基于有色噪声模型的GPS速度场精度与时间序列长度相关性研究

利用2010—2015年陆态网络GPS连续观测站的三维站坐标时序资料, 在采用最大似然估计MLE方法计算得到云南地区GPS基准站三维站坐标分量最优噪声模型的基础上, 进一步定量对比分析了有色噪声和白噪声模型下陆态网络GPS连续站速度场稳定性与时间序列长度的关系。 结果表明: 在闪烁噪声模型下, 中国大陆大部分地区GPS连续站1 a时段的速度不确定度大。 而随着时间的逐年累积, 闪烁噪声模型下的速度不确定度与同时段白噪声模型下的差异逐步减小, 闪烁噪声模型下3～4 a时段的速度不确定度与同时段白噪声模型的差异小于0.2 mm。 研究说明在有色噪声模型下要获得高精度的速度场需要3～4 a的观测数据, 白噪声模型下GPS速度场精度可靠可信的前提是采用不少于3～4 a的数据。     

山西省GNSS基准站时间序列分析

使用开源GAMIT/GLOBK软件对山西省GNSS基准站数据进行解算,解算中运用潮汐参数、全球通用的地球模型等得到山西省GNSS基准站高精度时间序列。基于时间序列模型剔除周期干扰,并用小波分析法分析时间序列的特性,研究结果可为地震预测与研究提供数据支撑。     

北京房山站神经网络高程时间序列分析

为了更好地分析高程时间序列的变化规律,使其能更好地应用到地壳运动监测.本文对房山站观测数据先采用PanTa方法剔除异常值,然后进行混沌动力学系统检验.经检验可知,北京房山站高程时间序列为非线性、非稳态时间序列,观测系统为部分确定性机制低阶混沌动力系统.因此对数据进行正则化RBF网络相空间重构和小波神经网络滤波,然后再对数据进行加窗谱估计、最小差距拟合和去除趋势FFT周期拟合计算分析.计算结果显示,北京房山站高程时间序列的平均谱功率为7694W,年周期为0.994～1.109(年),半年周期为0.438～0.617(年),年周期为0.247～0.378(年).分析计算结果表明,该时间序列斜趋势不明显,随机性不明显,其存在着年周期性、半年周期性和季周期性,其中年周期最为明显.     

中国大陆GNSS数据精化解算研究

使用GAMIT/GLOBK/QOCA处理中国地壳运动观测网络和中国大陆构造环境监测网络产出的1999～2011年GNSS连续观测和流动观测数据及相关IGS站的连续观测数据,并在求解中国大陆GNSS速度场过程中扣除了2001年昆仑山口西地震、2008年汶川地震、2011年日本地震的同震位移场,从而能够得到精化的中国大陆GNSS速度场.结果表明:精化的速度场不仅较为准确地扣除了强震的同震位移,而且整体一致性更好.     

基于多通道奇异谱分析的GNSS坐标时间序列共模误差的提取

共模误差是区域连续GNSS网中存在的一种与时空相关的主要误差源.为了有效的剔除共模误差,提高坐标时间序列的精度,本文提出了利用多通道奇异谱分析（Multi-channel Singular Spectrum Analysis,MSSA）提取共模误差的新思路,并利用实验区域18个测站9年（2002年到2010年）的GPS坐标时间序列进行实验,分析了共模误差对时间序列的影响和测站噪声特性的影响,并对共模误差序列进行周期探测,结果显示：通过MSSA能够有效的剔除共模误差,提高坐标时间序列的精度.     

基于独立分量分析的南极半岛GNSS网区域滤波

高精度GNSS速度场是研究地壳垂向运动及板块运动的基础,能够为冰川均衡调整（Glacial Isostatic Adjustment,GIA）的建模提供外部检核和新的约束.共性误差（Common Mode Error,CME）是区域连续GNSS时间序列中存在的一种与时空相关的主要误差源,通过空间滤波可有效的降低共性误差的影响,提高坐标时间序列的精度.目前广泛采用的主分量分析法（Principal Component Analysis,PCA）,基于二阶统计量（方差和协方差）进行处理,没有充分利用CME高阶统计信息.而独立分量分析ICA （Independent Component Analysis）,引入高阶统计量,能够分离出统计独立的非高斯信号.以南极半岛地区的15个GNSS站点为例,由于某些站点存在强烈的局部效应,因此引入了因子分析法首先对异常站进行剔除,然后对比分析了PCA和ICA方法在南极半岛地区区域滤波结果.结果显示,ICA的滤波效果要优于PCA,ICA滤波前后E、N、U三个方向RMS平均降低44.69%、26.94%、34.87%,不确定度分别降低37.43%,44.58%,55.86%,有效的降低了GNSS残差序列的发散性和速度的不确定度.     

利用GPS资料研究天津地区近期运动特征

利用最新GPS连续站与流动站观测数据,得到天津地区的速度场及时间序列结果,结合区域应变时间序列,分析天津地区近期运动特征。结果表明:从速度场结果来看,天津地区2013—2017期的速度场较周围区域数值较小,水平运动较弱;从水平时间序列结果来看,天津地区的GPS测站以稳定的速度向东南运动,从垂直时间序列来看,北部以稳定的速率上升,南部以稳定的速率下降;从区域应变结果来看,整体以稳定的速率积累,没有明显的变化。     

青海门源6.9级地震同震及震前GNSS变形特征分析

北京时间2022年1月8日1点45分,在我国青海省门源县发生了6.9级地震.通过震中附近陆态网络GNSS连续观测数据得到的同震位移场显示,距离震中最近的QHME站同震位移最大,EW向达到20.31 mm,SW向达到-35.45 mm,震中附近五个站的同震位移反映出此次地震的左旋同震破裂特征;GNSS站间基线时间序列结果...     

