal Vertical Variation in Xinjiang Region,China Using Independent Component Analysis
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摘要:
中国新疆地区水文气候变化复杂,其水储量变化及其负荷形变特征的精确提取极为重要。采用卫星重力数据GRACE(gravity recovery and climate experiment）反演新疆地区2010—2014年陆地水储量变化,利用独立成分分析法（independent component analysis,ICA）分解时空模式,提取时空特征信号。在此基础上,反演陆地水负荷迁移引起的地壳垂向变化,引入重力位系数与负荷勒夫数一阶项改正,回加非潮汐大气与海洋信号,结合尺度因子法校正GRACE反演结果,引入全球降水气候计划月降水资料分析形变影响,将其与测区12座连续运行参考站形变位移进行定量比较,重点分析各测站陆地水负荷信号与全球导航卫星系统（global navigation satellite system,GNSS）垂直位移的相关关系。结果表明,经ICA方法分解的新疆地区陆地水储量呈现多时间尺度特征,表现为明显的周年与长期变化；周年信号在西部帕米尔高原附近尤为显著；长期变化以逐年减少为主,在乌鲁木齐西部、天山一带信号较强；总体上,陆地水负荷垂直形变的时间序列波动幅度相对较小,幅值为－1.5~1.5 mm,与WGHM（WaterGAP global hydrology model）模型结果比较一致；形变时序与降水量变化除了存在明显的时间滞后之外,总体趋势相吻合；经非潮汐大气与海洋信号(non-tidal atmospheric and ocean model,GAC)改正后,GRACE结果与GNSS垂直位移的相关程度有所提升,各测站相关系数为0.63~0.91,加权均方根误差达16.18%~58.97%,相位延迟约为0.5~2个月。该研究方法可揭示新疆地区更为精细的水文信号特征,为区域参考框架精确维护提供重要技术支撑。
Abstract:ObjectivesIn recent years, the climate change in Xinjiang region,China is complex. It is of great significance to study the terrestrial water storage (TWS) and its load deformation for the accurate maintenance of the regional reference frame.
MethodsThe satellite gravity data GRACE（gravity recovery and climate experiment）was used to invert the changes of land water storage in Xinjiang region from 2010 to 2014, and the independent component analysis was used to decompose it into spatiotemporal models, and the spatial characteristics of multiple time scales were analyzed. On this basis, the correction on the first-order of gravity potential coefficient and load Love number is carried out, the correction of the non-tidal atmospheric and ocean model (GAC) from GRACE is introduced to obtain the vertical change of the crust caused by the migration of the land water load. The GRACE inversion results are corrected by scale factor method derived from WaterGAP global hydrology model (WGHM). The influence of deformation is analyzed by introducing monthly precipitation data from global precipitation climatology project. And the deformation displacements of the 13 continuously operating reference system stations in the survey area are quantitatively compared. The correlation between TWS load signal of each station and the annual vertical displacement of global navigation satellite system (GNSS) is analyzed.
ResultsThe results show that TWS in Xinjiang region presents multi-time scale characteristics, with obvious annual variation and long-term trend. The annual change is particularly significant near the western Pamirs Plateau, and the trend term is reflected in the long-term decrease year by year. The signal is relatively strong in the western Urumqi and Tianshan Mountains. In general, the change of land water load causes the vertical displacement of the crust in the study area, and the time series shows a small fluctuation with an amplitude of -1.5-1.5 mm, which is consistent with the deformation results of WGHM model. In addition to the obvious time lag, the time series of TWS load deformation and precipitation change are consistent with the overall trend. After GAC correction, the consistency between GRACE results and GNSS vertical displacement was enhanced, and the correlation coefficient and weighted root mean square（WRMS）were significantly improved. The correlation coefficient of each station was 0.63-0.91, and WRMS was 16.18%-58.97%.
ConclusionsThe research method in this paper can reveal more detailed hydrological signal characteristics in Xinjiang region, and the research results can provide important technical support for accurate maintenance of regional reference frame.
