Comparison of Point Estimation Techniques in the Spatial Analysis of Radium-226, Radium-228 and Potassium-40 in Soil

Many environmental surveys require the implementation of estimation techniques to determine the spatial distribution of the variable being investigated. Traditional methods of interpolation and estimation, for example, inverse distance squared and triangulation often ignore features of the data set such as anisotropy which may have a significant impact on the quality of the estimates produced. Geostatistical techniques may offer an improved method of estimation by modelling the spatial continuity of the variable using semi-variogram analysis. The theoretical model fitted to the semi-variogram is then used in the assignation of weighting factors to the samples surrounding the location to be estimated. This paper outlines the results of a comparison between three common estimation methods, polygonal, triangulation and inverse distance squared and a geostatistical method, in the estimation of soil radionuclide activities. The geostatistical estimation method known as kriging performed best over a range of parameters used to test the performance of the methods. Kriging exhibited the best correlation between actual and estimated values, the narrowest error distribution and the lowest overall estimation error. Polygonal estimation was best at reproducing the data set distribution. Conditional bias was evident in all the methods, low values being over-estimated and high values being under-estimated.     

Estimation of nested spatial patterns and seasonal variation in the longitudinal distribution of Sicyopterus japonicus in the Datuan Stream, Taiwan by using geostatistical methods

This study attempts to determine the scale-dependent hierarchical spatial variation and longitudinal distributions of Sicyopterus japonicus year round. The distribution of S. japonicus in the Datuan Stream in northern Taiwan was surveyed during the fall and winter 2007, as well as the spring and summer of 2008. The spatial structure of S. japonicus density was modeled using geostatistics. The longitudinal distributions of S. japonicus density were then estimated using kriging and hydrology distance with nested variogram models. Variography results indicate that nested variogram models could reflect the hierarchical structure in the spatial variation of seasonal S. japonicus density, with the small, median, and large ranges representing three nested scales. Models for the four seasons were consistent in that they shared the same shape of variogram models with various ranges and sill values. This model shape consistency implies stationary spatial correlations in the longitudinal fish distribution across the four seasons. The Kriging geostatistical method based on the multiple scales nested variogram models also provided robust estimates of S. japonicus densities at unsampled sections. We conclude that S. japonicus densities exhibit hierarchical patterns and variation in the four seasons along the study stream. Geostatistical methods with a nested variograms and hydrological distance are a highly effective means of delineating the hierarchical structure in longitudinal patterns of S. japonicus density in each season, providing estimates of the S. japonicus density for hierarchically structured spatial distributions and expanding knowledge of S. japonicus beyond the limits imposed by spatial and temporal scales.     

The depositional setting of the Late Quaternary sedimentary fill in southern Bannu basin,Northwest Himalayan fold and thrust belt,Pakistan

Geostatistical variogram and inversion techniques combined with modern visualization tools have made it possible to re-model one-dimensional electrical resistivity data into two-dimensional (2D) models of the near subsurface. The resultant models are capable of extending the original interpretation of the data to depict alluvium layers as individual lithological units within the 2D space. By tuning the variogram parameters used in this approach, it is then possible to visualize individual lithofacies and geomorphological features for these lithologic units. The study re-examines an electrical resistivity dataset collected as part of a groundwater study in an area of the Bannu basin in Pakistan. Additional lithological logs from boreholes throughout the area have been combined with the existing resistivity data for calibration. Tectonic activity during the Himalayan orogeny uplifted and generated significant faulting in the rocks resulting in the formation of a depression which subsequently has been filled with clay-silt and dirty sand facies typical of lacustrine and flood plain environments. Streams arising from adjacent mountains have reworked these facies which have been eroded and replaced by gravel-sand facies along channels. It is concluded that the sediments have been deposited as prograding fan shaped bodies, flood plain, and lacustrine deposits. Clay-silt facies mark the locations of paleo depressions or lake environments, which have changed position over time due to local tectonic activity and sedimentation. The Lakki plain alluvial system has thus formed as a result of local tectonic activity with fluvial erosion and deposition characterized by coarse sediments with high electrical resistivities near the mountain ranges and fine sediments with medium to low electrical resistivities towards the basin center.     

