Structural Controls and Predictive Mapping of Tin, Niobium and Tantalum Mineralization Associated with the Mayo Darlé Stanniferous Granitoids;Contributions of Geostatistics

The aim of this study of the spatial dispersion of tin, niobium and tantalum mineralization associated with the Mayo Darlé granitoids was to produce prospecting guides through predictive maps of Sn, Nb and Ta in the region. It was based on a database (in appendix) obtained after analysis of rock samples (greisens and quartz veins) collected in the field, using a portable X-ray fluorescence (XRF) spectrometer. Two approaches were used: 1) structural studies in the field using the directions of veins and fractures 2) the use of variographic maps, an essential element in geostatistics for determining directional anisotropies. A joint synthesis of the modelling results shows that tin, tantalum and niobium mineralization at Mayo Darlé is concentrated along strike intervals N315E to N320E, with mineralization also occurring along strike N35E for high-grade Sn, medium-grade Ta and low-grade Nb. In short, mineral concentrations disperse progressively in space: positively from east to west for tantalum and niobium, and inversely for tin.

Spatial-temporal difference between nitrate in groundwater and nitrogen in soil based on geostatistical analysis

The study of temporal and spatial variations of nitrate in groundwater under different soil nitrogen environments is helpful to the security of groundwater resources in agricultural areas.In this paper,based on 320 groups of soil and groundwater samples collected at the same time,geostatistical analysis and multiple regression analysis were comprehensively used to conduct the evaluation of nitrogen contents in both groundwater and soil.From May to August,as the nitrification of groundwater is dominant,the average concentration of nitrate nitrogen is 34.80 mg/L;The variation of soil ammonia nitrogen and nitrate nitrogen is moderate from May to July,and the variation coefficient decreased sharply and then increased in August.There is a high correlation between the nitrate nitrogen in groundwater and soil in July,and there is a high correlation between the nitrate nitrogen in groundwater and ammonium nitrogen in soil in August and nitrate nitrogen in soil in July.From May to August,the area of low groundwater nitrate nitrogen in 0-5 mg/L and 5-10 mg/L decreased from 10.97%to 0,and the proportion of high-value area(greater than 70 mg/L)increased from 21.19%to 27.29%.Nitrate nitrogen is the main factor affecting the quality of groundwater.The correlation analysis of nitrate nitrogen in groundwater,nitrate nitrogen in soil and ammonium nitrogen shows that they have a certain period of delay.The areas with high concentration of nitrate in groundwater are mainly concentrated in the western part of the study area,which has a high consistency with the high value areas of soil nitrate distribution from July to August,and a high difference with the spatial position of soil ammonia nitrogen distribution in August.

An Assessment and Geostatistics of Land-Use and Selected Physico-Chemical Properties of Soils in the Mount Cameroon Area

This work investigated the land-use/land-cover and some physico-chemical properties of the soils of Mt Cameroon and presented same in maps. ArcGIS Pro mapping software, Landsat images, Global Positioning Systems (GPS) coordinates collected from the field combined with updated shape files from competent services were used to produce the location and land-use/land-cover maps. Sixteen topsoil samples (0 - 20 cm) were collected, 4 from each land use/cover category: farmland, forest, plantation and settlement, and analysed for soil pH, cation exchange capacity (CEC), bulk density, moisture content and soil texture, in the laboratory using standard analytical procedures. This data was used to produce spatial distribution maps using ordinary kriging, in ArcGIS Pro. The main terrestrial land use/cover categories comprised of the forest (mangrove, lowland, montane and sub-montane), agroforestry, plantations, grassland, settlement, cropland, shrubby savannah, and bare lava. Bulk density showed the highest values in settlement areas and least values under forest land-use categories. Soil moisture content exhibited a reverse trend compared to that of soil bulk density. Forest soils were the sandiest while soils in plantation agricultural land were the most clayey. The soils were slightly acidic to neutral with soils from agricultural land being more acidic (pH(water) = 5.43). It is discernible from the results that the conversion from forest to other land use/cover classes enhances soil degradation and that soil physico-chemical properties adequately serve as indicators of soil quality in the Mt Cameroon area.