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感谢德国法拉克福大学自然地理研究所提供的WGHM 2.2c全球陆地水储量模型。
http://ch.whu.edu.cn/cn/article/doi/10.13203/j.whugis20220573
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图 2 ICA分解的新疆陆地水储量变化成分时间模式
Figure 2. Time Pattern of Terrestrial Water Storage Change Components in Xinjiang Region Decomposed by ICA
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图 3 ICA分解的新疆陆地水储量变化成分空间模式
Figure 3. Spatial Pattern of Terrestrial Water Storage Change Components in Xinjiang Region Decomposed by ICA
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图 4 尺度因子校正后的新疆地区陆地水负荷垂直形变
Figure 4. Vertical Deformation from Terrestrial Water Load in Xinjiang Region from GRACE After Scale Factor Correction
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图 5 GRACE监测的新疆地区陆地水负荷垂直形变与月降水量时间序列
Figure 5. Time Series of Vertical Deformation from Terrestrial Water Load Depending on GRACE and Monthly Preciptation in Xinjiang Region
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图 6 GRACE监测结果回加GAC改正前后形变时序与GNSS垂向位移比较
Figure 6. Comparison of Deformation Sequence and GNSS Elevation Coordinate Sequence Before and After GAC Correction in GRACE Monitoring Results
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图 7 GAC改正前后GRACE结果与GNSS垂直形变的相关系数与WRMS减小比值
Figure 7. Correlation Coefficient and WRMS Decrease Rate Between GRACE Results and GNSS Vertical Deformation Before and After GAC Correction
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图 8 GRACE监测结果与GNSS垂直形变周年变化
Figure 8. Annual Variation of Load Vertical Deformation from GRACE and GNSS Elevation Series
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图 9 GRACE监测与GNSS垂直位移的相位差
Figure 9. Phase Difference Between GRACE Monitoring Results and GNSS Vertical Displacement Results
表 1 新疆地区12个CORS站及其位置坐标
Table 1 The Names and Location Coordinates of 12 CORS Stations in Xinjiang Region
测站名 概略坐标 测站名 概略坐标 XJBC 78.77°E,39.81°N XJBE 86.85°E,47.69°N XJDS 84.88°E,44.31°N XJFY 89.53°E,46.99°N XJHT 79.04°E,37.16°N XJJJ 94.33°E,42.84°N XJML 90.29°E,43.80°N XJQH 90.97°E,46.15°N XJSH 86.10°E,44.20°N XJSS 90.25°E,42.89°N XJTZ 83.65°E,38.96°N XJWQ 80.99°E,44.96°N 
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表 2 GRACE监测的新疆地区地表负荷垂直形变与GNSS垂向位移之间的相关性指标
Table 2 Correlation Index Between Load Vertical Deformation Derived from GRACE and GNSS
测站 陆地水负荷形变 陆地水+非潮汐大气海洋负荷形变 相关系数 WRMS减小比值/% 相关系数 WRMS减小比值/% XJBC -0.68 -17.83 0.76 30.09 XJBE 0.27 3.63 0.90 46.34 XJDS -0.24 -10.56 0.81 41.12 XJFY 0.01 -3.42 0.81 39.31 XJHT -0.79 -22.79 0.70 22.09 XJJJ -0.10 -1.56 0.73 29.31 XJML -0.42 -5.37 0.79 35.20 XJQH -0.30 -11.21 0.68 25.80 XJSH -0.36 -5.58 0.79 29.02 XJSS -0.39 -6.88 0.91 58.97 XJTZ -0.60 -11.82 0.92 49.25 XJWQ -0.36 -23.10 0.63 16.18
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表 3 GRACE监测新疆地区地表负荷垂直形变与GNSS垂直位移周年变化的振幅与相位
Table 3 Annual Amplitude and Phase Between GRACE with GAC Correction and GNSS Vertical Time Series
测站 GRACE GNSS GRACE－GNSS 周年振幅/mm 周年相位/d 周年振幅/mm 周年相位/d 相位差/d XJBC 3.53±0.05 -124±2 6.71±0.01 -89±1 35±3 XJBE 6.02±0.05 -138±1 9.87±0.01 -119±1 19±0 XJDS 5.08±0.03 -130±1 5.74±0.01 -99±1 31±0 XJFY 5.32±0.06 -132±2 7.85±0.03 -102±1 30±1 XJHT 2.01±0.06 -95±5 5.36±0.01 -84±1 11±4 XJJJ 4.30±0.05 -104±2 8.08±0.03 -63±1 41±1 XJML 4.72±0.06 -116±2 8.26±0.02 -80±1 36±1 XJQH 4.67±0.06 -126±2 5.98±0.02 -78±1 48±1 XJSH 4.70±0.04 -127±1 11.04±0.03 -91±1 36±0 XJSS 4.79±0.05 -112±1 5.11±0.01 -96±1 16±0 XJTZ 3.73±0.03 -98±1 6.07±0.02 -91±1 7±0 XJWQ 5.01±0.04 -138±1 5.32±0.01 -88±1 50±0
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