用最大熵谱分析进行等时沉积序列的相关性对比

本文以鄂尔多斯盆地东部镇川堡含气区的下二叠统下石盒子组为例,提出对等时沉积序列进行最大熵谱分析的方法,以便寻找各地层序列间的历史成因联系和彼此间的亲疏程度,从而较好地解决了诸如古水流方向、河道形态及湖泊岸线位置等问题,研究结果表明,镇川堡含气区下石盒子组沉积物源来自东北付谷、宝德一带,古水流方向北东30-60°,发育两个河流系统,稳定主河道4条.下石盒子组地层序列最大熵谱分析的最佳滤波阶数m=62,谱跨度K的最佳参数为200.     

用最大熵谱分析进行等时沉积序列的相关性对比

本文以鄂尔多斯盆地东部镇川堡含气区的下二叠统下石盒子组为例,提出对等时沉积序列进行最大熵谱分析的方法,以便寻找各地层序列间的历史成因联系和彼此间的亲疏程度,从而较好地解决了诸如古水流方向、河道形态及湖泊岸线位置等问题,研究结果表明,镇川堡含气区下石盒子组沉积物源来自东北付谷、宝德一带,古水流方向北东30—60°,发育两个河流系统,稳定主河道4条.下石盒子组地层序列最大熵谱分析的最佳滤波阶数m=62,谱跨度K的最佳参数为200.     

桩基检测中的最大熵谱分析

本文利用最大熵谱法的原理对桩基检测信号进行谱分析,结果表明,与付氏谱相比,最大熵谱具有更高的精度.     

基于MEM1谱分析的水文时间序列隐含周期特性研究

水文时间序列的隐含周期(本文将简单周期、复合周期及近似周期等统称为隐含周期)的识别、判定是一个重要而又较为困难的问题,相对成熟和有效的做法是对其进行频谱分析。建立在最大熵原理(POME)基础之上的MEM1谱分析,克服了传统谱分析方法的诸多不足,具有频谱光滑、分辨率高等独特优势。为此,以黄河花园口(秦厂)测站年径流系列、月径流系列和年最大洪峰流量序列隐含周期特性的研究为例,探讨了MEM1谱分析在水文时间序列隐含周期特性中的应用。     

最大熵功率谱计算磁源深度方法应用初探

本文介绍了应用最大熵功率谱计算磁源深度的方法原理、理论模型试算结果及在方法应用方面的改进措施,肯定了利用磁场水平导数的最大熵功率谱计算深度的效果。     

气候变化对挠力河径流量影响的定量分析

三江平原位于黑龙江省东北部,是中国沼泽湿地集中分布区且面积最大的区域,挠力河作为该区域的一条典型沼泽性河流,其径流演变过程受到气候变化和人类活动的双重影响.文中利用水量平衡法和降水-径流经验模型,定量分析了变化期气候变化对径流的影响,并比较了两种方法的优劣性,研究结果表明:50年来挠力河变化期(1968~2005年)内的年径流量的变化大约40%是由气候变化引起.气候变化对径流量影响的主导因素是降水量的变化,降水量变化对宝清站和菜嘴子站径流量减少的贡献率分别为43%和35%,蒸发量变化对两水文站径流量减少的贡献率为10%左右.利用水量平衡法研究气候变化对河流径流量的影响,其研究结果要优于一般的降水-径流经验模型法,但经验模型也不失为一种快速且简便的方法.     

基于Halphen分布和最大熵的洪水频率分析

设计洪水估算值对水利水电工程的设计规划至关重要,其关键是选择合适的分布线型和参数估计方法。目前采用单一的频率曲线进行水文分析计算,其设计结果具有较大的不确定性。引入Halphen分布函数进行洪水频率分析,并提出了基于最大熵原理的参数估计方法。利用丹江口水库1929~2014年的年最大日流量资料系列,分析检验Halphen分布的拟合效果,并与传统的分布进行比较。结果表明,Halphen函数具有灵活的形式和较好的尾部特征,适合于水文频率分析,其拟合结果基本优于其他的传统分布。     

最大熵原理在水文水资源科学中的应用

简介最大熵原理的基本概念、理论和该原理在水文水资源科学领域中应用研究的进展,综述水文频串分析中推导概率分布和参数估计,时间序列最大熵谱分析等方面的研究成果,展望今后的研究趋向和应用前景。     

非平稳条件下北京市最大月降水量频率特征分析

为探究气候变化下极端降水的频率变化特征,基于北京市22个雨量站实测月降水量数据,以时间为协变量构建平稳和非平稳GEV模型,对北京市最大月降水量序列(极值降水序列)进行模拟和频率分析,并采用Bootstrap方法对频率分析结果的不确定性进行评价.结果表明:所有极值降水序列的最优概率分布模型均为非平稳GEV模型,该模型能够...     