Geostatistical Analysis of Soil Nutrients Based on GIS and Geostatistics in the Typical Plain and Hilly-Ground Area of Zhongxiang, Hubei Province

Techniques of geostatistics are used to perform traditional statistical analysis and spatial structural analysis with ArcGIS, geostatistical software GS+ and statistical software SPSS in order to obtain the knowledge of characteristics of distribution and spatial variability of soil nutrients in different parts of Zhongxiang, Hubei Province. Some skewed values appeared during the analyses. To decrease the influence of those skewed values, domain processing and Box-Cox transformation were used. The results indicated spatial variability of Total N, Avail. P, rapidly-available potassium (R-Avail. K) and effective zinc (Effect. Zn) was strong, that of organic carbon (Org. C), effective molybdenum (Effect. Mo) and effective copper (Effect. Cu) was medium while that of others was weak. Fitted model of Total N, R-Avail. K and Effect. Mo was spherical model, that of Org. C and Effect. Zn was exponential model, while fitted model of Avail. P and Effect. Cu was Gaussian model. Ratio of variability caused by random factors to overall variability was large. What’s more, the ranges of spatial autocorrelation of soil nutrients had much difference. The smallest value was 3600 m in Effect. Zn while the largest was 77970 m in Org. C. Other characteristics were also included. The study is helpful to soil sampling design, to make people realize the influence of Han River to spatial variability of soil nutrients in this area, and to spatial interpolation and mapping.

The application of geostatistics in grain size trend analysis： A case study of eastern Beibu Gulf

There are 71 surface sediment samples collected from the eastern Beibu Gulf. The moment parameters （i.e. mean size, sorting and skewness） were obtained after applying grain size analysis. The geostatistical analysis was then applied to study the spatial autocorrelation for these parameters; while range, a parameter in the semivariogram that meters the scale of spatial autocorrelation, was estimated. The results indicated that the range for sorting coefficient was physically meaningful. The trend vectors calculated from grain size trend analysis model were consistent with the annual ocean circulation patterns and sediment transport rates according to previous studies. Therefore the range derived from the semivariogram of mean size can be used as the characteristic distance in the grain size trend analysis, which may remove the bias caused by the traditional way of basing on experiences or testing methods to get the characteristic distance. Hence the results from geostatistical analysis can also offer useful information for the determination of sediment sampling density in the future field work.

Sediment distribution pattern mapped from the combination of objective analysis and geostatistics in the large shallow Taihu Lake, China

Investigation was made into sediment depth at 723 irregularly scattered measurement points which cover all the regions in Taihu Lake, China. The combination of successive correction scheme and geostatistical method was used to get all the values of recent sediment thickness at the 69×69 grids in the whole lake. The results showed that there is the significant difference in sediment depth between the eastern area and the western region, and most of the sediments are located in the western shore-line and northern regimes but just a little in the center and eastern parts. The notable exception is the patch between the center and Xishan Island where the maximum sediment depth is more than 4.0 m. This sediment distribution pattern is more than likely related to the current circulation pattern induced by the prevailing wind-forcing in Taihu Lake. The numerical simulation of hydrodynamics can strong support the conclusion. Sediment effects on water quality was also studied and the results showed that the concentrations of TP, TN and SS in the western part are obviously larger than those in the eastern regime, which suggested that more nutrients can be released from thicker sediment areas.

Using Multivariate Statistical and Geostatistical Methods to Identify Spatial Variability of Trace Elements in Agricultural Soils in Dongguan City,Guangdong,China

Dongguan （东莞） City, located in the Pearl River Delta, South China, is famous for its rapid industrialization in the past 30 years. A total of 90 topsoil samples have been collected from agricultural fields, including vegetable and orchard soils in the city, and eight heavy metals （As, Cu, Cd, Cr, Hg, Ni, Pb, and Zn） and other items （pH values and organic matter） have been analyzed, to evaluate the influence of anthropic activities on the environmental quality of agricultural soils and to identify the spatial distribution of trace elements and possible sources of trace elements. The elements Hg, Pb, and Cd have accumulated remarkably here, incomparison with the soil background content of elements in Guangdong （广东） Province. Pollution is more serious in the western plain and the central region, which are heavily distributed with industries and rivers. Multivariate and geostatistical methods have been applied to differentiate the influences of natural processes and human activities on the pollution of heavy metals in topsoils in the study area. The results of cluster analysis （CA） and factor analysis （FA） show that Ni, Cr, Cu, Zn, and As are grouped in factor F1, Pb in F2, and Cd and Hg in F3, respectively. The spatial pattern of the three factors may be well demonstrated by geostatistical analysis. It is shown that the first factor could be considered as a natural source controlled by parent rocks. The second factor could be referred to as ＂industrial and traffic pollution sources＂. The source of the third factor is mainly controlled by long-term anthropic activities, as a consequence of agricultural activities, fossil fuel consumption, and atmospheric deposition.

