利用重力异常匹配技术实现潜艇导航

潜艇的惯性导航误差是随时间积累的,利用重力异常数据进行辅助导航可以对惯性导航的漂移误差进行校正.首先利用2′×2′重力异常数据库作为基础信息,结合Kalman滤波算法对某区域进行了模拟计算,模拟过程采用了增益系数和信息更新序列的新方法进行Kalman 滤波的处理,结果表明在重力异常变化幅度较大的地区,重力异常可以进行潜艇的辅助导航.     

优化滤波方法及其在中国大陆布格重力异常数据处理中的应用

在优选延拓法的理论基础上,研究提出基于格林等效层概念和维纳滤波器的优化滤波法,用于对重力异常数据进行去噪和分离.与传统向上延拓法和优选延拓法相比,优化滤波法分离异常与延拓高度无关,不需要已知延拓高度,具有一定的优势.理论重力模型数据的去噪和异常分离试验表明优化滤波法有效,异常分离效果优于传统向上延拓法和带通滤波法.利用优化滤波法对中国大陆重力异常数据去噪和异常分离,得到有效的布格重力异常和区域重力异常.以中国大陆深地震探测推断的莫霍面深度信息为约束,对区域重力异常数据进行密度界面约束反演,得到中国大陆莫霍面深度分布.本文方法为中国大陆深部探测和区域构造研究提供一定的技术支撑.     

高斯滤波在处理GRACE数据中的模拟研究：西藏拉萨的重力变化率

本文利用重力卫星GRACE数据计算了青藏高原的空间重力分布,以及用不同高斯滤波半径得到的拉萨重力变化率.结果显示重力变化率的估算依赖于高斯滤波器空间半径的大小.由GRACE得到的重力变化速率同地表面绝对重力测量得到的值吻合很好,即当滤波器空间半径趋近0时,GRACE估算的重力变化率趋于地表面测量值.接下来对于地面信号应用不同高斯滤波器空间半径进行了数值模拟计算.结果显示一个物理信号的估算依赖于滤波半径,如果计算区域等于或小于质量分布区域,尤其是均匀分布的质量,不管使用什么样的滤波半径,都给出一个相当准确的结果.如果计算区域大于质量分布区域,由于截断引起的信号泄漏,计算会有很大的误差.如果质量异常很小,除非滤波半径十分小,否则很难从空间观测辨别它.如果计算区域在质量分布区域之外,计算结果几乎为0,尤其对较小的滤波半径.高斯滤波器的这些性质在应用GRACE数据中具有重要意义.我们进一步讨论了引起拉萨重力变化的物质来源,表明拉萨重力变化率不是由当前冰川融化（PDIM）（或者小冰期,LIA）效应引起的,因为在拉萨及其周边没有冰川融化发生.重力变化率主要归因于与印度板块碰撞有关的构造变形,而发生的地表位移、地表剥蚀和GIA作用是不容忽视的.     

利用GRACE数据反演日本Mw9.0地震区域黏滞性

利用CSR(Center for Space Research)发布的GRACE RL05月重力场模型数据,通过水文模型GLDAS(Global Land Data Assimilation System)和CPC(Climate Prediction Center)扣除土壤水和雪水的影响,根据冰川模型扣除GIA(Global Isostatic Adjustment)的影响,采用P3M6去相关滤波和300 km扇形滤波,基于最小二乘拟合的方法得到日本M_W 9.0地震的同震及断层上下盘两个特征点重力变化时间序列,利用PSGRN/PSCMP模型对日本M_W 9.0地震区域黏滞性进行了反演,并计算了同震及震后5年研究区域重力变化的空间分布.结果表明,扣除土壤水和冰川均衡调整因素的影响,同震重力变化为-5.2×10~(-8)～2.9×10~(-8) ms~(-2);两个特征点在震后5年重力均增加,下盘重力增加较大;日本M_W 9.0地震区域黏滞性横向差异较明显,断层上下盘的地幔黏滞系数分别为2.5×10~(18) Pa·s、5.0×10~(17) Pa·s时,与GRACE观测值较接近,综合考虑断层上下盘的震后重力变化,区域黏滞系数大约为1.5×10~(18) Pa·s.     