Stochastic analyses of maximum daily rainfall series recorded at two stations across the Mediterranean Sea

Independence, stationarity, homogeneity, trend, and periodicity tests are applied on 48-year-long complete and 79-year-long incomplete maximum daily rainfall series recorded at Alexandria, Egypt, and on 61-year-long maximum daily rainfall series recorded at Antalya, Turkey, which are located at the southeastern and northeastern shores of the Mediterranean Sea. The results indicate no significant trend and no periodicity in mean, and both series are independent and homogeneous. Linear regression trend test applied to the 10 % highest part of the Alexandria series indicated a significant increasing trend. Next, frequency analysis is applied on each of these series by the probability distributions of Gumbel, general extreme-values, three-parameter log-normal, Pearson-3, log-Pearson-3, log-logistic, generalized Pareto, and Wakeby. The distributions, except for the generalized Pareto and Wakeby, pass the χ ² and Kolmogorov–Smirnov goodness-of-fit tests at 90 % probability. By visual inspection of the plots of histograms together with the probability density functions, and by the results of the χ ², Kolmogorov–Smirnov, and probability plot correlation coefficient tests, the general extreme-value distribution whose parameters are computed by the method of probability-weighted moments is deemed to be suitable for these two maximum daily rainfall series.     

On the equivalence of kriging and maximum entropy estimators

This study compares kriging and maximum entropy estimators for spatial estimation and monitoring network design. For second-order stationary random fields (a subset of Gaussian fields) the estimators and their associated interpolation error variances are identical. Simple lognormal kriging differs from the lognormal maximum entropy estimator, however, in both mathematical formulation and estimation error variances. Two numerical examples are described that compare the two estimators. Simple lognormal kriging yields systematically higher estimates and smoother interpolation surfaces compared to those produced by the lognormal maximum entropy estimator. The second empirical comparison applies kriging and entropy-based models to the problem of optimizing groundwater monitoring network design, using six alternative objective functions. The maximum entropy-based sampling design approach is shown to be the more computationally efficient of the two.     

ARC/INFO在流域水文分析中的应用

以吉林东部某山区小流域水文分析为例,将地理信息系统(GIS)与流域研究相结合,运用ARC/INFO的图像处理功能建立流域数字高程模型(DEM),利用其表面分析功能进行坡度、坡向、流线和流域识别等分析,实现GIS在流域水文分析中的应用。结果表明:运用ARC/INFO分析得到的流域坡度、坡向、流线及流域边界划分合理,输出结果直观美化,并在此基础上预测降水的汇流方向,效果较好。实现了对地形的三维化,提供了一种山区流域水文分析方法。     

Estimation of semivariograms by the maximum entropy method

A wide variety of semivariograms may be represented in terms of a first- or second-order autoregressive (AR) process, and the nugget effect may be included by use of a moving average (MA) process. The weighting parameters for these models have a simple functional dependence on the value of the sill and the semivariance at the first and second lag. These may be estimated either graphically from the semivariogram or directly from the computed values. Improved spectral estimates of geophysical data have been obtained by the use of the maximum entropy method, and the necessary equations were adapted here for the estimation of the weighting parameters of the AR and the MA processes. Comparison among the semivariograms obtained for the ideal case, the observed case, and the estimated case for artificial series show excellent correspondence between the ideal and estimated while the observed semivariogram may show marked divergence.     

多年冻土区风火山流域降水河水稳定同位素特征分析

由于多年冻土区流域土壤冻融过程对水循环影响的复杂性,水循环物理过程观测存在困难和不足,而利用稳定同位素方法可以有效地解决该问题。因此,基于2009年长江源风火山流域夏季定点降水和河水δD和δ¹⁸O,对研究区降水河水稳定同位素特征进行分析。结果表明,研究区夏季降水δD和δ¹⁸O受到降水量和温度的双重影响,即受海洋性和大陆局地气团的交替影响。河水氢氧同位素的季节变化和空间差异与壤中流、地下水补给河流的季节差异和植被覆盖的空间差异有关。随着地温升高和土壤冻融锋面的迁移,河水补给来源和同位素特征发生改变,表明土壤冻融变化对多年冻土流域径流过程起到重要作用。此外,蒸发分馏作用是研究区河水同位素的重要影响因素。     

Determination of optimal numbers of class intervals using maximum entropy

Based on the maximum entropy concept, optimal numbers of class intervals(K) for a closed array of samples has been determined. From the analysis, two values ofK (8 and 19) are selected as the most appropriate. ForK=8, the probability of occurrence on each unequal-size interval isp _i=0.125, whereasK=19 results inp _i=0.0526. An objective method for determining interval limits, modified from a previous method by Full et al. (1984), is also included.Contribution 114, Instituto Argentino de Oceanografia.     