Groundwater quality assessment using multivariate analysis,geostatistical modeling, and water quality index(WQI): a case of study in the Boumerzoug-El Khroub valley of Northeast Algeria

In this study,the analytical data set of 26 groundwater samples from the alluvial aquifer of Boumerzoug-E1 khroub valley has been processed simultaneously with Multivariate analysis,geostatistical modeling,WQI,and geochemical modeling.Cluster analysis identified three main water types based on the major ion contents,where mineralization increased from group 1 to group 3.These groups were confirmed by FA/PCA,which demonstrated that groundwater quality is influenced by geochemical processes(water-rock interaction)and human practice(irrigation).The exponential semivariogram model WQI.Groundwater chemistry has a strong spatial structure for Mg,Na,Cl,and NO3,and a moderate spatial structure for EC,Ca,K,HCO3,and SO4.Water quality maps generated using ordinary Kriging are consistent with the HCA and PCA results.All water groups are supersaturated with respect to carbonate minerals,and dissolution of kaolinite and Ca-smectite is one of the processes responsible for hydrochemical evolution in the area.

Integration of Tracer Test Data to Refine Geostatistical Hydraulic Conductivity Fields Using Sequential Self-Calibration Method

On the basis of local measurements of hydraulic conductivity, geostatistical methods have been found to be useful in heterogeneity characterization of a hydraulic conductivity field on a regional scale. However, the methods are not suited to directly integrate dynamic production data, such as, hydraulic head and solute concentration, into the study of conductivity distribution. These data, which record the flow and transport processes in the medium, are closely related to the spatial distribution of hydraulic conductivity. In this study, a three-dimensional gradient-based inverse method--the sequential self-calibration （SSC） method--is developed to calibrate a hydraulic conductivity field, initially generated by a geostatistical simulation method, conditioned on tracer test results. The SSC method can honor both local hydraulic conductivity measurements and tracer test data. The mismatch between the simulated hydraulic conductivity field and the reference true one, measured by its mean square error （MSE）, is reduced through the SSC conditional study. In comparison with the unconditional results, the SSC conditional study creates the mean breakthrough curve much closer to the reference true curve, and significantly reduces the prediction uncertainty of the solute transport in the observed locations. Further, the reduction of uncertainty is spatially dependent, which indicates that good locations, geological structure, and boundary conditions will affect the efficiency of the SSC study results.

Spatial analysis of carbon storage density of mid-subtropical forests using geostatistics： a case study in Jiangle County, southeast China

The mid-subtropical forest is one of the biggest sections of subtropical forest in China and plays a vital role in mitigating climate change by sequestering carbon.Studies have examined carbon storage density(CSD) distribution in temperate forests. However, our knowledge of CSD in subtropical forests is limited. In this study, Jiangle County was selected as a study case to explore geographic variation in CSD. A spatial heterogeneity analysis by semivariogram revealed that CSD varied at less than the mesoscale(approximately 2000–3000 m). CSD distribution mapped using Kriging regression revealed an increasing trend in CSD from west to east of the study area.Global spatial autocorrelation analysis indicated that CSD was clustered at the village level(at 5% significance).Some areas with local spatial autocorrelation were detected by Anselin Local Moran's I and Getis-Ord G*. A geographically weighted regression model showed different impacts on the different areas for each determinant. Generally, diameter at breast height, tree height, and stand density had positive correlation with CSD in Jiangle County, but varied substantially in magnitude by location.In contrast, coefficients of elevation and slope ranged from negative to positive. Based on these results, we propose certain measures to increase forest carbon storage,including increasing forested area, improving the quality of the current forests, and promoting reasonable forest management decisions and harvesting strategies. The established CSD model emphasizes the important role of midsubtropical forest in carbon sequestration and provides useful information for quantifying mid-subtropical forest carbon storage.