GPS数据解算过程中相关问题研究

基于2011和2012年陆态网GPS连续观测数据,分析了GPS水平速度场数据解算过程中,不同对流层延迟参数个数与初始坐标偏差对解算精度的影响;利用重采样方法模拟生成多组不同时间间隔的流动数据,分析了不同时间间隔的流动观测模式下的解算精度。通过实验证实,为了得到高精度的GPS单日松弛解,必须进行对流层延迟估计,对流层参数个数设置为2,7,13时解算精度存在少量差别,表现为随着参数增多解算精度有所提高;初始坐标误差在10m时可以得到精度较高的时间序列结果,误差在30m及50m时不能得到可用的时间序列;当流动观测时间间隔大于1年时,可以获得较为可靠的水平速度场结果;时间间隔短于1年时,水平速度场解算精度较低。     

呼图壁地下储气库GNSS连续站一致性分析

利用新疆呼图壁地下储气库内外的3个GNSS连续站一年的观测资料分析库区内部2个连续站的一致性及其与呼图壁M_S6. 2地震的关系。研究表明:储气库库区内部2个GNSS连续站的位置时间序列和基线时间序列均显示出较好的一致性,站点稳定,可以做为基准点。由于距离12月8日呼图壁M_S6. 2地震较远,地下储气库库区的2个连续站震前未能有明显形变异常反映,同震效应较小,震后有小幅的波动变化。     

SCIENCE CHINA Earth Sciences SUBJECT INDEX TO VOLUME 57(2014)

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Distribution of throughfall and stemflow in multi‐strata agroforestry,perennial monoculture,fallow and primary forest in central Amazonia,Brazil

The partitioning of rain water into throughfall, stemflow and interception loss when passing through plant canopies depends on properties of the respective plant species, such as leaf area and branch angles. In heterogeneous vegetation, such as tropical forest or polycultural systems, the presence of different plant species may consequently result in a mosaic of situations with respect to quantity and quality of water inputs into the soil. As these processes influence not only the water availability for the plants, but also water infiltration and nutrient leaching, the understanding of plant effects on the repartitioning of rain water may help in the optimization of land use systems and management practices. We measured throughfall and stemflow in a perennial polyculture (multi‐strata agroforestry), monocultures of peach palm (Bactris gasipaes) for fruit and for palmito, a monoculture of cupuaçu (Theobroma grandiflorum), spontaneous fallow and primary forest during one year in central Amazonia, Brazil. The effect on rain water partitioning was measured separately for four useful tree species in the polyculture and for two tree species in the primary forest. Throughfall at two stem distances, and stemflow, differed significantly between tree species, resulting in pronounced spatial patterns of water input into the soil in the polyculture system. For two tree species, peach palm for fruit (Bactris gasipaes) and Brazil nut trees (Bertholletia excelsa), the water input into the soil near the stem was significantly higher than the open‐area rainfall. This could lead to increased nutrient leaching when fertilizer is applied close to the stem of these trees. In the primary forest, such spatial patterns could also be detected, with significantly higher water input near a palm (Oenocarpus bacaba) than near a dicotyledonous tree species (Eschweilera sp.). Interception losses were 6·4% in the polyculture, 13·9 and 12·3% in the peach palm monocultures for fruit and for palmito, respectively, 0·5% in the cupuaçu monoculture and 3·1% in the fallow. With more than 20% of the open‐area rainfall, the highest stemflow contributions to the water input into the soil were measured in the palm monocultures and in the fallow. Copyright © 1999 John Wiley & Sons, Ltd.     

A Monte Carlo study of rainfall forecasting with a stochastic model

A procedure for short-term rainfall forecasting in real-time is developed and a study of the role of sampling on forecast ability is conducted. Ground level rainfall fields are forecasted using a stochastic space-time rainfall model in state-space form. Updating of the rainfall field in real-time is accomplished using a distributed parameter Kalman filter to optimally combine measurement information and forecast model estimates. The influence of sampling density on forecast accuracy is evaluated using a series of a simulated rainfall events generated with the same stochastic rainfall model. Sampling was conducted at five different network spatial densities. The results quantify the influence of sampling network density on real-time rainfall field forecasting. Statistical analyses of the rainfall field residuals illustrate improvement in one hour lead time forecasts at higher measurement densities.     

Anthropogenic Eutrophication and Red Tide Outbreak in Lacustrine Systems of the Kashmir Himalaya

Red tide, a recurrent phenomenon has become conspicuous in several Kashmir lake ecosystems since 1991. The responsible organism (Euglena pedunculata), a rare flagellate rediscovered in the Kashmir Himalaya (Khan 1993) caused first and unprecedented red tide outbreak, constituting a maximum of 96% of resident numerical phytoplankton density in Dal Lake. At present, conflicting hypotheses exist on the generation of causal assemblage(s) imparting redness to waters: Jeeji Bai (1991) linked its origin to acid precipitation – a fallout of burning oil‐fields during the Gulf War – whilst Khan (1993) holds local factor(s) responsible. Field/experimental studies support the latter contention that the influx of untreated sewage, in unison with warm temperatures, high levels of PhAR, iron and interruption to hydrological flow‐pattern together with absence/or reduction in grazing activity created conducive environmental milieu for red tide outbreak. Dal Lake “red tide” drifted the bloom‐inoculum to other waters, including Lake Wular, where additional ecological niches were carved out, threatening the aesthetic value and biological diversity of Kashmir lakes. Ecological monitoring indicates frequent seasonal red tide occurrence in Dal Lake (including summer‐autumn event of 1998) which testifies its unabated eutrophication status. Further studies are needed on ecological adaptability and biogeographic distribution of this rare and unique red tide‐causing flagellate.