The ash contents in coal particles were examined in the paper dependably on particle size and its density. So, the two-dimensional regressive function Z = Z（P, D） was the searched object, where Z is random variable ...The ash contents in coal particles were examined in the paper dependably on particle size and its density. So, the two-dimensional regressive function Z = Z（P, D） was the searched object, where Z is random variable describing ash contents, P---density and D---particle diameter. This dependence was determined based on experimental data concerning the coal of type 31. For this coal, the method of ordinary kriging was applied to calculate the values of random variable Z. This method required the proper selection of so-called variogram function, in which four forms were considered in this paper in purpose to select the best solution. The given results were then evaluated by the mean standard error value and compared with empirical data.展开更多
Application of geostatistical techniques when evaluating mineral deposits could reflect some geological characteristics which help through the stage of planning and production. In the present study<span style="...Application of geostatistical techniques when evaluating mineral deposits could reflect some geological characteristics which help through the stage of planning and production. In the present study<span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> an attempt has been done on two phosphate deposits at Elsebaiya area on both sides of the River Nile namely</span><span style="font-family:Verdana;">:</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> Um Tondoba mine at Elsebaiya East area and Western River Nile mine in Elsebaiya West area. Depending on the available data, statistical analysis illustrated differences in the distribution of P</span><sub><span style="font-size:12px;font-family:Verdana;">2</span></sub><span style="font-family:Verdana;">O</span><sub><span style="font-size:12px;font-family:Verdana;">5</span></sub><span style="font-family:Verdana;"> % and ore thickness within the studied areas. Geostatistics used to start with constructing variograms for P</span><sub><span style="font-size:12px;font-family:Verdana;">2</span></sub><span style="font-family:Verdana;">O</span><sub><span style="font-size:12px;font-family:Verdana;">5</span></sub><span style="font-family:Verdana;"> % and thickness for the two phosphate deposits to be used with ordinary kriging models, also constructing cross variograms between P</span><sub><span style="font-size:12px;font-family:Verdana;">2</span></sub><span style="font-family:Verdana;">O</span><sub><span style="font-size:12px;font-family:Verdana;">5</span></sub><span style="font-family:Verdana;"> % and thickness to be used with cokriging models where the difference in the variogram parameters reflected a specific variation for each deposit horizontally and vertically. The ordinary kriging models and cokriging models illustrated different distribution behavior through both the two kriging techniques.</span></span>展开更多
The primary network of groundwater level observation wells aims at realizing a regional groundwater management policy. It may give a regional picture of groundwater level with emphasis on the natural situation. Observ...The primary network of groundwater level observation wells aims at realizing a regional groundwater management policy. It may give a regional picture of groundwater level with emphasis on the natural situation. Observation data from the primary network can be used to estimate the actual state of groundwater system. Since the cost of the installation and maintenance of a groundwater monitoring network is extremely high, the assessment of effectiveness of the network becomes very necessary. Groundwater level monitoring networks are the examples of discontinuous sampling on variables presenting spatial continuity and highly skewed frequency distributions. Anywhere in the aquifer, ordinary kriging provides estimates of the variable sampled and a standard error of the estimate. In this article, the average Kriging standard deviation was used as a criterion for the determination of network density,and the GIS-based approach was analysized. A case study of groundwater level network simulation in the Chaiwopu Basin, Xinjiang Uygur Autonomous Region, China, was presented. In the case study, the initial phreatic water observation wells were 18, a comparison of the three variogram parameters of the three defferent variogram models shows that the Gaussian model is the best. Finally, a network with 55 wells was constructed.展开更多