Geostatistical Assessment of the Spatial Distribution of Some Chemical Properties in Calcareous Soils

Spatial patterns of soil fertility parameters and other extrinsic factors need to be identified to develop farming practices that match agricultural inputs with local crop needs. Little is known about the spatial structure of nutrition in Iran. The present study was conducted in a 132-ha field located in central Iran. Soil samples were collected at 0-30 cm depth and were then analyzed for total nitrogen （N）, available phosphorus （P）, available potassium （K）, available copper （Cu）, available zinc （Zn）, available iron （Fe） and available manganese （Mn）. The results showed that the contents of soil organic matter, Cu and Zn in Marvdasht＇s farms were low. The spatial distribution model and spatial dependence level for soil chemical properties varied in the field. N, K, carbonate calcium equivalent （CaCO3） and electrical conductivity （EC） data indicated the existence of moderate spatial dependence. The variograms for other variables revealed stronger spatial structure. The results showed a longer range value for available P （480 m）, followed by total N （429 m）. The value of other chemical properties values showed a shorter range （128 to 174 m）. Clear patchy distribution of N, P, K, Fe, Mn, Cu and Zn were found from their spatial distribution maps. This proved that sampling strategy for estimating variability should be adapted to the different soil chemical properties and field management. Therefore, the spatial variability of soil chemical properties with strong spatial dependence could be readily managed and a site-specific fertilization scheme for precision farming could be easily developed.

Geostatistical Analyst for Deciding Optimal Interpolation Strategies for Delineating Compact Zones

Variability maps of Hydraulic conductivity (K) were generated by using geo statistical analyst extension of ARC GIS for delineating compact zones in a farm. In the initial exploratory spatial data analysis, K data for 0 - 15 and 15 - 30 cm soil layers showed spatial dependence, anisotropy, normality on log transformation and linear trend. Outliers present in both layers were also removed. In the next step, cross validation statistics of different combinations of kriging (Ordinary, simple and universal), data transformations (none and logarithmic) and trends (none and linear) were compared. Combination of no data transformation and linear trend removal was the best choice as it resulted in more accurate and unbiased prediction. It thus, confirmed that for generating prediction maps by kriging, data need not be normal. Ordinary kriging is appropriate when trend is linear. Among various available anisotropic semivariogram models, spherical model for 0 - 15 cm and tetra spherical model for 15 - 30 cm were found to be the best with major and minor ranges between 273 - 410 m and 98 - 213 m. The kriging was superior to other interpolation techniques as the slope of the best fit line of scatter plot of predicted vs. measured data points was more (0.76) in kriging than in inverse distance weighted interpolation (0.61) and global polynomial interpolation (0.56). In the generated prediction maps, areas where K was <12 cm?day–1 were delineated as compact zone. Hence, it can be concluded that geostatistical analyst is a complete package for preprocessing of data and for choosing the optimal interpolation strategies.

A comparative study of geometric and geostatistical methods for qualitative reserve estimation of limestone deposit

Mining projects especially relating to limestone deposits require an accurate knowledge of tonnage and grade,for both short and long-term planning.This is often difficult to establish as detailed exploration operations,which are required to get the accurate description of the deposit,are costly and time consuming.Geologists and mining engineers usually make use of geometric and geostatistical methods,for estimating the tonnage and grade of ore reserves.However,explicit assessments into the differences between these methods have not been reported in literature.To bridge this research gap,a comparative study is carried out to compare the qualitative reserve of Oyo-Iwa limestone deposit located in Nigeria,using geometric and geostatistical methods.The geometric method computes the reserve of the limestone deposit as 74,536,820 t(mean calcite,CaO grade=52.15)and 99,674,793 t(mean calcite,CaO grade=52.32),for the Northern and Southern zones of the deposit,respectively.On the other hand,the geostatistical method calculates the reserve as 81,626,729.65 t(mean calcite,CaO grade=53.36)and 100,098,697.46 t(mean calcite,CaO grade=52.96),for the two zones,respectively.The small relative difference in tonnage estimation between the two methods(i.e.,9.51%and 0.43%),proves that the geometric method is effective for tonnage estimation.In contrast,the relative difference in grade estimation between the two methods(i.e.,2.32%and 1.26%)is not negligible,and could be crucial in maintaining the profitability of the project.The geostatistical method is,therefore,more suitable,reliable and preferable for grade estimation,since it involves the use of spatial modelling and cross-validated interpolation.In addition,the geostatistical method is used to produce quality maps and three-dimensional(3-D)perspective view of the limestone deposit.The quality maps and 3-D view of the limestone deposit reveal the variability of the limestone grade within the deposit,and it is useful for operational management of the limestone raw materials.The qualitative mapping of the limestone deposit is key to effective production scheduling and accurate projection of raw materials for cement production.

