Spatial variability of soil properties in relation to land use and topography in a typical small watershed of the black soil region,northeastern China

Soil degradation resulted from unreasonable land use and erosion has been a serious problem in the black soil region of northeastern China. This paper seeks to understand the relationships between topsoil properties and topography and land use for land management targeting at improving soil quality in this region. A total of 292 soil samples and 81 volumetric rings were taken from a typical small watershed of the region in June 2005 for examining total carbon (TC), total nitrogen (TN), soil texture (classified into gravel, sand, silt, and clay), and bulk density (ρ _b), respectively. Spatial variability of these soil properties was evaluated with classical statistics and geostatistics methods. The results of classical statistics indicated that TC, TN, sand, silt, clay content, and ρ _b were moderate variables while gravel had great variability. Soil properties were mainly correlated to slope position, elevation and land types. Geostatistical analyses showed that the spatial autocorrelation for TC, TN, and silt was weak, strong for clay and moderate for and ρ _b sand, respectively. The spatial variations of soil properties are affected comprehensively by topographic factors, land use, erosion, and erosion control in this watershed. Past erosion, however, is the most important component to induce change of soil properties. In this small watershed, current soil and water conservation measures play an important role in controlling soil loss. But the restoration of soil properties was unsatisfactory. Comparing with untilled soil of this region, TC, TN, silt content are excessively low; whereas ρ _b, sand and clay content are excessively high; gravel appears at most sampling locations. It is necessary for improving soil properties to protect forest and grassland and change cultivation system of farmlands.     

Hydrogeological modeling of radionuclide transport in low permeability media: a comparison between Boom Clay and Ypresian Clay

Deep low-permeability clay layers are considered as suitable environments for disposal of high-level radioactive waste. In Belgium, the Boom Clay is the reference host formation and the Ypresian Clay an alternative host formation for research and safety and feasibility assessment of deep disposal of nuclear waste. In this study, two hydrogeological models are built to calculate the radionuclide fluxes that would migrate from a potential repository through these two clay formations. Transport parameter heterogeneity is incorporated in the models using geostatistical co-simulations of hydraulic conductivity, diffusion coefficient and diffusion accessible porosity. The calculated radionuclide fluxes in the two clay formations are compared. The results show that in the Ypresian Clay larger differences between the fluxes through the lower and the upper clay boundary occur, larger total output radionuclide amounts are calculated and a larger effect of parameter heterogeneity on the calculated fluxes is observed, compared to the Boom Clay.     

Seabird guano influences on desert islands: soil chemistry and herbaceous species richness and productivity

An understanding of the effects of guano deposition on arid soil chemistry and the consequences for plant communities is lacking. This study examined patterns of herbaceous species richness and productivity, soil chemistry, soil moisture and soil respiration on 11 islands in the Gulf of California, six of which receive seabird guano deposition. Species richness was significantly lower on islands with guano (“Bird” islands) than islands without guano (“Non-bird” islands), with very little overlap in species composition; however, productivity was significantly greater on Bird than on Non-bird islands. As expected, Bird island soils had higher concentrations of NO₃⁻, NH₄⁺ and total nitrogen (N) than Non-bird island soils; and, measurements of δ¹⁵N indicate that the higher concentrations of N were derived from guano. We also found that soil moisture and respiration were significantly higher, but pH was significantly lower, on Bird than Non-bird islands. These results suggest that guano deposition in deserts stimulates productivity—even in dry years—due to elevated N and, indirectly, soil moisture. Guano deposition also results in a decrease in species richness and a change in species composition probably due to elevated N, N toxicity, or low pH. However, we also found that pH varied more on Bird than on Non-bird islands; and that salinity—while not different between island types—was significantly patchier on Bird than on Non-Bird islands. These results suggest that guano deposition affects not only the general chemical composition of soils, but also results in greater spatial variation in soil chemical composition, which may ultimately affect species richness and composition. Therefore, understanding spatial patterning in soil chemistry as a result of guano deposition is critical for understanding guano effects on plant richness and productivity.     