Estimation of spatial distrubition of groundwater level and risky areas of seawater intrusion on the coastal region in Çarşamba Plain,Turkey, using different interpolation methods

Groundwater level plays a significant role in coastal plains. Heavy pumping and excessive use of near-coast groundwater can increase the intrusion of seawater into the aquifers. In the present study, groundwater levels were measured at 59 groundwater wells at different times during pre- and post-irrigation seasons (April and September of the year 2012) in Çar?amba Plain, Turkey. To select the best method, two deterministic interpolation methods (inverse distance weighing (IDW) with the weights of 1, 2, and 3 and radial basis function (RBF) with spline with tension (SPT) and completely regularized spline (CRS)) and two stochastic methods (ordinary kriging (OK) with spherical, exponential, and Gaussian variograms) and cokriging (COK)) were compared and then the best interpolation method was used to evaluate the spatial distribution of groundwater levels in different seasons and seasonal changes. A total of nine different techniques were tested. Also, risky areas of seawater intrusion in coastal area were determined using the best methods for two periods. The performance of these interpolation methods is evaluated by using a validation test method. Statistical indices of correlation (R ²), mean absolute error (MAE), and root-mean-square error (RMSE) were used to select and validate the best methods. Comparisons between predicted and observed values indicated RBF as the optimal method for groundwater level estimation in April and September. When the best method RBF and the worst method IDW were compared, significant differences were observed in the spatial distribution of groundwater. Results of the study also revealed that excessive groundwater withdrawals during the post-irrigation season dropped the groundwater levels up to 2.0 m in some sections. With regard to seawater intrusion, 9,103 ha of land area was determined to be highly risky and risky.     

Kriging and Bilinear Methods for Estimating Spatial Pattern of Atmospheric Pollutants

Two statistical methods to reconstruct the spatial pattern ofenvironmental data are compared: the Kriging and the Bilinear.The comparison is performed by evaluating two differentcharacteristics of the methods: the interpolation and the estimation. The Kriging method is demonstrated to be better thanthe Bilinear regarding all the statistics studied, although thedifferences are not very significant. Especially, the Kriging ismore efficient than the Bilinear in the reconstruction of peakvalues and it does not extrapolate local trends. The methods areapplied to a set of environmental data measured in an urban area.     

Spatial variability of the shallow groundwater level and its chemistry characteristics in the low plain around the Bohai Sea,North China

To characterize the spatial distribution of groundwater level (GWL) and its chemistry characteristics in the low plain around the Bohai Sea, shallow groundwater depth of 130 wells were determined. Water soluble ions composition, total dissolved solid (TDS), electric conductivity (EC), total hardness (TH), total alkalinity (TA), and total salt content (TS) of 128 representative groundwater samples were also measured. Classical statistics, geostatistical method combined with GIS technique were then used to analyze the spatial variability and distribution of GWL and groundwater chemical properties. Results show that GWL, TDS, EC, TH, TA, and TS all presented a lognormal distribution and could be fitted by different semivariogram models (spherical, exponential, and Gaussian). Spatial structure of GWL, TDS, EC, TH, TA, and TS changed obviously. GWL decreased from west inland plain to the east coastal plain, however, TDS, EC, and TS increased from west to east, TH and TA were higher in the middle and coastal plain area. Groundwater chemical type in the coastal plain was SO₄²⁻·Cl⁻—Na⁺ while chemical types in the inland plain were SO₄²⁻·Cl⁻—Ca²⁺·Mg²⁺ and HCO₃⁻—Ca²⁺·Mg²⁺.     

Comparison of stochastic and deterministic methods for mapping groundwater level spatial variability in sparsely monitored basins

In sparsely monitored basins, accurate mapping of the spatial variability of groundwater level requires the interpolation of scattered data. This paper presents a comparison of deterministic interpolation methods, i.e. inverse distance weight (IDW) and minimum curvature (MC), with stochastic methods, i.e. ordinary kriging (OK), universal kriging (UK) and kriging with Delaunay triangulation (DK). The study area is the Mires Basin of Mesara Valley in Crete (Greece). This sparsely sampled basin has limited groundwater resources which are vital for the island’s economy; spatial variations of the groundwater level are important for developing management and monitoring strategies. We evaluate the performance of the interpolation methods with respect to different statistical measures. The Spartan variogram family is applied for the first time to hydrological data and is shown to be optimal with respect to stochastic interpolation of this dataset. The three stochastic methods (OK, DK and UK) perform overall better than the deterministic counterparts (IDW and MC). DK, which is herein for the first time applied to hydrological data, yields the most accurate cross-validation estimate for the lowest value in the dataset. OK and UK lead to smooth isolevel contours, whilst DK and IDW generate more edges. The stochastic methods deliver estimates of prediction uncertainty which becomes highest near the southeastern border of the basin.     