Geostatistical Studies and Anomalous Elements Detection, Bardaskan Area, Iran

The aim of this study is geostatistical analysis and detection of anomalous elements in the Bardaskan area (in geological map of Bardaskan on scale 1:100,000 which is provided by the GSI organization). The study area is located in Khorasan province of Iran. Due to the availability of lithogeochemical regular data in the region as well as the importance of exploration of metal minerals in order to simplify and summarize the geochemical map, geostatistical methods were used to identify the mineralization potential of the region. Initially, using single-variable and multivariate statistical methods, anomalous elements were separated. Then, the thresholds (various communities) for the titanium element that was most likely to be anomalous were identified. Using these limits, the discriminant analysis was applied to the elements. Titanium, iron and magnesium elements were identified as the main mineral elements in the region. These elements indicate mineralization in the mafic bed rocks. Finally the map of the concentration of titanium element was mapped across the region with Kriging interpolation method. As a result, two anomalies of the titanium element in the region were identified.

Geostatistical Analysis of Spatial Distribution and Dynamics of Dead Heart of Sugarcane Seedlings Caused by Borer

Dead heart of sugarcane is an important symptom caused by borer attack. In the present study, the spatial distribution and dynamics of dead heart of sugarcane in the field were investigated based on geostatistical analysis, and semivariograms were computed in four separate directions(0°, 45°, 90° and 135°) and fitted with various theoretical models to determine the best fitted one. The Ordinary Kriging was used to interpolate spatial data. The results revealed that the density of dead hearts of sugarcane increased in a single-peak pattern, and the degree of spatial aggregation and random variation both decreased with the increase in the density of dead heart. In addition, dead heart of sugarcane caused by borer exhibited spatial aggregation.With the increase in the density of dead heart, the degree of spatial aggregation decreased, while the correlation increased. Kriging interpolation indicated that the correlation between the spatial patches was weak in early seedling stage, and became strong in middle and late seedling stage.

Geostatistical analysis of variations in soil salinity in a typical irrigation area in Xinjiang, northwest China

Characterizing spatial and temporal variability of soil salinity is tremendously important for a variety of agronomic and environmental concerns in arid irrigation areas. This paper reviews the characteristics and spatial and temporal variations of soil salinization in the Ili River Irrigation Area by applying a geostatistical approach. Results showed that: (1) the soil salinity varied widely, with maximum value of 28.10 g/kg and minimum value of 0.10 g/kg, and was distributed mainly at the surface soil layer. Anions were mainly SO42- and Cl-, while cations were mainly Na+ and Ca2+; (2) the abundance of salinity of the root zone soil layer for different land use types was in the following order: grassland > cropland > forestland. The abundance of salinity of root zone soil layers for different periods was in the following order: March > June > September; (3) the spherical model was the most suitable variogram model to describe the salinity of the 0-3 cm and 3-20 cm soil layers in March and June, and the 3-20 cm soil layer in September, while the exponential model was the most suitable variogram model to describe the salinity of the 0-3 cm soil layer in September. Relatively strong spatial and temporal structure existed for soil salinity due to lower nugget effects; and (4) the maps of kriged soil salinity showed that higher soil salinity was distributed in the central parts of the study area and lower soil salinity was distributed in the marginal parts. Soil salinity tended to increase from the marginal parts to the central parts across the study area. Applying the kriging method is very helpful in detecting the problematic areas and is a good tool for soil resources management. Managing efforts on the appropriate use of soil and water resources in such areas is very important for sustainable agriculture, and more attention should be paid to these areas to prevent future problems.