A geostatistical study was conducted with the objective of developing a better understanding of the sediments deposited in the tailings dam of an iron mine located in Brazil.The samples,derived from two drilling campa...A geostatistical study was conducted with the objective of developing a better understanding of the sediments deposited in the tailings dam of an iron mine located in Brazil.The samples,derived from two drilling campaigns conducted in 2001 and 2010,were statistically evaluated and validated for the construction of both a 3D geological model and an estimated model.The geological body modeling process was performed using an implicit method,which was based on the interpretation and adjustments of vertical sections and considered the positions of the samples and the grades of the chemical components of interest.In addition,the primitive topography was also considered to determine the base and limits of the deposit,as well as the current topography.The ordinary kriging(OK)method was chosen to estimate the grades of the chemical components and the retained/passing percentages of the particle size fractions described in the samples.The kriging model was validated through two analyses:mean comparison and drift analyses.The total tonnage of the estimated model was 287.14 Mt,with an average Fe grade of 63.89%.展开更多
Purpose: There is a significant rise in mortality rates from breast and cervical cancers in Low- and Middle-Income Countries. In Ghana, approximately 4482 women are diagnosed with these diseases at advanced stages. Un...Purpose: There is a significant rise in mortality rates from breast and cervical cancers in Low- and Middle-Income Countries. In Ghana, approximately 4482 women are diagnosed with these diseases at advanced stages. Unfortunately, the early detection rate for these cancers is low compared to other women’s health services. This situation underscores the need to identify the locations of reproductive-age women who have not been screened for these cancers, to implement targeted public health interventions. This study aims to pinpoint these women’s locations for tailored interventions. Method: Bivariate analysis assessed the relationship between the independent and outcome variables. Hot spot analysis and Kriging Ordinary interpolation were employed to pinpoint the locations of these women. Results: Breast cancer examination and cervical cancer test rates were low, with a strong association between the two screening services. Several significant variables were identified: place of residence (p Conclusion: Low participation in these screening services was related to women’s age and the outreach efforts of fieldworkers. Breast and cervical cancer screenings are interconnected and could be combined to improve attendance rates. The Community-based Health Planning and Services (CHPS) implementation strategy could be cost-effective for screening women through targeted interventions, especially in identified clusters.展开更多
[Objective] The aim was to explore evaluated precision on quality of soil environment polluted with zinc in agricultural production areas and to provide references for verification of production area.[Method] In Shula...[Objective] The aim was to explore evaluated precision on quality of soil environment polluted with zinc in agricultural production areas and to provide references for verification of production area.[Method] In Shulan City in Jilin Province,soils were sampled and analyzed in a laboratory using single-factor pollution index and GIS based spatial interpolation.The quality of environment polluted with zinc was assessed and related methods were compared according to Environment Quality Standard of Green Food Production Area.[Result] Spatial interpolation of zinc in soils based on GIS proved more precise than traditional methods;cokriging method with co-factors was higher in precision than common cokriging;cokriging method with zinc and organic matter was higher in precision than cokriging with zinc alone.[Conclusion] Quality assessment on environment polluted with zinc based on GIS interpolation is more scientific and reasonable than traditional methods.展开更多
In global change research, changes of soil organic carbon (SOC) reservoirs intropical and subtropical regions are still unknown. The temporal-spatial variability of SOC stockswas determined in a basin of over 579 km^2...In global change research, changes of soil organic carbon (SOC) reservoirs intropical and subtropical regions are still unknown. The temporal-spatial variability of SOC stockswas determined in a basin of over 579 km^2 in subtropical China from 1981to 2002. ArcGIS8.l softwarewas utilized for spatial analysis of semivariance, ordinary kriging (OK), and probability kriging(PK). Grid and hierarchical approaches were employed for the sampling scenario in 2002 with 106Global Position System (GPS) established spots sampled. Bulk topsoil samples (0—30 cm) werecollected at three random sites on each spot. The SOC content for 1981 came from the SOC map of theSecond National Soil Survey. Geostatistical results of the nugget to sill ratio (0.215-0.640)in therehabilitating ecosystem indicated a moderate spatial dependence for SOC on this large scale. Therange of SOC changed from 2.04 km in 1981 to 7.15 km in 2002. The mean topsoil SOC increased by 4.6%from 10.63 g kg^(-1) (1981) to 11.12 g kg^(-1)(2002). However, during this 21-year period 25.2% ofthe total basin area experienced a decrease in SOC. Also, the probability kriging results showedthat the geometric mean probabilities of SOC <= 6.0 g kg^(-1), <= 11.0 g kg^(-1) and > 15.0 gkg^(-1) were 0.188, 0.534 and 0.378, respectively in 2002, comparing to 0.234, 0.416 and 0.234 inthat order in 1981, respectively. The SOC storage in the topsoil increased by 17.0% during this timewith the main increase occurring in forests and cultivated land,which amounted to 82.5% and 17.0%of the total increase, respectively.展开更多