智利M_W8.8地震同震重力梯度变化

利用GFZ Release 05卫星重力GRACE观测数据,计算2010年2月27日智利MW8.8逆冲型地震的同震重力和重力梯度变化,分析其分布特征,可知:由GRACE探测到的同震重力变化在断层俯冲区域可达-9.5μGal,断层隆升区域可达+3.5μGal,结果与利用SNREI地球模型的位错理论计算的同震重力变化较一致,说明利用GFZ Release05 DDK5滤波数据,更能精确的反映同震重力场变化;GRACE检测的智利地震同震径向重力梯度变化Trr最大可达-600μE,位于发震断层东侧俯冲区域;通过对同震重力梯度分布特征分析,初步判断发生同震物质迁移的区域范围在断层俯冲区域为(67°—72°W,33°—38°S),在断层隆升区域为(73°—77°W,35°—39°S)。     

中国东北地区重力场研究——利用改进的三方向小子域滤波划分主构造线及大地构造单元

利用重力异常进行大地构造单元的划分是区域重力资料处理与解释的重要任务.为了精细地划分中国东北地区大地构造单元及其分界线位置,对三方向小子域滤波进行了改进,探讨了改进的三方向小子域滤波的合理性.利用小子域及改进的三方向小子域滤波对研究区布格重力异常进行处理,并与欧拉反褶积反演结果进行对比分析.结果表明,改进的三方向小子域滤波在识别平面断裂的应用中具有更好的效果.综合分析东北地区布格重力异常特征、小子域和改进的三方向小子域滤波结果,划分出延续性较好、规模较大的断裂18条.对研究区重力异常进行了分区,描述了一、二级异常的分区特点,给出了东北地区大地构造单元的基本格架.黑河-齐齐哈尔-白城等重要构造线平面位置的确定突破了传统的重力异常分区模式,指出东北地区NE向构造具有走滑特征,且走滑距离具有由西向东逐渐增大的特点.     

航空重力数据Kalman滤波平滑技术应用研究

提出一种用于航空重力数据低通滤波处理的卡尔曼(Kalman)滤波模型,采用该模型,利用Kalman最优线性平滑技术,对GT-1A航空重力勘查系统的测量数据进行了滤波试验研究,结果表明,上述模型是可行的,获得与GT-1A系统滤波结果几乎同样满意的滤波效果,二者滤波结果差值的标准偏差可达±0.2mGal.     

基于时变重力数据的川滇地区场源模型反演和解释

时变重力信号能反映地球内部介质迁移引起的不均衡变化,本文利用三维欧拉反褶积方法,通过建立合适的场源模型获得最佳反演参数,并采用水平梯度滤波法消除部分虚假发散解,优化反演结果.在此基础上,利用川滇地区2015-2019年流动重力重复观测资料,分析了不同时空尺度的区域重力场动态变化特征,开展对川滇地区重力变化场源特征的定性...     

天生桥一级水电站水库畜水初期的水库地震

引言 天生桥一级水电站位于贵州省安龙县和广西省隆林县交界处的红水河上游南盘江上，是红水河梯级电站的第一级。     

GRACE和地面重力测量监测到的中国大陆长期重力变化

自2002年以来,GRACE卫星探测计划可提供高精度的时变地球重力场,用以探测地球系统的物质分布.自1998年中国大陆重力监测网建立以来,利用FG5绝对重力仪和LCR-G型相对重力仪每2年对该网进行重复测量获取重力场时变信息.基于此,本文利用GRACE和地面重力测量获得了中国大陆重力场的长期年变率,利用位错理论根据USGS发布的断层模型计算了2008年汶川M_s8.0级地震的同震重力变化并进行了300 km高斯滤波.GRACE卫星重力和地面重力结果均表明华北地区地下水流失严重,在绝对重力基准站上,GRACE卫星重力与绝对重力变化率较为一致,汶川区域的地面重力变化结果可视为大地震前兆信息.     

A method for estimating soil moisture storage in regions under water stress and storage depletion: a case study of Hai River Basin,North China

Soil moisture is a consideration for soil conservation, agricultural production and climate modelling. This article presents a simple method for estimating soil moisture storage under water stress and storage depletion conditions. The method is driven by the common agro‐hydrologic variables of precipitation (PPT), irrigation (IRR) and evapotranspiration (ET). The proposed method is successfully tested for the 152 000 km² floodplain region of Hai River Basin using 48 consecutive months (2003–2006) of data. Soil moisture data from global land data assimilation system/Noah land surface model are validated with ground‐truth data from 102 soil moisture monitoring sites. The validated soil moisture is used in combination with in situ groundwater data to quantify total water storage change (TWSC) in the region. The estimated storage change is in turn compared with gravity recovery and climate experiment‐derived TWSC for the study area. The soil moisture and TWSC terms show favourable agreements, with discrepancies of < 10% on the average. While there is no consistent seasonal trend in soil moisture, TWSC shows a strong seasonality. It is low in spring and high in summer. This trend corresponds with the IRR–PPT season in the study area. Change in groundwater and total water storage indicates storage depletion in the basin. Storage depletion in the region is driven mainly by groundwater IRR and ET loss. Despite the low PPT and high ET, there is narrowing seasonal trend in soil moisture. This is achieved at the expense of groundwater storage. IRR pumping has induced extensive groundwater depletion in the basin. It is therefore vital to develop cultivation strategies that aim at limiting IRR pumping and ET loss. Water management practices that not only reduce waste but also ensure high productivity and ecological sustainability could also mitigate storage depletion in the region. These measures could reduce further not only the seasonal trend in soil moisture but also that in groundwater storage. Copyright © 2011 John Wiley & Sons, Ltd.     