Comparison of Groundwater Level Estimation Using Neuro-fuzzy and Ordinary Kriging

Water level in aquifer plays the main role in groundwater modeling as one of the input data. In practice, due to aspects of time and cost, data monitoring of water levels is conducted at a limited number of sites, and interpolation technique such as kriging is widely used for estimation of this variable in unsampled sites. In this study, the efficiency of the ordinary kriging (OK) and adaptive network-based fuzzy inference system (ANFIS) was investigated in interpolation of groundwater level in an unconfined aquifer in the north of Iran. The results showed that ANFIS model is more efficient in estimating the groundwater level than OK.     

Spatial variability of soil <Superscript>137</Superscript>Cs in the South Caspian region

In a comprehensive program of environmental radioactivity survey in South Caspian region,¹³⁷Cs inventories in soil has been measured at more than 50 sites in the Iranian northern province of Guilan. This has been the first wide-range survey of soil radionuclide inventories in the narrow band sensitive ecosystem of south Caspian shore. Radioactivity measurements were carried out using HPGe gamma-spectrometry system. The activity concentration of ¹³⁷Cs in surface soil exhibits a mean value of 17.6 ± 9.4 Bq kg⁻¹, with a range of 2.3–41.7 Bq kg⁻¹. In many sites, split-level sampling method has been applied down to a depth of 20 cm. There were found generally two profiles. Most profiles exhibit a negative exponential distribution, while others revealed a clear subsurface peak in 5–10-cm layer. Cesium deposition in the study area has been estimated to be in the range of 0.38–2.9 kBq m⁻² with a mean value of 1.7 kBq m⁻². Distribution patterns of ¹³⁷Cs concentration levels and deposition values have been estimated using Kriging interpolation method. Observed hotspots in deposition pattern coincide with areas of higher precipitation.     

An attempt to evaluate the recharge source and extent using hydrogeochemistry and stable isotopes in North Henan Plain,China

A thorough understanding of groundwater recharge source, particularly its rate, is usually a prerequisite for effective water resources management. In this paper, we report the impact of Yellow River water seepage from the North Henan Plain, using both hydrogeochemical and stable isotopic analysis data. Seven Yellow River water samples, 10 groundwater samples from a river-parallel transect, and 36 groundwater samples from four different perpendicular transects to the Yellow River in the western, middle, and eastern plain were collected and analyzed. It inferred that cation exchange of Ca²⁺ and/or Mg²⁺ for Na⁺ occurred in groundwaters because of the dissolution of carbonate rocks. The hydrogeochemical results indicate that western piedmont lateral groundwater and the Yellow River are both important sources of groundwater recharge for the western transect of the North Henan Plain, while the former is a greater recharge source for the middle transect, and the latter is a greater recharge source for the eastern transect. Stable isotope data support Yellow River water incursion into the groundwater. The approximate distance (based on chloride concentration) from the Yellow River to border of the impact zone is17.43–23.40 km in the western plain, 52.46 km in the middle plain, and 49.82 km in the eastern plain.     

Spatiotemporal variation of groundwater quality using integrated multivariate statistical and geostatistical approaches in Amol–Babol Plain,Iran

In recent years, groundwater quality has become a global concern due to its effect on human life and natural ecosystems. To assess the groundwater quality in the Amol–Babol Plain, a total of 308 water samples were collected during wet and dry seasons in 2009. The samples were analysed for their physico-chemical and biological constituents. Multivariate statistical analysis and geostatistical techniques were applied to assess the spatial and temporal variabilities of groundwater quality and to identify the main factors and sources of contamination. Principal component analysis (PCA) revealed that seven factors explained around 75 % of the total variance, which highlighted salinity, hardness and biological pollution as the dominant factors affecting the groundwater quality in the Plain. Two-way analysis of variance (ANOVA) was conducted on the dataset to evaluate the spatio-temporal variation. The results showed that there were no significant temporal variations between the two seasons, which explained the similarity between six component factors in dry and wet seasons based on the PCA results. There are also significant spatial differences (p?>?0.05) of the parameters under study, including salinity, potassium, sulphate and dissolved oxygen in the plain. The least significant difference (LSD) test revealed that groundwater salinity in the eastern region is significantly different to the central and western side of the study area. Finally, multivariate analysis and geostatistical techniques were combined as an effective method for demonstrating the spatial structure of multivariate spatial data. It was concluded that multiple natural processes and anthropogenic activities were the main sources of groundwater salinization, hardness and microbiological contamination of the study area.     

The assessment of spatial distribution of soil salinity risk using neural network

Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km²) results were used to upscale soil salinity to a district area (∼300 km²). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m⁻¹). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70–90% of locations were correctly estimated.     