Soil organic matter (SOM) content is one of the main factors to be considered in the evaluation of soil health and fertility. As timing, human and monetary resources often limit the amount of available data, geostatis...Soil organic matter (SOM) content is one of the main factors to be considered in the evaluation of soil health and fertility. As timing, human and monetary resources often limit the amount of available data, geostatistical techniques provide a valid scientific approach to cope with spatial variability, to interpolate existing data and to predict values at unsampled locations for accurate SOM status survey. Using geostatistical and geographic information system (GIS) approaches, the spatial variability of some physical and chemical soil parameters was investigated under Mediterranean climatic condition in the Abruzzo region of central Italy, where soil erosion processes accelerated by human induced factors are the main causes of soil degradation associated with low SOM content. Experimental semivariograms were established to determine the spatial dependence of the soil variables under investigation. The results of 250 soil sampling point data were interpolated by means of ordinary kriging coupled with a GIS to produce contour maps distribution of soil texture, SOM content related to texture, and C/N ratio. The resulting spatial interpolation of the dataset highlighted a low content of SOM in relation with soil texture in most of the surveyed area (87%) and an optimal C/N ratio for only half of the investigated surface area. Spatial location of degraded area and the assessment of its magnitude can provide decision makers with an accurate support to design appropriate soil conservation strategies and then facilitate a regional planning of agri-environmental measures in the framework of the European Common Agricultural Policy.展开更多
Climate research relies heavily on good quality instrumental data; for modeling efforts gridded data are needed. So far, relatively little effort has been made to create gridded climate data for China. This is especia...Climate research relies heavily on good quality instrumental data; for modeling efforts gridded data are needed. So far, relatively little effort has been made to create gridded climate data for China. This is especially true for high-resolution daily data. This work, focuses on identifying an accurate method to produce gridded daily precipitation in China based on the observed data at 753 stations for the period 1951-2005. Five interpolation methods, including ordinary nearest neighbor, local polynomial, radial basis function, inverse distance weighting, and ordinary kriging, have been used and compared. Cross-validation shows that the ordinary kriging based on seasonal semi-variograms gives the best performance, closely followed by the inverse distance weighting with a power of 2. Finally the ordinary kriging is chosen to interpolate the station data to a 18 km× 18 km grid system covering the whole country. Precipitation for each 0.5°×0.5° latitude-longitude block is then obtained by averaging the values at the grid nodes within the block. Owing to the higher station density in the eastern part of the country, the interpolation errors are much smaller than those in the west （west of 100°E）. Excluding 145 stations in the western region, the daily, monthly, and annual relative mean absolute errors of the interpolation for the remaining 608 stations are 74%, 29%, and 16%, respectively. The interpolated daily precipitation has been made available on the internet for the scientific community.展开更多
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 geo...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.展开更多
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 operation...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.展开更多
Southern Bangladesh＇s irrigation and drinking water is threatened by saline intrusion. This study aimed to establish an irrigation water quality index （IWQI） using a geostatistical model and multivariate indices in...Southern Bangladesh＇s irrigation and drinking water is threatened by saline intrusion. This study aimed to establish an irrigation water quality index （IWQI） using a geostatistical model and multivariate indices in Gopalganj district, south-central Bangladesh. Groundwater samples were taken randomly （different depths） in two seasons （wet-monsoon and dry-monsoon）. Hydrochemical analysis revealed groundwater in this area was neutral to slightly alkaline and dominating cations were Na^＋, Mg^2＋, and Ca^2＋ along with major anions Cl^- and HCO3^-. Principal component analysis and Gibbs plot helped explain possible geochemical processes in the aquifer. The irrigation water evaluation indices showed： electrical conductivity （EC） 〉750 μS/cm, moderate to extreme saline; sodium adsorption