Analysis of spatial distribution and multi-year trend of the remotely sensed soil moisture on the Tibetan Plateau

Long-term highly accurate surface soil moisture data of TP(Tibetan Plateau)are important to the research of Asian monsoon and global atmospheric circulation.However,due to the sparse in-situ networks,the lack of soil moisture observations has seriously hindered the progress of climate change researches of TP.Based on the Dual-Channel soil moisture retrieval algorithm and the satellite observation data of AMSR-E(Advanced Microwave Scanning Radiometer for EOS),we have produced the surface soil moisture data of TP from 2003 to 2010 and analyzed the seasonal characteristic of the soil moisture spatial distribution and its multi-year changing trend in area of TP.Compared to the in-situ observations,the accuracy of the soil moisture retrieved by the proposed algorithm is evaluated.The evaluation result shows that the new soil moisture product has a better accuracy in the TP region than the official product of AMSR-E.The spatial distribution of the annual mean values of soil moisture and the seasonal variations of the monthly-averaged soil moisture are analyzed.The results show that the soil moisture variations in space and time are consistent with the precipitation distribution and the water vapor transmission path in TP.Based on the new soil moisture product,we also analyzed the spatial distribution of the changing trend of multi-year soil moisture in TP.From the comparisons with the precipitation changing trend obtained from the meteorological observation sites in TP,we found that the spatial pattern of the changing trend of soil moisture coincides with the precipitation as a whole.     

应用平滑先验信息方法移除GRACE数据中相关误差

由于GRACE卫星数据解算的时变重力场模型中高阶位系数存在误差,这些误差在重力异常图中表现为南北向的条带噪声,在应用GRACE时变重力场数据时必须进行滤波.本文在空间域引入了一种有效消除GRACE时变重力场条带噪声的平滑先验信息方法,并将其与目前常用的高斯滤波和去相关误差等滤波方法分别应用于合成的质量变化趋势数字模型,检测不同滤波方法消除条带噪声的能力及其对真实信号的影响.滤波结果显示,与目前常用的高斯滤波和去相关误差滤波器相比,本文滤波方法在有效移除条带噪声的同时,具有有效信号幅度衰减小、有效信号形变小以及保存了更多的短波长细节信息等优势;此外,统计结果显示,本文滤波结果在信号最大值、最小值以及残差均方根等方面均与模拟真实信号最为接近.相比300km高斯平滑和组合滤波结果,有效信号振幅的极小值和极大值分别提高了约18%和6%,残差均方根分别降低了25%和33%.说明本文滤波方法移除GRACE相关误差的同时,在保留有效信号方面具有明显的优势.     

地球模型对季节性负荷形变计算的影响——以川滇地区为例

利用川滇地区的GNSS和GRACE数据, 结合不同地球模型和负荷理论, 研究了地球模型对地表季节性负荷形变计算的影响, 该工作对于选取合适的地球模型开展负荷形变研究具有一定的参考价值。 研究表明: ① 川滇地区GNSS观测的地壳垂向季节性形变振幅为20 mm左右, GRACE反演的垂向形变与GNSS的结果相位一致, 振幅存在差异。 ② 区域地球模型的负荷勒夫数与其他地球模型的差异较大, 且负荷勒夫数h_n对地球结构的变化较为敏感。 ③ 区域地球模型可以改善GRACE反演的负荷形变结果, 从而减小与GNSS观测结果的差异。 ④ 川滇地区大部分GNSS测站的加权均方根比值减小量呈现由东北向西南方向逐渐增加的变化趋势。     

