A bivariate meta-Gaussian density for use in hydrology

Convenient bivariate densities found in the literature are often unsuitable for modeling hydrologic variates. They either constrain the range of association between variates, or fix the form of the marginal distributions. The bivariate meta-Gaussian density is constructed by embedding the normal quantile transform of each variate into the Gaussian law. The density can represent a full range of association between variates and admits arbitrarily specified marginal distributions. Modeling and estimation can be decomposed into i) independent analyses of the marginal distributions, and ii) investigation of the dependence structure. Both statistical and judgmental estimation procedures are possible. Some comparisons to recent applications of bivariate densities in the hydrologic literature motivate and illustrate the model.     

Farlie-Gumbel-Morgenstern bivariate densities: Are they applicable in hydrology?

Certain bivariate densities constructed from marginals have recently been suggested as models of hydrologic variates such as rainfall intensity and depth. It is pointed out that (i) these densities belong to the families of the Farlie-Gumbel-Morgenstern densities and the Farlie polynomial densities, which have been extensively studied in the statistical literature, and that (ii) these densities have a limited potential applicability in hydrology since they can model only weakly associated variates, whose product-moment correlationR is within the range |R|1/3, under the first family of densities, and |R|1/2 under the second family.     

Farlie-Gumbel-Morgenstern bivariate densities: Are they applicable in hydrology?

Certain bivariate densities constructed from marginals have recently been suggested as models of hydrologic variates such as rainfall intensity and depth. It is pointed out that (i) these densities belong to the families of the Farlie-Gumbel-Morgenstern densities and the Farlie polynomial densities, which have been extensively studied in the statistical literature, and that (ii) these densities have a limited potential applicability in hydrology since they can model only weakly associated variates, whose product-moment correlationR is within the range |R|1/3, under the first family of densities, and |R|1/2 under the second family.     

地震信号随机噪声压制的双树复小波域双变量方法

有效地压制地震信号中的噪声是地震信号解释和后续处理的重要环节之一.本文建立两种双树复小波域双变量模型对地震信号中的随机噪声进行压制.地震信号经双树复小波变换后,同一方向实部与虚部系数、实部（或虚部）系数与对应的模之间存在较强的相关性.鉴于此,对同一方向实部与虚部小波系数建立双变量模型,从含噪地震信号小波系数中估计原始信号的小波系数,再基于双树复小波逆变换重构得到降噪后的地震信号.进一步对同一方向实部（或虚部）系数与对应的模建立双变量模型,得到地震信号随机噪声压制的第二种双树复小波域双变量方法.最后对合成地震记录和实际地震资料中的随机噪声进行压制的实验结果证实本文两种方法都能够有效地压制地震信号中的随机噪声.     

Use of mixed bivariate distributions for deriving inter‐station correlation coefficients of rain rate

Even though rain rate is notorious for its spatial and temporal intermittency, its effect on the second‐order statistics of rain rate, especially the inter‐station correlation coefficients, has not been intensively evaluated before. This study has derived and compared the inter‐station correlation coefficient of rain rate for three cases of data: (1) only the positive measurements at both locations; (2) the positive measurements at either one or both locations; (3) all the measurements including zero measurement at both locations. For these three cases, the inter‐station correlation coefficients are analytically derived by applying the mixed bivariate log‐normal distribution. As an application example, the model parameters are estimated using the rain rate data collected at the Geum River basin, Korea, and the resulting inter‐station correlation coefficients are evaluated and compared with those estimated by applying the Gaussian distribution. We could find that highly biased inter‐station correlation coefficients are unavoidable when simply estimating them under the assumption of Gaussian distribution, or even when using the log‐transformed rain rate data. Copyright © 2007 John Wiley & Sons, Ltd.     