ratio （SAR）, excellent to doubtful; total hardness （TH）, moderate to very hard; residual sodium bicarbonate, safe to marginal; Kelly＇s ratio 〉1; soluble sodium percentage （SSP）, fair to poor; magnesium adsorption ratio, harmful for soil; and IWQI, moderate to suitable. In addition, the best fitted semivariogram for IWQI, EC, SAR, SSP, and TH confirmed that most parameters had strong spatial dependence and others had moderate to weak spatial dependence. This variation might be due to the different origin/sources of major contributing ions along with the influence of variable river flow and small anthropogenic contributions. Furthermore, the spatial distribution maps for IWQI, EC, SSP, and TH during both seasons confirmed the influence of salinity from the sea; low-flow in the major river system was the driving factor of overall groundwater quality in the study area. These findings may contribute to management of irrigation and/or drinking water in regions with similar groundwater problems.展开更多
Integrating land use type and other geographic information within spatial interpolation has been proposed as a solution to improve the performance and accuracy of soil nutrient mapping at the regional scale. This stud...Integrating land use type and other geographic information within spatial interpolation has been proposed as a solution to improve the performance and accuracy of soil nutrient mapping at the regional scale. This study developed a non-algorithm approach, i.e., applying inverse distance weighting （IDW） and ordinary kriging （OK）, to individual land use types rather than to the whole watershed, to determine if this improved the performance in mapping soil total C （TC）, total N （TN）, and total P （TP） in a 200-km2 urbanizing watershed in Southeast China. Four land use types were identified by visual interpretation as forest land, agricultural land, green land, and urban land. One hundred and fifty soil samples （0-10 cm） were taken according to land use type and patch size. Results showed that the non-algorithm approach, interpolation based on individual land use types, substantially improved the performance of IDW and OK for mapping TC, TN, and TP in the watershed. Root mean square errors were reduced by 3.9% for TC, 10.770 for TN, and 25.9% for TP by the application of IDW, while the improvements by OK were slightly lower as 0.9% for TC, 7.7% for TN, and 18.1% for TP. Interpolations based on individual land use types visually improved depiction of spatial patterns for TC, TN, and TP in the watershed relative to interpolations by the whole watershed. Substantial improvements might be expected with denser sampling points. We suggest that this non-algorithm approach might provide an alternative to algorithm-based approaches to depict watershed-scale nutrient patterns.展开更多
An attempt to estimate the reserves in the High Phosphorous stockpile （HP） at the Choghart Iron mine of Iran was carded out using geostatistical modeling. Grade and tonnage estimates of ore stockpiles can help conve...An attempt to estimate the reserves in the High Phosphorous stockpile （HP） at the Choghart Iron mine of Iran was carded out using geostatistical modeling. Grade and tonnage estimates of ore stockpiles can help convert them into a valuable ore reserve. This is valuable in consideration of increasing metal demand, and the depletion of in situ ore reserves, around the world. Estimation of reserves in stockpiles is difficult partly because of geological and grade discontinuities created during the dumping of the ore piles. Data input for the HP stockpile at Choghart was performed based upon pre-existing information gathered during extraction from the various mining benches. After establishing the input data files the reserve estimates were found using geostatistical methods aided by the international mining software SURPAC. The stockpile was divided in to three domains and the reserves in each domain were estimated separately. A grade block model was used to compute the reserve. Fe% and P% were estimated using the Ordinary Kriging method. The results showed that the total tonnage of the HP stockpile is 4.5 million tons with an average zrade of 55% Fe and 1.03% P.展开更多
To consider the complex soil-structure interaction in a pile-slope system,it is necessary to analyze the performance of pile-slope systems based on a three-dimensional(3D)numerical model.Reliability analysis of a pile...To consider the complex soil-structure interaction in a pile-slope system,it is necessary to analyze the performance of pile-slope systems based on a three-dimensional(3D)numerical model.Reliability analysis of a pile-slope system based on 3D numerical modeling is very challenging because it is computationally expensive and the performance function of the pile failure mode is only defined in the safe domain of soil stability.In this paper,an efficient hybrid response surface method is suggested to study the system reliability of pile-reinforced slopes,where the support vector machine and the Kriging model are used to approximate performance functions of soil failure and pile failure,respectively.The versatility of the suggested method is illustrated in detail with an example.For the example examined in this paper,it is found that the pile failure can significantly contribute to system failure,and the reinforcement ratio can effectively reduce the probability of pile failure.There exists a critical reinforcement ratio beyond which the system failure probability is not sensitive to the reinforcement ratio.The pile spacing affects both the probabilities of soil failure and pile failure of the pile-reinforced slope.There exists an optimal location and an optimal length for the stabilizing piles.展开更多