青藏高原GRACE卫星重力长期变化

本文采用最新的GRACE(Gravity Recovery and Climate Experiment)(RL05)数据,通过水文模型(Global Land Data Assimilation System,GLDAS与Climate Prediction Center,CPC)扣除土壤水及雪水的影响,利用Paulson提供的冰川模型结果扣除GIA(Glacial Isostatic Adjustment)的影响,采用尺度因子的方法减少数据处理过程中误差的影响,最终基于最小二乘计算方法得到2003—2013中国及周边地区长期性重力异常变化情况.结果发现青藏高原有较为明显的重力上升信号,我们认为该信号可能由印度板块俯冲欧亚板块导致青藏高原地壳增厚所引起.接着依据GPS观测结果和艾黎均衡假说构建了地壳形变模型并通过直立长方体模型予以正演模拟分析.以班公湖—怒江断裂带为界将青藏高原划分为南北两大区块,结果显示青藏高原重力异常大致以0.2μGal·a-1的速率在递增,小于GRACE得到的0.3±0.08μGal·a-1的增长速率(对应于地壳增厚速率约3mm·a-1),剩余未解释部分可能与湖水、冰川因素、冻土因素等有关.该结果对于认识青藏高原隆升动力学有一定参考意义.     

Significance of secular trends of mass variations determined from GRACE solutions

Since 2002 the Earth’s gravity field is globally observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission. The GRACE monthly gravity field solutions, available from several analysis centres, reflect mass variations in the atmosphere, hydrosphere and geosphere. Due to correlated noise contained in these solutions, it is, however, first necessary to apply an appropriate filtering technique. The resulting, smoothed time series are applied not only to determine variations with different periodic signatures (e.g., seasonal, short and medium-term), but to derive long-periodic mass variations and secular trends as well. As the GRACE monthly solutions always show the integral effect of all mass variations, for separation of single processes, like the GIA (Glacial isostatic adjustment)-related mass increase in Fennoscandia, appropriate reduction models (e.g. from hydrology) are necessary.In this study we show for the example of the Fennoscandian uplift area that GRACE solutions from different analysis centres yield considerably different secular trends. Furthermore, it turns out that the inevitable filtering of the monthly gravity field models affects not only the amplitudes of the signals, but also their spatial resolution and distribution such as the spatial form of the detected signals. It also becomes evident that the determination of trends has to be performed together with the determination of periodic components. All periodic terms which are really contained in the data, and only such, have to be included. The restricted time span of the available GRACE measurements, however, limits the separation of long-periodic and secular signals. It is shown that varying the analysis time span affects the results considerably. Finally, a reduction of hydrological signals from the detected integral secular trends using global hydrological models (WGHM, LaDWorld, GLDAS) is attempted. The differences among the trends resulting from different models illustrate that the state-of-the-art hydrology models are not suitable for this purpose as yet. Consequently, taking the GRACE monthly gravity field solutions from one centre, choosing a single filter and applying an insufficiently reliable reduction model leads sometimes to a misinterpretation of considered geophysical processes. Therefore, one has to be cautious with the final interpretation of the results.     

Glacial isostatic adjustment in Fennoscandia from GRACE data and comparison with geodynamical models

The Earth’s gravity field observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission shows variations due to the integral effect of mass variations in the atmosphere, hydrosphere and geosphere. Several institutions, such as the GeoForschungsZentrum (GFZ) Potsdam, the University of Texas at Austin, Center for Space Research (CSR) and the Jet Propulsion Laboratory (JPL), Pasadena, provide GRACE monthly solutions, which differ slightly due to the application of different reduction models and centre-specific processing schemes. The GRACE data are used to investigate the mass variations in Fennoscandia, an area which is strongly influenced by glacial isostatic adjustment (GIA). Hence the focus is set on the computation of secular trends. Different filters (e.g. isotropic and non-isotropic filters) are discussed for the removal of high frequency noise to permit the extraction of the GIA signal. The resulting GRACE based mass variations are compared to global hydrology models (WGHM, LaDWorld) in order to (a) separate possible hydrological signals and (b) validate the hydrology models with regard to long period and secular components. In addition, a pattern matching algorithm is applied to localise the uplift centre, and finally the GRACE signal is compared with the results from a geodynamical modelling. The GRACE data clearly show temporal gravity variations in Fennoscandia. The secular variations are in good agreement with former studies and other independent data. The uplift centre is located over the Bothnian Bay, and the whole uplift area comprises the Scandinavian Peninsula and Finland. The secular variations derived from the GFZ, CSR and JPL monthly solutions differ up to 20%, which is not statistically significant, and the largest signal of about 1.2 Gal/year is obtained from the GFZ solution. Besides the GIA signal, two peaks with positive trend values of about 0.8 Gal/year exist in central eastern Europe, which are not GIA-induced, and also not explainable by the hydrology models. This may indicate that the recent global hydrology models have to be revised with respect to long period and secular components. Finally, the GRACE uplift signal is also in quite good agreement with the results from a simple geodynamical modelling.     