小波变换在裂缝识别和裂缝密度评价中的研究(英文)

通过常规测井曲线小波变换来评价裂缝参数是一个较新的研究课题。本文针对火山岩裂缝储层,对常规测井曲线做coif5、bior4.4和db5基小波的小波变换,通过变换后的分解信号与成像测井裂缝密度的对比研究,寻找出与裂缝密度相匹配的基小波,再将常规测井曲线在这个基小波下的分解信号与曲线变化率法相结合建立裂缝指示曲线来识别裂缝发育段,最后通过裂缝指示曲线与成像测井的裂缝密度之间的量化关系来比较准确的评价裂缝密度。将裂缝指示曲线法在松辽盆地南部进行了应用,通过裂缝指示曲线求取的裂缝密度与成像测井的裂缝密度之间的相对误差为0.53。     

A bivariate gamma distribution for use in multivariate flood frequency analysis

A gamma distribution is one of the most frequently selected distribution types for hydrological frequency analysis. The bivariate gamma distribution with gamma marginals may be useful for analysing multivariate hydrological events. This study investigates the applicability of a bivariate gamma model with five parameters for describing the joint probability behavior of multivariate flood events. The parameters are proposed to be estimated from the marginal distributions by the method of moments. The joint distribution, the conditional distribution, and the associated return periods are derived from marginals. The usefulness of the model is demonstrated by representing the joint probabilistic behaviour between correlated flood peak and flood volume and between correlated flood volume and flood duration in the Madawask River basin in the province of Quebec, Canada. Copyright © 2001 John Wiley & Sons, Ltd.     

电离层加热实验中超强电子密度增强特征

2011年11月利用欧洲非相干散射雷达协会(EISCAT)的大功率加热设备和诊断设施开展了挪威高纬度地区电离层加热实验. 在此次加热实验中, UHF雷达探测到了十分明显的电子密度增强现象, 反射高度附近电子密度最大增幅可达269.3%, 而在远离谐振区的300~500 km及以上高度的增幅也可达30%~50%. 通过对加热前后离子线谱和数据残差的对比分析, 表明300~500 km的电子密度增强是真实可信的, 在如此大的空间范围出现增幅如此大的电子密度增强特征实属罕见. 另外通过对等离子体线谱的分析, 得到了等离子体线双谐振峰结构, 本文利用电子的速度分布函数和等离子体线谱之间的关系, 对加热实验中观测到的等离子体线谱进行了仿真, 提出了超热电子是引起本次电子密度增强的可能机制. 并利用仿真中所使用的超热电子速度参数对超热电子的电离能力、横向和纵向自由程进行了计算, 最终验证了所提出的物理机制的合理性.     

高邮地震台地磁异常与江苏及邻区地震关系的研究

应用加卸载响应比法、日变幅逐日比法、空间相关分析法,研究分析了高邮地磁台1992～1997年地磁垂直分量观测资料发现,在中强地震前高邮台的地磁场存在明显的磁异常变化,提出了适用于高邮台的地震分析预报参数。     

基于GA-BP理论的储层视裂缝密度地震非线性反演方法

基于GA-BP理论,将自适应遗传算法与人工神经网络技术(BP算法)有机地相结合,形成了一种储层裂缝自适应遗传-神经网络反演方法.这种新的方法是由编码、适应度函数、遗传操作及混合智能学习等组成,即在成像测井裂缝密度数据约束下,通过对目标问题进行编码(称染色体),然后对染色体进行选择、交叉和变异等遗传操作,使染色体不断进化,从而快速获得全局最优解.在反演执行过程中,利用地震数据和成像测井裂缝密度数据之间的非线性映射关系建立训练样本,将GA算法与BP算法有机地结合,优化三层前向网络参数;或将GA与ANFIS相结合,优化ANFIS网络参数.并采用GA算法与TS算法(Tabu Search)相结合的自适应混合学习算法,该学习算法自始至终将GA和BP两种算法按一定的概率比例进行,其概率自适应变化,以达到混合算法的均衡.这种混合算法提高了网络的收敛速度和精度.我们分别利用两个研究地区的6井和1井成像测井裂缝密度数据与地震数据之间的非线性映射关系建立训练样本,对过这两口井的测线的地震数据进行反演,获得了视裂缝密度剖面,视裂缝密度剖面上裂缝分布特征符合沉积相分布特征和岩石力学性质的变化特征.这种视裂缝密度剖面含有储层裂缝的定量信息,其误差可为油气勘探开发实际要求所允许.因此,这种新的方法优于只能作裂缝定性分析的常规裂缝地震预测方法,具有广阔的应用前景.     

