复测水准网拟稳抗差解算模型

变形监测网平差的主要方法是秩亏平差法或拟稳平差法。本文基于抗差估计原理，首先推导了秩亏平差模型的抗差解式和拟稳抗差解，并推导了普通秩亏抗差解与拟稳抗差解之间的转换关系。使得拟稳抗差估计的解算简便直观。     

Tidal flow forecasting using reduced rank square root filters

The Kalman filter algorithm can be used for many data assimilation problems. For large systems, that arise from discretizing partial differential equations, the standard algorithm has huge computational and storage requirements. This makes direct use infeasible for many applications. In addition numerical difficulties may arise if due to finite precision computations or approximations of the error covariance the requirement that the error covariance should be positive semi-definite is violated. In this paper an approximation to the Kalman filter algorithm is suggested that solves these problems for many applications. The algorithm is based on a reduced rank approximation of the error covariance using a square root factorization. The use of the factorization ensures that the error covariance matrix remains positive semi-definite at all times, while the smaller rank reduces the number of computations and storage requirements. The number of computations and storage required depend on the problem at hand, but will typically be orders of magnitude smaller than for the full Kalman filter without significant loss of accuracy. The algorithm is applied to a model based on a linearized version of the two-dimensional shallow water equations for the prediction of tides and storm surges. For non-linear models the reduced rank square root algorithm can be extended in a similar way as the extended Kalman filter approach. Moreover, by introducing a finite difference approximation to the Reduced Rank Square Root algorithm it is possible to prevent the use of a tangent linear model for the propagation of the error covariance, which poses a large implementational effort in case an extended kalman filter is used.     

Spatial continuity measures for probabilistic and deterministic geostatistics

Geostatistics has traditionally used a probabilistic framework, one in which expected values or ensemble averages are of primary importance. The less familiar deterministic framework views geostatistical problems in terms of spatial integrals. This paper outlines the two frameworks and examines the issue of which spatial continuity measure, the covarianceC (h) or the variogram (h), is appropriate for each framework. AlthoughC (h) and (h) were defined originally in terms of spatial integrals, the convenience of probabilistic notation made the expected value definitions more common. These now classical expected value definitions entail a linear relationship betweenC (h) and (h); the spatial integral definitions do not. In a probabilistic framework, where available sample information is extrapolated to domains other than the one which was sampled, the expected value definitions are appropriate; furthermore, within a probabilistic framework, reasons exist for preferring the variogram to the covariance function. In a deterministic framework, where available sample information is interpolated within the same domain, the spatial integral definitions are appropriate and no reasons are known for preferring the variogram. A case study on a Wiener-Levy process demonstrates differences between the two frameworks and shows that, for most estimation problems, the deterministic viewpoint is more appropriate. Several case studies on real data sets reveal that the sample covariance function reflects the character of spatial continuity better than the sample variogram. From both theoretical and practical considerations, clearly for most geostatistical problems, direct estimation of the covariance is better than the traditional variogram approach.This paper was presented at MGUS 87 Conference, Redwood City, California, 14 April 1987.     

有偏估计与LS估计的比较与选择

从假设检验的角度研究测量平差Gauss-Markov模型中有偏估计与LS估计的选择问题。首先在均方误差准则下对目前应用最广泛的2种有偏估计－－岭估计和主成分估计与LS估计进行了比较研究，得到了岭估计、主成分估计优于LS估计的条件；然后运用统计方法对这些条件的成立进行了假设检验；最后通过数值实验说明，在一定显著性水平下当原假设被接受时，说明没有理由不相信采用有偏估计来代替LS估计的合理性，可认为采用有偏估计将对LS估计做出比较有效的改进，当原假设被拒绝时，说明对采用有偏估计的优越性产生了怀疑，此时建议仍采用LS估计。     

GPS基线非线性解算的精度评定方法

在GPS基线向量非线性平差解算的基础上，分析了单位权中误差估值，平差值的精度估计和基线长度的精度估计，并给出了简明的直接估计公式，为GPS基线向量非线性平差解算的精度评定提供了直接的评定公式。     

伊豆-小笠原下方660km间断面的区域性差异

利用南、北加州地震台网、华盛顿州西北太平洋地震台网单分量短周期地震仪和德国、瑞士地震台网／台阵的三分量宽频带地震仪记录的1981～2000年伊豆——小笠原地区下方地震的波形资料，使用N次根倾斜叠加方法提取近源一侧来自间断面SdP转换震相，以研究660km间断面区域性差异．研究发现，自35Ｎ 到26Ｎ 的各剖面依次体现了和达 本尼奥夫带（Wadati-Benioff zone）倾角逐渐加大，且地震分布的最大深度也逐步增大，俯冲板块对660km间断面存在的影响也因此产生了差异性:没有俯冲板块影响的情况下，该间断面出现在CM）660km深度处，而受到俯冲板块明显作用的地区，则该间断面普遍出现下陷．转换点分布的一定程度分散性可能是间断面本身复杂结构、震相误判或一维球对称地球模型假定等因素造成的．这一转换点分布的分散性是一个亟需解决的问题．      