乌鲁木齐市米东区农田土壤重金属含量的空间分布特征

利用地理信息系统（GIS）及地统计学方法,对乌鲁木齐米东区农田土壤中重金属（Hg、Cu、Zn、Pb、Ni、Cd及Cr）的含量进行空间变异性分析。结果表明：除Cu、Zn、Pb和Hg超过土壤背景值外,7种重金属的平均含量均未超过国家环境质量二级标准（GB15618-1995）;7种重金属均具有较好的空间变异结构,可以用指数模型、球状模型和高斯模型拟合,且具有不同程度的块金效应;Cd、Cr具有强烈的空间自相关性,Pb、Ni、Cu、Zn和Hg属中等强度空间相关, 说明其含量受外源污染的影响较大;采用普通克里格插值法得出7种重金属的空间分布图,除Cd空间分布规律不明显外,其它6种重金属均存在显著的空间分布规律。     

利用 GIS地理统计模块预测海南岛植被指数季节性变化趋势

虽然采用遥感图像提取的植被指数在空间上能较好的反映作物的状况,但其不能预测植被指数在空间上的变化范围,如果能从整体上了解不同市县在不同季节的平均植被指数值,就可以对该区域整体植被状态进行量化分析,也就可以从大范围内进行植被指数的预测分析.利用地理信息系统(GIS)和地统计学相结合的地理统计分析模块(ArcGIS Geostatistical Analyst),根据MODIS遥感数据提取的每季度不同市县平均NDVI植被指数,采用Kriging插值的方法分析了海南岛归一化植被指数(NDVI)季节性变化趋势,并     

The practice of fast conditional simulations through the LU decomposition of the covariance matrix

The LU-matrix approach to conditional simulations allows fast generation of large numbers of realizations for a given stochastic process. Simplicity, flexibility, and quality are its main advantages. Its implementation for cases where dense grids and/or large numbers of conditioning data cause computational problems is discussed. A case study is presented.     

Geophysical data integration,stochastic simulation and significance analysis of groundwater responses using ANOVA in the Chicot Aquifer system,Louisiana, USA

Data integration is challenging where there are different levels of support between primary and secondary data that need to be correlated in various ways. A geostatistical method is described, which integrates the hydraulic conductivity (K) measurements and electrical resistivity data to better estimate the K distribution in the Upper Chicot Aquifer of southwestern Louisiana, USA. The K measurements were obtained from pumping tests and represent the primary (hard) data. Borehole electrical resistivity data from electrical logs were regarded as the secondary (soft) data, and were used to infer K values through Archie’s law and the Kozeny-Carman equation. A pseudo cross-semivariogram was developed to cope with the resistivity data non-collocation. Uncertainties in the auto-semivariograms and pseudo cross-semivariogram were quantified. The groundwater flow model responses by the regionalized and coregionalized models of K were compared using analysis of variance (ANOVA). The results indicate that non-collocated secondary data may improve estimates of K and affect groundwater flow responses of practical interest, including specific capacity and drawdown.

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Résumé  L’intégration de données entre en jeu lorsque plusieurs niveaux intermédiaires d’assistance sont nécessaires pour corréler données primaires et secondaires de diverses manières. Le présent article décrit une méthode géostatistique qui intègre les mesures de conductivité hydraulique (K) et les données de résistivité électrique, afin d’estimer plus efficacement la distribution de K dans l’Aquifère Supérieur de Chicot, au sud-ouest de la Louisiane (Etats-Unis). Les mesures de K sont issues des pompages d’essai et représentent les données primaires (“dures”). Les données des diagraphies de résistivité électrique ont été considérées comme des données secondaires (“molles”), à partir desquelles les valeurs de K ont été déduites, par la loi d’Archie et l’équation de Kozeny-Carman. Un pseudo semi-variogramme croisé a été développé afin de pallier à l’absence de colocalisation des données de résistivité. Les incertitudes sur les semi-variogrammes automatiques et sur les pseudo semi-variogrammes croisés ont été quantifiées. Les réponses du modèle d’écoulement des eaux souterraines aux modèles régionalisés et co-régionalisés de K ont été comparés, par les analyses de variance (ANOVA). Les résultats montrent que les données secondaires non-colocalisées peuvent améliorer les estimations de K, et affecter efficacement les réponses des écoulements souterrains, y compris les débits spécifiques et les rabattements.