Temporal and spatial variability in water quality of wetlands in the Minneapolis/St. Paul,MN metropolitan area: Implications for monitoring strategies and designs

Temporal and spatial variability in wetland water-quality variables were examined for twenty-one wetlands in the Minneapolis/St. Paul metropolitan area and eighteen wetlands in adjacent Wright County. Wetland water quality was significantly affected by contact with the sediment (surface water vs. groundwater), season, degree of hydrologic isolation, wetland class, and predominant land-use in the surrounding watershed (p<0.05). Between years, only nitrate and particulate nitrogen concentrations varied significantly in Wright County wetland surface waters. For eight water-quality variables, the power of a paired before-and-after comparison design was greater than the power of a completely randomized design. The reverse was true for four other water-quality variables. The power of statistical tests for different classes of water-quality variables could be ranked according to the predominant factors influencing these: climate factors>edaphic factors>detritivory>land-use factors>biotic-redox or other multiple factors.For two wetlands sampled intensively, soluble reactive phosphate and total dissolved phosphorus were the most spatially variable (c.v.=76–249%), while temperature, color, dissolved organic carbon, and DO were least variable (c.v.=6–43%). Geostatistical analyses demonstrated that the average distance across which water-quality variables were spatially correlated (variogram range) was 61–112% of the mean radius of each wetland. Within the shallower of the two wetlands, nitrogen speciation was explained as a function of dissolved oxygen, while deeper marsh water-quality variables were explained as a function of water depth or distance from the wetland edge. Compositing water-quality samples produced unbiased estimates of individual sample means for all water quality variables examined except for ammonium.     

全国近岸海域水质空间插值算法精度分析

空间插值技术对近海环境数据的分析和表征具有广泛应用价值,但目前针对各类模型适用性和精度比较的研究很少。基于2009年全国近岸海域299个站位的水质监测数据,利用交叉检验法,对3种插值算法13种模型的空间拟合结果进行分析和验证。结果表明,13种模型的模拟值与实测值显著相关(r=0.643~0.750,P0.01,n=299),说明其均适用于近岸海域水质的空间模拟;综合比较模拟结果与实测结果的相关系数、平均误差、平均绝对误差、均方差及偏离程度,排序为IDW(p2)Spline-TensionIDW(p3)IDW(p4)IDW(p1)IDW(p5)IDW(p6)Kriging-GuassianKriging-Spherical,Kriging-CircularKriging-LinearKriging-ExponentialSpline-Regularized,提出IDW(p2)是精度最优的空间插值模型。     

A probabilistic methodology to assess the risk of groundwater quality degradation

An approach to assess the risk of groundwater quality degradation with regard to fixed standards, based on DisjunctiveKriging (DK) is presented. The DK allows one to evaluate the Conditional Probability (CP) of overriding a given threshold of concentration of a pollutant at a given time, and at a generic point in a consideredgroundwater system. The result of such investigation over the considered area can be plotted in form of maps of spatial risk. By repeating this analysis at different times, severalspatial riskmaps will be produced, one for each consideredtime. By means of non-parametric statistics, the temporal trendof the CPs can be evaluated at every point of the considered area. The trend index, assessed by means of a sort of classification of the trend values obtained as described above,can be superimposed on the most recent values of the spatialrisk (i.e.: the most recent values of probability). Consequentlya classification of the risk of groundwater quality degradationresults with which to weigh both the spatial distribution and thetemporal behaviour of the probability to exceed a given standardthreshold. The methodology has been applied to values of nitrateconcentration sampled in the monitoring well network of theModena plain, northern Italy. This area is characterised by intensive agricultural exploitation and hog breeding along withindustrial and civil developments. The influence of agriculture on groundwater results in a high nitrate pollution that limitsits use for potable purposes.     

A new four-step hierarchy method for combined assessment of groundwater quality and pollution

A new four-step hierarchy method was constructed and applied to evaluate the groundwater quality and pollution of the Dagujia River Basin. The assessment index system is divided into four types: field test indices, common inorganic chemical indices, inorganic toxicology indices, and trace organic indices. Background values of common inorganic chemical indices and inorganic toxicology indices were estimated with the cumulative-probability curve method, and the results showed that the background values of Mg²⁺ (51.1 mg L^?1), total hardness (TH) (509.4 mg L^?1), and NO₃ ^? (182.4 mg L^?1) are all higher than the corresponding grade III values of Quality Standard for Groundwater, indicating that they were poor indicators and therefore were not included in the groundwater quality assessment. The quality assessment results displayed that the field test indices were mainly classified as grade II, accounting for 60.87% of wells sampled. The indices of common inorganic chemical and inorganic toxicology were both mostly in the range of grade III, whereas the trace organic indices were predominantly classified as grade I. The variabilities and excess ratios of the indices were also calculated and evaluated. Spatial distributions showed that the groundwater with poor quality indices was mainly located in the northeast of the basin, which was well-connected with seawater intrusion. Additionally, the pollution assessment revealed that groundwater in well 44 was classified as “moderately polluted,” wells 5 and 8 were “lightly polluted,” and other wells were classified as “unpolluted.”     