Application of Multivariate Geostatistics in Environmental Epidemiology: Case Study from Houston, Texas

This study represents an example of investigating the associations between the joint exposure to ozone (O3) and particulate matter of sizes less than or equal to 2.5 micrometers in aerodynamic diameter (PM2.5) and cardiovascular disease (CVD) emergency room (ER) visits and chronic obstructive pulmonary disease (COPD) ER visits using multivariate geostatistics in Houston, Texas, from 2004 to 2009. Analyses showed lack of strong pair-wise association among the predictors of O3, PM2.5, wind speed, relative humidity, and temperature. Whereas CVD and COPD ER visits exhibited a strong positive correlation. Both outcomes drastically increased from 2006 possibly due to immigration from neighboring locations. Parametric testing showed that the data differed significantly between the years. Multivariate multiple regression results on the 2009 data showed that PM2.5, relative humidity, and temperature were significant to both CVD and COPD ER visits. Codispersion coefficients were constant which justified the assumption of intrinsic correlation. That is, our predictors had strong influence on the spatial variability of CVD and COPD ER visits. This multivariate geostatistics approach predicted an increase of 34% in CVD ER visits and 24% increase in COPD ER visits, which calls for more attention from policy makers. The use of multivariate geostatistics analyses enabled us to successfully detect the effects of risk factors on both outcomes.

Application of Multivariate Geostatistics to Investigate the Surface Sediment Distribution of the High-Energy and Shallow Sandy Spiekeroog Shelf at the German Bight, Southern North Sea

Surface sediment data acquired by the grab sampling technique were used in the present study to produce a high-resolution and full coverage surface grain-size mapping. The objective is to test whether the hypothetically natural relationship between the surface sediment distribution and complex bathymetry could be used to improve the quality of surface sediment patches mapping. This is based on our hypothesis that grain-size characteristics of the ridge surface sediments must be intrinsically related to the hydrodynamic condition, i.e. storm-induced currents and the geometry of the seabed morphology. The median grain-size data were obtained from grab samples with inclusive bathymetric point recorded at 713 locations on the high-energy and shallow shelf of the Spiekeroog Barrier Island at the German Bight of the Southern North Sea. The area features two-parallel shoreface-connected ridges which is situated obliquely WNW-SSE oriented and mostly sandy in texture. We made use the median grain-size (d50) as the predictand and the bathymetry as the covariable to produce a high-resolution raster map of median grain-size distribution using the Cokriging interpolation. From the cross-validation of the estimated median grain-size data with the measured ones, it is clear that the gradient of the linear regression line for Cokriging is leaning closer towards the theoretical perfect-correlation line (45°) compared to that for Anisotropy Kriging. The interpolation result with Cokriging shows more realistic estimates on the unknown points of the median grain-size and gave detail to surface sediment patchiness, which spatial scale is more or less in agreement with previous studies. In addition to the moderate correlation obtained from the Pearson correlation (r = 0.44), the cross-variogram shows a more precise nature of their spatial correlation, which is physically meaningful for the interpolation process. The present study partially contributes to the framework of habitat mapping and nature protection that is to fill the gaps in physical information in a high-energetic and shallow coastal shelf.

Delineation of groundwater potential zones in Wadi Saida Watershed of NW-Algeria using remote sensing,geographic information system-based AHP techniques and geostatistical analysis

Sustainable management of groundwater resources has now become an obligation,especially in arid and semi-arid regions given the socio-economic importance of this resource.The optimization in zoning for groundwater exploitation helps in planning and managing groundwater supply works such as boreholes and wells in the catchment.The objective of this study is to use remote sensing and GIS-based Analytical Hierarchy Process(AHP)techniques to evaluate the groundwater potential of Wadi Saida Watershed.Spatial analysis such as geostatistics was also used to validate results and ensure more accuracy.Through the GIS tools and remote sensing technique,earth observation data were converted into thematic layers such as lineament density,geology,drainage density,slope,land use and rainfall,which were combined to delineate groundwater potential zones.Based on their respective impact on groundwater potential,the AHP approach was adopted to assign weights on multi-influencing factors.These results will enable decision-makers to optimize hydrogeological exploration in large-scale catchment areas and map areas.According to the results,the southern part of the Wadi Saida Watershed is characterized as a higher groundwater potential area,where 32%of the total surface area falls in the excellent and good class of groundwater potential.The validation process revealed a 71%agreement between the estimated and actual yield of the existing boreholes in the study area.