通道特性相关时带乘性噪声系统观测噪声的最优估计

研究在较弱的乘性噪声条件下系统观测噪声的最优估计问题,就乘性噪声为一般随机矩阵且各观测通道乘性噪声在同时刻相关的情形,给出了在线性最小方差意义下的观测噪声最优滤波算法和最优平滑算法。针对这些算法进行了仿真研究,仿真结果表明算法有较好的估计效果。     

Raingauge network optimization in a tropical urban area by coupling cross-validation with the geostatistical technique

An adequate and reliable raingauge network is essential for observing rainfall data in hydrology and water resource applications. A raingauge network developed for a catchment area is commonly extended periodically to increase data accuracy. Due to financial constraints, the network is reviewed for the optimal number of stations. A new optimization approach is developed in this study by coupling a cross-validation technique with a geostatistical method for raingauge network optimization to prioritize raingauge stations. The spatial interpolation error of the spatial rainfall distribution, measured as the root mean square error (E_rms) optimization criterion is applied to a raingauge network in a tropical urban area. The results indicate that this method can successfully optimize the number of rainfall stations in an existing raingauge network, as the stations are prioritized based on their importance in the network.     

鄱阳湖典型洲滩湿地水分补排关系

湿地水分在地下水含水层-土壤-植物-大气界面的运移和转换是维持能量和营养物平衡的重要环节,水分运移是湿地生态水文过程研究的关键.数值模型模拟已成为水分运移研究的重要手段,然而限于复杂的湿地自然条件及有限的监测手段,部分界面水分通量连续动态变化数据的获取及定量化工作较为困难,目前应用数值模拟法于湿地水分运移研究的案例仍不多见.本文以鄱阳湖典型湿地为研究区,构建垂向一维数值模型,阐释了湖泊水位显著季节性变化条件下,湿地水分在不同界面的传输过程,量化了湿地水分的补排关系.结果表明:(1)界面水分通量季节性差异大,降雨入渗地面和根系层水分渗漏均对降雨变化响应敏感,主要集中在4—6月,分别占年总量(1450和1053 mm)的65%和73%.土面蒸发和植物蒸腾年总量为176和926 mm,土面蒸发主要受气候条件影响,植物蒸腾还与植物生长特征有关,均集中在7—8月,分别占年总量的30%和47%.深层土壤向浅层根系层的水分补给集中发生在地下水浅埋时段6—8月,占年总量(609 mm)的76%;(2)湿地植物根系层水分补排受鄱阳湖水位季节性波动影响显著.除丰水期(7—9月)主要补给为深层土壤水外,退、枯、涨水期的主要补给均为降水入渗.涨水期(4—6月)和枯水期(12—3月)的主要排泄为根系层水分渗漏,丰水期以植物蒸腾排泄为主,退水期(10—11月),土面蒸发与植物蒸腾为主要排泄,且比重相当.本文定量了鄱阳湖典型湿地不同界面水分连续交换关系,区分了土面蒸发和植物蒸腾,辨析了各界面水分的主要影响因子,研究结果有助于深入理解水分在湿地生态系统地下水含水层-土壤-植物-大气界面的相互作用机制,认识湖泊洲滩湿地水量平衡,为揭示湖泊水情变化对湿地生态的可能影响提供依据,为湿地生态水文过程研究提供重要方法和理论参考.     

Large roots dominate the contribution of trees to slope stability

Tree roots provide surface erosion protection and improve slope stability through highly complex interactions with the soil due to the nature of root systems. Root reinforcement estimation is usually performed by in situ pullout tests, in which roots are pulled out of the soil to reliably estimate the root strength of compact soils. However, this test is not suitable for the scenario where a soil progressively fails in a series of slump blocks – for example, in unsupported soils near streambanks and road cuts where the soil has no compressive resistance at the base of the hillslope. The scenario where a soil is unsupported on its downslope extent and progressively deforms at a slow strain rate has received little attention, and we are unaware of any study on root reinforcement that estimates the additional strength provided by roots in this situation. We therefore designed two complementary laboratory experiments to compare the force required to pull the root out. The results indicate that the force required to pull out roots is reduced by up to 50% when the soil fails as slump blocks compared to pullout tests. We also found that, for slump block failure, roots had a higher tendency to slip than to break, showing the importance of active earth pressure on root reinforcement behaviour, which contributes to reduced friction between soil and roots. These results were then scaled up to a full tree and tree stand using the root bundle and field-measured spatial distributions of root density. Although effects on the force mobilized in small roots can be relevant, small roots have virtually no effect on root reinforcement at the tree or stand scale on hillslopes. When root distribution has a wide range of diameters, the root reinforcement results are controlled by large roots, which hold much more force than small roots. © 2019 John Wiley & Sons, Ltd.