区域PM2.5时空回归建模与预测

基于区域PM_(2.5)时空建模和预测的需要及PM_(2.5)浓度呈现明显的时空分布趋势的状况,以苏南地区2014年PM_(2.5)日监测数据为实验数据,使用回归克里格对区域PM_(2.5)进行时空建模和估值。利用最小二乘法建立了PM_(2.5)与时空位置的三元二次回归趋势模型,建模点趋势值与实测值间的平均误差接近于0,表明趋势模型拟合效果较好;拟合了样点残差的理论变异函数模型,表明该地区PM_(2.5)的空间和时间相关性范围分别为150 km和4 d;基于该模型,使用时空普通克里格对残差进行时空插值;插值结果与趋势项相加,得到PM_(2.5)回归克里格估值结果;通过对比不考虑趋势的时空普通克里格估值结果,发现考虑时空趋势的时空回归克里格法精度提高了1. 29%。对所提方法进行了创新性分析,并对不足之处进行了讨论。     

Groundwater quality assessment and its correlation with gastroenteritis using GIS: a case study of Rawal Town,Rawalpindi, Pakistan

Majority of the people of Pakistan get drinking water from groundwater source. Nearly 40 % of the total ailments reported in Pakistan are the result of dirty drinking water. Every summer, thousands of patients suffer from acute gastroenteritis in the Rawal Town. Therefore, a study was designed to generate a water quality index map of the Rawal Town and identify the relationship between bacteriological water quality and socio-economic indicators with gastroenteritis in the study area. Water quality and gastroenteritis patient data were collected by surveying the 262 tubewells and the major hospitals in the Rawal Town. The collected spatial data was analyzed by using ArcGIS spatial analyst (Moran’s I spatial autocorrelation) and geostatistical analysis tools (inverse distance weighted, radial basis function, kriging, and cokriging). The water quality index (WQI) for the study area was computed using pH, turbidity, total dissolved solids, calcium, hardness, alkalinity, and chloride values of the 262 tubewells. The results of Moran’s I spatial autocorrelation showed that the groundwater physicochemical parameters were clustered. Among IDW, radial basis function, and kriging and cokriging interpolation techniques, cokriging showed the lowest root mean square error. Cokriging was used to make the spatial distribution maps of water quality parameters. The WQI results showed that more than half of the tubewells in the Rawal Town were providing “poor” to “unfit” drinking water. The Pearson’s coefficient of correlation for gastroenteritis with fecal coliform was found significant (P?P?P?相似文献   

Spatial assessment of water quality parameters in Jhelum city (Pakistan)

In this study, we assess the drinking water quality of Jhelum city. Two hundred and ninety-two drinking water samples were randomly collected in the study area. These samples were chemically analyzed for three key toxic (in excess) elements such as pH, total dissolved solids (TDS), and calcium. Geostatistical techniques such as variogram and kriging were used to investigate the spatial variations of these minerals across the city. The spatial structure for each element was found to be anisotropic, and thus, anisotropic variograms were used. The kriging predictions revealed significant concentrations of the above-stated elements at some locations in the study area. While comparing with the World Health Organization, United States Environmental Protection Agency, and Pakistan Environmental Protection Agency standards, the water samples were found to be unsatisfactory for drinking. We conclude that the drinking water in this region is of poor quality and needs proper treatment to make it palatable.     

山区土壤重金属空间插值性能的改进

山区土壤重金属监测中,密集均匀的布点采样困难大,成本高。根据稀疏非均匀样本数据准确预测山区土壤重金属空间分布,对可视化描述检测元素的分布及趋势具有重要意义。基于云南省楚雄市南部山区表层土壤中重金属锰、钒的采样数据,对集成径向基函数神经网络(IRBFANNs)和传统插值方法:反距离(IDW)、普通克里格(OK)、径向基函数神经网络(RBFANNs),进行了不同等级采样密度下的插值性能比较。结果表明,样本点数量减少时,传统预测方法的插值精度都有所下降,而IRBFANNs算法在样本点较少情况下能够保持最好的插值精确度和稳定性,有效改进了空间插值性能。