Correcting the Smoothing Effect of Ordinary Kriging Estimates

The smoothing effect of ordinary kriging is a well-known dangerous effect associated with this estimation technique. Consequently kriging estimates do not reproduce both histogram and semivariogram model of sample data. A four-step procedure for correcting the smoothing effect of ordinary kriging estimates is shown to be efficient for the reproduction of histogram and semivariogram without loss of local accuracy. Furthermore, this procedure provides a unique map sharing both local and global accuracies. Ordinary kriging with a proper correction for smoothing effect can be revitalized as a reliable estimation method that allows a better use of the available information.     

Statistical identification of orographic effects in the regional analysis of extreme rainfall

Regional models of extreme rainfall must address the spatial variability induced by orographic obstacles. However, the proper detection of orographic effects often depends on the availability of a well‐designed rain gauge network. The aim of this study is to investigate a new method for identifying and characterizing the effects of orography on the spatial structure of extreme rainfall at the regional scale, including where rainfall data are lacking or fail to describe rainfall features thoroughly. We analyse the annual maxima of daily rainfall data in the Campania region, an orographically complex region in Southern Italy, and introduce a statistical procedure to identify spatial outliers in a low order statistic (namely the mean). The locations of these outliers are then compared with a pattern of orographic objects that has been a priori identified through the application of an automatic geomorphological procedure. The results show a direct and clear link between a particular set of orographic objects and a local increase in the spatial variability of extreme rainfall. This analysis allowed us to objectively identify areas where orography produces enhanced variability in extreme rainfall. It has direct implications for rain gauge network design criteria and has led to promising developments in the regional analysis of extreme rainfall. Copyright © 2015 John Wiley & Sons, Ltd.     

Data analysis of a revisited exploration geochemical dataset of quartz porphyrites from SW Jordan using GIS techniques

The spatial distribution of Cu and its pathfinder elements in quartz porphyrites along Wadi Araba was studied in order to gain an insight about the geologic framework of Cu mineralization in the area. A geochemical exploration data set of 242 samples was revisited. Multivariate statistical and geostatistical analysis were performed on the data set. The objectives of the study were to define Cu relationships with its possible pathfinder elements and to figure out whether geostatistical treatment of exploration data would help telescoping already existing Cu mineralization in Wadi Araba, SW Jordan. Factor analysis and hierarchical cluster analysis were performed on the data set. The results of which indicate that seven elements, namely, Ba, Cr, Mn, Ni, Sc, Sr and V can be considered as pathfinder elements for Cu. Significant correlations do exist between Cu and these elements. The encountered experimental semivariograms of the defined pathfinders were fit to exponential models with varying nugget effects with the exception of Mn which was fit to the spherical model. Ordinary kriging was found to be most appropriate to generate geochemical exploration maps. The applied methods succeeded in deriving valuable information and visualizing the already existing Cu mineralization in Wadi Abu Khusheiba area.     

基于模糊预测对象的证据权方法及其在土地沙漠化评价中的应用

为了使在地理信息系统中被广泛用于点事件预测的证据权方法能对面事件进行评价和预测, 提出了一种新的基于模糊训练层的证据权方法.它是一种更广泛的证据权方法, 与普通证据权方法所不同的是, 它的训练层是模糊集合, 其取值是它的隶属度.通过适当的变换也可以把点训练层转换为模糊集合.因此, 该方法可以对面事件、点事件和线事件进行评价和预测.该方法可以处理训练层和证据层均为模糊集合的情况, 被称为双重模糊证据权方法.作为该方法的一个应用实例, 本文介绍毛乌素沙漠边缘的晋陕蒙地区土地沙漠化评价的应用实例.      

卫星遥感海表温度反演结果再处理研究

针对东海渔区的海洋渔业应用,以中国东海渔区(121°～124°E,29°～32°N)NOAA level-2B SST反演数据为例,通过不同空间内插方法的对比分析,得到最优内插模型,继而获取海表温度图像和海温等值线图,为海洋渔业提供必要的基础资料.     

基于GIS的近海剩余环境容量计算模型

探讨一种基于GIS 克里格插值方法的剩余环境容量计算方法, 通过GIS 地统计分析插值模型将水质模拟问题转化为数学统计问题, 充分利用水质水体、沉积物监测数据, 采用克里格插值法对污染物浓度和水深在局部海域内进行插值, 将研究区域离散为一个个的均匀栅格单元, 比较每个单元污染物浓度与水质目标之间的差值, 从而估算得到研究海域的剩余环境容量。通过2009 年8 月锦州湾剩余环境容量的计算实例表明, 基于GIS 的剩余环境容量初步计算方法在资料缺乏地区是十分简便、有效的, 这为海域开发利用区环境管理与规划提供了参考。     

利用克里金技术标定新疆及附近地区P/S震相幅值比及其在地震事件识别中的应用

针对中国的乌鲁木齐台（WMQ）和哈萨克斯坦的马坎奇台（MAK）,采用贝叶斯克里金技术建立了新疆及附近地区地震事件的震相幅值比的校正曲面,并分析了校正曲面与地震波传播路径的关系,以及校正曲面对于改善震相幅值比判据识别效果的有效性.分析结果表明,建立的校正曲面基本合理,结合传播路径差异和地震波传播规律,能够较好地解释校正曲面的起伏特征. 而且,在传播路径差异较大,使得震相幅值比经震中距校正后离散度仍然较高的情况下,利用校正曲面修正震相幅值比,可以进一步降低其离散度,从而改善判据的识别效果.经校正曲面修正后,对天然地震的误识率由16.3%下降为5.2％.      

Improving kriging of groundwater level data using nonlinear normalizing transformations—a field application

Abstract

The present research study investigates the application of nonlinear normalizing data transformations in conjunction with ordinary kriging (OK) for the accurate prediction of groundwater level spatial variability in a sparsely-gauged basin. We investigate three established normalizing methods, Gaussian anamorphosis, trans-Gaussian kriging and the Box-Cox method to improve the estimation accuracy. The first two are applied for the first time to groundwater level data. All three methods improve the mean absolute prediction error compared to the application of OK to the non-transformed data. In addition, a modified Box-Cox transformation is proposed and applied to normalize the hydraulic heads. The modified Box-Cox transformation in conjunction with OK is found to be the optimal spatial model based on leave-one-out cross-validation. The recently established Spartan semivariogram family provides the optimal model fit to the transformed data. Finally, we present maps of the groundwater level and the kriging variance based on the optimal spatial model.

Editor D. Koutsoyiannis; Associate editor A. Montanari

Citation Varouchakis, E.A., Hristopoulos, D.T., and Karatzas, G.P., 2012. Improving kriging of groundwater level data using nonlinear normalizing transformations—a field application. Hydrological Sciences Journal, 57 (7), 1404–1419.     

When do we need a trend model in kriging?

Under usual estimation practice with local search windows for data and for interpolation situations, universal kriging and ordinary kriging yield the same estimates, using a data set with apparent trend, for both the unknown attribute and its trend component. Modeling the trend matters only in extrapolation situations. Because conditions of the case study presented arise most frequently in practice, the simpler ordinary kriging is the preferred option.