Chemistry and source identification of wet precipitation in a rural watershed of subtropical China

South China is one of the regions severely suffering from acid rain in the world.However,few systematic studies of rural precipitation chemistry have been performed in comparison with the extensive studies on their urban counterparts of this region.In order to characterize the current acid rain status and identify its possible sources in the rural area of South China,we analyzed precipitation collected event by event from a rural forested watershed in southern Anhui Province between March 2007 and February 2010.The results showed that the concentrations of major ions within precipitation in the studied rural area were significantly lower than those reported for the urban areas of the same latitude in China.Nevertheless,the precipitation acidity(with an average pH value of 4.49) and the frequency of acid rain(95%) were considerably high.The relatively high ratio of(SO42+ NO 3)/(Ca2+ +NH4+) was the main cause of acid rain in this rural area,as SO 2 and NO x were the main precursors of acid rain,while Ca2+ and NH4+acted as the dominant neutralizers to the acidity.Source identification indicated that Ca2+ and Mg2+ mainly were derived from alkaline dust,SO42,NO 3 and NH4+originated mainly from anthropogenic sources such as industrial and agricultural activities,most Na +,Cl,K + and some of Mg2+ were derived from the sea.The results suggested that the major ions within precipitation in the rural area of South China were related to the meso-scale and long-range transport of particles and aerosols in the air.     

降雨和地形地貌对水文模型模拟结果的影响分析

概念性水文模型数量众多,判断模型是否适合研究流域可以通过模拟结果来体现,但是熟悉流域的产汇流特性可以筛选模型,从根源上大量减少工作量,也可以解决相似流域无资料的问题。选取6种概念性水文模型,以马渡王、板桥和志丹这3个半湿润与半干旱流域为研究区域,探讨流域特性与模型结构之间的关系,并通过降雨和地形地貌分析其对模型模拟结果的影响。研究结果表明,流域地形及植被对产汇流过程有重要影响,由于局部产流现象严重,河道坡度影响大于流域平均坡度,当区域气候条件相差不大时,地形地貌比降雨对流域产汇流特性影响更大。因此对于水文模型的选择,可以在熟悉流域产汇流特性的基础上因地制宜,必要时可以增加适合研究流域的模块来获得更好的预报,在半干旱与半湿润流域,同时具有蓄满和超渗机制的模型能得到更好的应用。     

Effects of linear trend and mean value on maximum entropy spectral analysis

Using artificial samples, it is shown that, even for the method of maximum entropy spectral analysis (mesa) evolved by Burg, a presence of a linear trend gives distortions (frequency shifts) in the low frequency (high periodicity) region and hence, it is advisable to eliminate linear trends before attempting spectral analysis. The effect of the presence of a non-zero mean is not very definite; but, very large mean values seem to reduce the sharpness of the peaks. The implications of these findings for the results by Jin and Thomas for some geomagnetic parameters are discussed.     

Spatial prediction of soil properties in a watershed scale through maximum likelihood approach

Surface map of soil properties plays an important role in various applications in a watershed. Ordinary kriging (OK) and regression kriging (RK) are conventionally used to prepare these surface maps but generally need large number of regularly girded soil samples. In this context, REML-EBLUP (REsidual Maximum Likelihood estimation of semivariogram parameters followed by Empirical Best Linear Unbiased Prediction) shown capable but not fully tested in a watershed scale. In this study, REML-EBLUP approach was applied to prepare surface maps of several soil properties in a hilly watershed of Eastern India and the performance was compared with conventionally used spatial interpolation methods: OK and RK. Evaluation of these three spatial interpolation methods through root-mean-squared residuals (RMSR) and mean squared deviation ratio (MSDR) showed better performance of REML-EBLUP over the other methods. Reduction in sample size through random selection of sampling points from full dataset also resulted in better performance of REML-EBLUP over OK and RK approach. The detailed investigation on effect of sample number on performance of spatial interpolation methods concluded that a minimum sampling density of 4/km² may successfully be adopted for spatial prediction of soil properties in a watershed scale using the REML-EBLUP approach.