弹性波逆时偏移中的稳定激发振幅成像条件

本文针对弹性波逆时偏移,提出稳定的激发振幅成像条件.在震源波场的正向传播过程中,计算每个网格点的能量,并保存最大能量密度的时刻和相应的波场值;在检波器波场的逆时传播过程中,在每个网格点提取最大能量密度时刻的检波器波场值,并利用保存的最大能量震源波场做归一化,获得角度依赖的反射系数成像剖面.相比于归一化互相关成像条件,该成像条件在震源波场的正向传播过程中无需存储波场快照,节省大量磁盘空间和I/O吞吐任务,提高了计算效率;相比于弹性波的激发时间成像条件,该成像条件自动校正了水平分量在震源两侧的极性反转,在多炮叠加时避免振幅损失.数值试验表明,与归一化成像条件相比,稳定激发振幅成像条件具有更小的计算量,偏移剖面的低频假象更弱,水平分量的成像能力更优,具有更高的空间分辨率.     

Neutron and density logging responses to gas reservoir for well-balanced and under-balanced logging:Gas reservoirs of sandstone in a western China field

Studying the response differences between neutron and density logging of gas reservoir for well-balanced and under-balanced logging will be of significance in evaluation of gas reservoir under the under-balanced condition and application of logging data. With Monte Carlo simulation technique,the paper obtains the relationship between neutron and density logging measurement and borehole di-ameter,porosity or gas saturation for well-balanced and under-balanced logging. The conclusions show that the response trend of under-balanced logging to gas reservoirs agrees with that of well-balanced logging with small borehole,and under-balanced logging data can be used usually as well-balanced logging data. When borehole diameter is large,under-balanced logging data should be corrected for the influences of borehole.     

A global river routing network for use in hydrological modeling

In this paper a relatively simple procedure is presented to construct a global river routing network on a 0.5° latitude–longitude grid. In this network all grid cells in a catchment are coupled and have a flow direction, making it a useful tool in the modeling of river flow on a global scale. The flow directions are based on a digital elevation model and on information on the locations of major rivers (‘stream burning’). The presented river routing network is specifically designed for the assessment of fresh water shortages. We tested the validity of the river routing network by comparing the computed drainage areas with published estimates. This comparison revealed a good similarity and it is concluded that the presented river routing network has sufficient quality to be implemented in global climate models. This could mean a considerable improvement of the surface parameterization in these models.     

一种震相拾取误差的自动判别和计算方法

本文给出了一个主要用于深地震测深数据的震相识别误差（不确定性）的判别和计算方法.该方法集中讨论从记录截面拾取震相这一过程所引起的判别误差.以震相前后一定时窗内的地震记录振幅的均方根之比为判别依据,找出误差分布范围并给出走时误差与振幅比的分级相关函数.由此,当震相确定后,计算程序将根据记录数据自动算出识别误差.实践证明该方法不仅更加客观真实、方便快捷,而且为今后震相提取工作的进一步科学规范打下了基础.     

A note on benchmarking of numerical models for density dependent flow in porous media

Verification of numerical models for density dependent flow in porous media (DDFPM) by the means of appropriate benchmark problems is a very important step in developing and using these models. Recently, Infinite Horizontal Box (IHB) problem was suggested as a possible benchmark problem for verification of DDFPM codes. IHB is based on Horton–Rogers–Lapwood (HRL) problem. Suitability of this problem for the benchmarking purpose has been investigated in this paper. It is shown that the wavelength of instabilities fails to be a proper criterion to be considered for this problem. However, the threshold of instability formation has been found to be appropriate for benchmarking purpose.     

A semi-empirical method for predicting hydrological drought magnitudes in the Canadian prairies

Abstract

A hydrological drought magnitude (M _T ) expressed in standardized terms is predicted on annual, monthly and weekly time scales for a sampling period of T years in streamflow data from the Canadian prairies. The drought episodes are considered to follow the Poisson law of probability and, when coupled with the gamma probability distribution function (pdf) of drought magnitude (M) in the extreme number theorem, culminate in a relationship capable of evaluating the expected value, E(M _T ). The parameters of the underlying pdf of M are determined based on the assumption that the drought intensity follows a truncated normal pdf. The E(M _T ) can be evaluated using only standard deviation (σ), lag-1 autocorrelation (ρ) of the standardized hydrological index (SHI) sequence, and a weighting parameter Φ (ranging from 0 to 1) to account for the extreme drought duration (L _T ), as well as the mean drought duration (L_m ), in a characteristic drought length (L_c ). The SHI is treated as standard normal variate, equivalent to the commonly-used standardized precipitation index. A closed-form relationship can be used for the estimation of first-order conditional probabilities, which can also be estimated from historical streamflow records. For all rivers, at the annual time scale, the value of Φ was found equal to 0.5, but it tends to vary (in the range 0 to 1) from river to river at monthly and weekly time scales. However, for a particular river, the Φ value was nearly constant at monthly and weekly time scales. The proposed method estimates E(M _T ) satisfactorily comparable to the observed counterpart. At the annual time scale, the assumption of a normal pdf for drought magnitude tends to yield results in close proximity to that of a gamma pdf. The M _T , when transformed into deficit-volume, can form a basis for designing water storage facilities and for planning water management strategies during drought periods.