利用SWARM卫星高低跟踪探测格陵兰岛时变重力信号

GRACE重力卫星任务即将结束,后续GRACE Follow-On卫星计划于2017年发射,在此期间,迫切需要一个新的卫星计划继续对全球时变重力场进行连续监测,以保证时变重力场信息时间序列的连贯性.SWARM计划包括三颗轨道高为300~500 km的近极轨卫星星座,类似于三颗CHAMP卫星,具有接替时变重力场探测的潜力.本文首先分析SWARM(模拟)、CHAMP、GRACE反演至60阶时变重力场球谐系数的误差特性及不同高斯平滑半径对高频误差的抑制效果,然后分别利用SWARM、CHAMP、GRACE的时变重力场模型恢复全球质量变化,结果表明,SWARM模拟观测数据的高频误差低于CHAMP观测数据,探测时变重力场的整体精度优于CHAMP,略低于GRACE探测精度;其次,对比2003年1月—2009年12月期间CHAMP(hl-SST)和GRACE(ll-SST)时变重力场模型反演格陵兰岛冰盖质量变化趋势,结果显示,CHAMP数据得到格陵兰岛冰盖质量变化趋势为-50.2±2.0 Gt/a,GRACE所得结果为-41.2±1.6 Gt/a,两者相差21.8%;最后,对比2000年1月—2004年12月间SWARM模拟数据和"真实"模型数据反演的格陵兰岛冰盖质量变化趋势,结果表明,两者相差19.2%.本文研究表明,利用SWARM hl-SST数据探测时变重力场可以达到20%相对精度水平,有潜力用于填补GRACE和GRACE Follow-On期间探测地球时变重力场的空白.     

Groundwater Storage Changes: Present Status from GRACE Observations

Satellite gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) provide quantitative measurement of terrestrial water storage (TWS) changes with unprecedented accuracy. Combining GRACE-observed TWS changes and independent estimates of water change in soil and snow and surface reservoirs offers a means for estimating groundwater storage change. Since its launch in March 2002, GRACE time-variable gravity data have been successfully used to quantify long-term groundwater storage changes in different regions over the world, including northwest India, the High Plains Aquifer and the Central Valley in the USA, the North China Plain, Middle East, and southern Murray–Darling Basin in Australia, where groundwater storage has been significantly depleted in recent years (or decades). It is difficult to rely on in situ groundwater measurements for accurate quantification of large, regional-scale groundwater storage changes, especially at long timescales due to inadequate spatial and temporal coverage of in situ data and uncertainties in storage coefficients. The now nearly 13 years of GRACE gravity data provide a successful and unique complementary tool for monitoring and measuring groundwater changes on a global and regional basis. Despite the successful applications of GRACE in studying global groundwater storage change, there are still some major challenges limiting the application and interpretation of GRACE data. In this paper, we present an overview of GRACE applications in groundwater studies and discuss if and how the main challenges to using GRACE data can be addressed.     

利用GPS与GRACE监测陆地水负荷导致的季节性水平形变：以喜马拉雅山地区为例

地表陆地水负荷变化是引起重力场和地壳形变呈现季节性特征的主要因素,并且能够利用地表及空间大地测量技术对其进行有效的监测.本文通过对质量负荷形变效应的理论模拟,描述了水平分量的形变指向以及垂直与水平分量的幅值比可以提高对负荷区域的辨别程度,并且联合GPS坐标时间序列及GRACE模型对喜马拉雅山地区的季节性负荷形变进行了详细对比分析,研究结果显示两者垂直分量的季节性变化具有较好的一致性,且GPS周年项幅值要大于GRACE.而由GRACE解算得到的水平分量结果表明该地区季节性形变主要受东南亚及印度东北部地区的陆地水负荷控制,位于喜马拉雅山地区多数GPS台站的垂直分量及北向分量的初相位与GRACE模型解算结果相近,而部分GPS台站的东向分量与GRACE模型存在明显不同,由此导致GPS与GRACE监测到的形变指向存在差异.通过对GRACE估算精度以及GPS垂直与水平分量幅值比的深入分析,发现GPS对局部周边地区的河流、谷地及农田灌溉等负荷变化造成的形变效应较为敏感,而GRACE由于截断阶次及平滑滤波等影响因素,不仅造成在水平分量上的分辨率远低于垂直分量,而且整体估算精度要低于GPS观测得到的形变信息.