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Resumen  La integración de datos es un gran desafío cuando existen diferentes niveles de apoyo entre datos primarios y secundarios que es necesario correlacionar de varias maneras. Se describe un método geoestadístico el cual integra mediciones de conductividad hidráulica (K) y datos de resistividad eléctrica para tener una mejor estimación de la distribución de K en el Acuífero Chicot Superior del suroeste de Luisiana, Estados Unidos de América. Las mediciones de K se obtuvieron de pruebas de bombeo y representan los datos primarios (duros). Los datos de sondeos de resistividad eléctrica se consideraron como datos secundarios (suaves) y se usaron para inferir valores de K a través de la ley de Archie y la ecuación de Carman-Kozeny. Se desarrolló un pseudo semivariograma cruzado para enfrentar la falta de colocación de datos de resistividad. Se cuantificaron las incertidumbres en los auto-semivariogramas y en los semivariogramas cruzados. Las respuestas del modelo de flujo de agua subterránea por los modelos coregionalizados y regionalizados de K se compararon usando el análisis de varianza (ANOVA). Los resultados indican que los datos secundarios no colocados pueden mejorar los estimados de K y afectar las respuestas de flujo de agua subterránea de interés práctico, incluyendo capacidad específica y descenso.

     

Geostatistical study of the feldspar content and quality of a granite deposit

In order to characterise the saleable feldspar in a granite deposit, a methodology was developed in accordance with the exploitation process. This consisted of mechanically extracting the surface layer of the batholith and separating the feldspar from the quartz using the granulometric separation method, given that the size of the grains of the feldspar is greater than that of quartz.

Following washing, grinding and magnetic separation of the feldspar in order to eliminate the ferromagnesium minerals, the saleable feldspar was characterised in terms of the factors that determine its market value, namely, its content in Al₂O₃, SiO₂, Na₂O and K₂O.

Following the opening of prospecting pits in the granite massif, samples were analysed in the laboratory using three different granulometric cuts and by reproducing the treatment process. The values for the quality variables of saleable feldspar were obtained, and the results were interpolated to the entire deposit using the kriging method.

In order to summarise the information from the above-mentioned variables, a quality index was constructed using multivariate statistics and by employing market criteria, and subsequently, the values of the index were interpolated to the entire deposit using bidimensional kriging.

The map of saleable quality feldspar from the deposit permits both affirmation of the treatment process yield for each granulometric cut and the planning of extraction from the deposit to obtain a homogeneous quality in the saleable feldspar.     

Optimizing a piezometric network in the estimation of the groundwater budget: a case study from a crystalline-rock watershed in southern India

An estimate of the groundwater budget at the catchment scale is extremely important for the sustainable management of available water resources. Water resources are generally subjected to over-exploitation for agricultural and domestic purposes in agrarian economies like India. The double water-table fluctuation method is a reliable method for calculating the water budget in semi-arid crystalline rock areas. Extensive measurements of water levels from a dense network before and after the monsoon rainfall were made in a 53 km² watershed in southern India and various components of the water balance were then calculated. Later, water level data underwent geostatistical analyses to determine the priority and/or redundancy of each measurement point using a cross-validation method. An optimal network evolved from these analyses. The network was then used in re-calculation of the water-balance components. It was established that such an optimized network provides far fewer measurement points without considerably changing the conclusions regarding groundwater budget. This exercise is helpful in reducing the time and expenditure involved in exhaustive piezometric surveys and also in determining the water budget for large watersheds (watersheds greater than 50 km²).