Spatial prediction model and its application to chemistry of atmospheric precipitation in Jordan

This study is concerned with the spatial variability of some wet atmospheric precipitation parameters such as; pH, conductivity (EC). The study also depicts the spatial variability of some ions (cations and anions) of atmospheric precipitation in Jordan such as, Ca²⁺, Mg²⁺, Na⁺ and K⁺, HCO₃⁻, Cl⁻, NO₃⁻ and SO₄²⁻. The basis of the work is to establish a relationship through the cumulative semivariogram technique between the distance ratios and the spatial dependence structure of the chemical composition of atmospheric precipitation. All semivariogram models are constructed in this study in order to understand the behavior of the spatial distribution. The spatial distributions of rainwater parameters show differences from station to station which is expressed in terms of angle, where the larger the angle the weaker the correlation. The semivariogram (SV) models are constructed to show the variation of the rainfall chemistry in Jordan. The SV models show weak correlation between mountain and leeside mountain stations, i.e. mountain and desert stations. On the other hand, good correlations are observed when transferring from south to north of the country. The larger is the found angle, the weaker is the correlation. For most of the SV model the correlation is found to be very weak between desert and mountainous locality. The Standard Regional Dependence Factor (SRDF) is used for prediction of the distribution of rain fall parameters. It shows the relative error between observed and predicted values of rainwater parameters. The overall regional relative error between the observed and estimated concentrations remains less than 15%.     

Groundwater contaminant source identification based on QS-ILUES

When groundwater pollution occurs,to come up with an efficient remediation plan,it is particularly important to collect information of contaminant source(location and source strength)and hydraulic conductivity field of the site accurately and quickly.However,the information can not be obtained by direct observation,and can only be derived from limited measurement data.Data assimilation of observations such as head and concentration is often used to estimate parameters of contaminant source.As for hydraulic conductivity field,especially for complex non-Gaussian field,it can be directly estimated by geostatistics method based on limited hard data,while the accuracy is often not high.Better estimation of hydraulic conductivity can be achieved by solving inverse groundwater problem.Therefore,in this study,the multi-point geostatistics method Quick Sampling(QS)is proposed and introduced for the first time and combined with the iterative local updating ensemble smoother(ILUES)to develop a new data assimilation framework QS-ILUES.It helps to solve the contaminant source parameters and non-Gaussian hydraulic conductivity field simultaneously by assimilating hydraulic head and pollutant concentration data.While the pilot points are utilized to reduce the dimension of hydraulic conductivity field,the influence of pilot points’layout and the ensemble size of ILUES algorithm on the inverse simulation results are further explored.     

Coupling urbanization analyses for studying urban thermal environment and its interplay with biophysical parameters based on TM/ETM+ imagery

Studies of urbanization and urban thermal environment are now attracting wide interests among scientists all over the world. This study investigated the influences of urbanization on urban thermal environment as well as the relationships of thermal characteristics to other biophysical variables in Guangzhou, China utilizing three dates of Landsat TM/ETM+ images acquired in 1990, 2000, and 2005, respectively. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban enlargement. As a key parameter for studying urban thermal characteristics, the land surface temperature (LST) was also retrieved from thermal infrared band of each TM/ETM+ dataset. Based on these parameters, the urban expansion, urban heat island effect and the relationships of LSTs to other biophysical parameters were then analyzed. Results indicated that the area ratio of impervious surface in Guangzhou increased significantly, which grew from 20.56% in 1990, to 34.72% in 2000, and further to 41.12% in 2005, however, the intensity of urban heat island was not always enlarged in observed years. In addition, Geostatistical analyses showed that the mean-centre of the impervious surface was moving towards the northwest during 1990–2005. And correlation analyses revealed that, at the pixel-scale, the association of LSTs to other two variables (vegetation abundance and percent impervious surface) was not straightforward, while LSTs possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional-scale, respectively. This study provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.     