Editor D. Koutsoyiannis; Associate editor C. Onof

Citation Sharma, T.C. and Panu, U.S., 2013. A semi-empirical method for predicting hydrological drought magnitudes in the Canadian prairies. Hydrological Sciences Journal, 58 (3), 549–569.     

水位电信号干扰识别的新方法

通过对十五台站水位数据干扰原因进行调查分析,得到一类受电信号变换干扰影响明显的台站。通过对该类台站的水位数据进行小波分解,利用小波模极大值原理,得到水位受明显干扰的时刻。通过对多个台站不同时段内电信号变换影响的水位数据分析,得到该类干扰的典型动态,以及识别方法。     

Ice cover exists: A quick method to delineate groundwater inputs in running waters for cold and temperate regions

Groundwater can be important in regulating stream thermal regimes in cold, temperate regions, and as such, it can be a significant factor for aquatic biota habits and habitats. Groundwater typically remains at a constant temperature through time; that is, it is warmer than surface water in winter and cooler in summer. Further, small tributaries are often dominated by groundwater during low flows of winter and summer. We exploit these thermal patterns to identify and delineate tributary/groundwater inputs along a frozen river (ice‐on) using publically available satellite data, and we tested the findings against airborne, thermal infrared (TIR) data. We utilize a supervised maximum likelihood classification (sMLC) to identify possible groundwater inputs while the river is in a frozen state (kappa coefficient of 96.77 when compared with visually delineated possible groundwater inputs). We then compare sMLC‐identified possible groundwater inputs with TIR‐classified groundwater inputs, which confirmed that there was no statistical difference (χ² = .78), that is, confirming that groundwater inputs can be delineated in north temperate river systems using available satellite imagery of the system's frozen state. Our results also established the spatial extent and influence of possible groundwater inputs in two seasons. The thermal plumes were longer and narrower in winter; this is likely related to seasonal differences in dispersion regimes. We hypothesize that differences between summer and winter is related to either (a) tributaries that are modulated by shading in summer or (b) aquifer disconnection from the river in winter owing to frozen ground conditions and lack of aquifer recharge. This method of establishing tributary/groundwater inputs and contributions to surface water thermal regimes is relatively simple and can be useful for science and management as long as “ice cover exists”; that is, the system can achieve a frozen state.     

A spatially distributed model for the assessment of land use impacts on stream temperature in small urban watersheds

Stream temperatures in urban watersheds are influenced to a high degree by changes in landscape and climate, which can occur at small temporal and spatial scales. Here, we describe a modelling system that integrates the distributed hydrologic soil vegetation model with the semi‐Lagrangian stream temperature model RBM. It has the capability to simulate spatially distributed hydrology and water temperature over the entire network at high time and space resolutions, as well as to represent riparian shading effects on stream temperatures. We demonstrate the modelling system through application to the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The results suggest that the model was able to produce realistic streamflow and water temperature predictions that are consistent with observations. We use the modelling construct to characterize impacts of land use change and near‐stream vegetation change on stream temperatures and explore the sensitivity of stream temperature to changes in land use and riparian vegetation. The results suggest that, notwithstanding general warming as a result of climate change over the last century, there have been concurrent increases in low flows as a result of urbanization and deforestation, which more or less offset the effects of a warmer climate on stream temperatures. On the other hand, loss of riparian vegetation plays a more important role in modulating water temperatures, in particular, on annual maximum temperature (around 4 °C), which could be mostly reversed by restoring riparian vegetation in a fairly narrow corridor – a finding that has important implications for management of the riparian corridor. Copyright © 2014 John Wiley & Sons, Ltd.