地统计学在淡水生态学中的应用

建立在区域化定量理论基础上的地统计学是一门空间统计学分支学科,主要用于研究自然现象的相关性和依赖性。这一理论主要内容包括：半方差图（用以描述研究对象空间相关性）;Ｋｒｉｇｅ空间内插技术（通过空间上抽样点的调查数据对空间上未测点进行估计）;以及通过半方差图求算分形体的分形维数,本文在介绍该理论基本原理的基础上,探讨了其在淡水生态学上的实际应用。     

Spatial variability of soil available Zn and Cu in paddy rice fields of China

As a source of nutrient supplements, the deficiency or excess of micronutrients in soil is directly connected to the plant uptake and, thereby, status of micronutrients in the human population. Proper management of micronutrients requires an understanding of the variations of soil micronutrients across the fields. This study is to investigate the spatial patterns of soil available Zn and Cu in paddy rice fields. Four hundred and sixty three soil samples were taken in Hangzhou–Jiaxing–Huzhou (HJH) watershed in Zhejiang Province, China, and available Zn and Cu were analyzed using an atomic adsorption spectrometer. Geostatistical semivariograms analysis indicated that the available Zn and Cu were best fitted to a spherical model with a range of 40.5 and 210.4 km, respectively. There were moderate spatial dependences for Zn and Cu over a long distance and the dependence were attributed to soil types and anthropogenic activities. The overlay analysis of spatial patterns and soil types gave us greater understanding about how intrinsic factors affect the spatial variation of available micronutrients. Based on the above, macroscopically regionalized management of soil available micronutrients and the implications to potential risk were discussed.     

地统计学方法进展研究

地统计学近年来成为空间分析的重要工具，其应用领域广泛分布在自然科学的众多领域。系统地论述了地统计学理论方法的进展，给出地统计学的总体理论框架，它包括局部估值、不确定性预测、随机模拟及多点地统计学四部分。并指出所有这些方法的理论基础是随机变量理论，其核心是利用变异函数获得研究对象的空间分布规律。同时，分别介绍了每个部分的具体方法，特别提到了新发展的多点地统计学方法。最后对地统计学的软件应用加以总结，指出将GIS与地统计学相结合是一种必然的趋势。     

地质统计学新进展

地质统计学(空间信息统计学)是数学地质领域中一门发展迅速且有着广泛应用前景的新兴科学。结合地质统计学发展现状,对地质统计学的新进展进行了研究,从地质统计学理论体系、应用及软件开发等方面探讨了地质统计学的发展前缘。并指出时空多元技术、条件模拟、非参数和非线性将是地质统计学今后的发展趋势。     

Simulation of mineral grades with hard and soft conditioning data: application to a porphyry copper deposit

This work deals with the geostatistical simulation of mineral grades whose distribution exhibits spatial trends within the ore deposit. It is suggested that these trends can be reproduced by using a stationary random field model and by conditioning the realizations to data that incorporate the available information on the local grade distribution. These can be hard data (e.g., assays on samples) or soft data (e.g., rock-type information) that account for expert geological knowledge and supply the lack of hard data in scarcely sampled areas. Two algorithms are proposed, depending on the kind of soft data under consideration: interval constraints or local moment constraints. An application to a porphyry copper deposit is presented, in which it is shown that the incorporation of soft conditioning data associated with the prevailing rock type improves the modeling of the uncertainty in the actual copper grades.     

The hydrochemical facies and anomalous fluoride content in the Serra Geral aquifer system,southern Brazil: a GIS approach with tectonic and principal component analysis

Groundwater with high fluoride content and water mixture patterns were studied in Serra Geral aquifer system (SGAS) using three aspects, principal component analysis (PCA), tectonic scenery and hydrochemical interpretation from 309 groundwater chemical data information from deep wells. A four-component model is suggested and explains 81% of total variance in the PCA. Six hydrochemical facies were identified. These facies suggest two different fluoride sources. Tectonic approach shows the relationship between defined hydrochemical facies and regional fracture control. The applied methodology reveals a minimum level to understand hydrochemical mixtures. The fluoride enrichment mechanisms into the groundwater are comprised in advance to guide the future uses of SGAS to the public supply.