[Objective] The aim was to study the spatial information of temperature and precipitation data in Hengduan mountains. [Method] Considering GIS spatial interpolation and numerical statistics theory, spatial prediction ...[Objective] The aim was to study the spatial information of temperature and precipitation data in Hengduan mountains. [Method] Considering GIS spatial interpolation and numerical statistics theory, spatial prediction were carried out to the ten years average temperature and precipitation flux observation data in 109 sparse meteorological stations in Hengduan Mountains. Based on the spatial range of geographic position of Hengduan Mountains, and 1∶1 000 000 scale DEM as data sources, and using trend surface simulation and residual ordinary Kriging interpolation correction method, the spatial continuous surface for annual average temperature and precipitation were studied. [Result] It was scientific and reasonable to use certain unevenly distributed sparse climate observation station value, and by dint of trend simulation and residue interpolation method to get climate consecutive spatial result. This method can not only accurate the temperature and precipitation spatial distributions to grid point, but also can reflect macro and micro geography factors and topographic influence factor of variation. Furthermore, it can be predicted error term trend surface reasonable spatial distribution. Simulation results were basically in accordance with the objective law, and can be used for the region climate data spatial informatization simulation. [Conclusion] The study provided scientific spatial basic data for the further study of ecological and vegetation in Hengduan Mountains.展开更多
Among spatial interpolation techniques,geostatistics is generally preferred because it takes into account the spatial correlation between neighbouring observations in order to predict attribute values at unsampled loc...Among spatial interpolation techniques,geostatistics is generally preferred because it takes into account the spatial correlation between neighbouring observations in order to predict attribute values at unsampled locations.A doline of approximately 15 000 m 2 at 1 900 m above sea level (North Italy) was selected as the study area to estimate a digital elevation model (DEM) using geostatistics,to provide a realistic distribution of the errors and to demonstrate whether using widely available secondary data provided more accurate estimates of soil pH than those obtained by univariate kriging.Elevation was measured at 467 randomly distributed points that were converted into a regular DEM using ordinary kriging.Further,110 pits were located using spatial simulated annealing (SSA) method.The interpolation techniques were multi-linear regression analysis (MLR),ordinary kriging (OK),regression kriging (RK),kriging with external drift (KED) and multi-collocated ordinary cokriging (CKmc).A cross-validation test was used to assess the prediction performances of the different algorithms and then evaluate which methods performed best.RK and KED yielded better results than the more complex CKmc and OK.The choice of the most appropriate interpolation method accounting for redundant auxiliary information was strongly conditioned by site specific situations.展开更多
This study investigates the spatial variability of soil organic matter(SOM),soil organic carbon(SOC)and pH in the upper 20-cm layer and 20-40 cm layer in Moso bamboo(Phyllostachys pubescens Pradelle)forests using a ge...This study investigates the spatial variability of soil organic matter(SOM),soil organic carbon(SOC)and pH in the upper 20-cm layer and 20-40 cm layer in Moso bamboo(Phyllostachys pubescens Pradelle)forests using a geostatistics model.Interpolation maps of SOM,SOC,and pH were developed using ordinary kriging(OK)and inverse distance weighted(IDW)methods.The pH,SOC,and SOM of the two soil layers ranged from 4.6 to 4.7,from 1.5 to 2.7 g kg^(-1)and from 20.3 to 22.4 g kg^(-1),respectively.The coefficient of variation for SOM and SOC was 29.9-43.3%while a weak variability was found for pH.Gaussian and exponential models performed well in describing the spatial variability of SOC contents with R^(2)varying from 0.95 to 0.90.The nugget/sill values of pH are less than 25%,which indicates a strong spatial correlation,while the nugget/sill values of SOC and SOM fall under moderate spatial correlation.Interpolation using ordinary kriging and inverse distance weighted methods revealed that the spatial distribution of SOM,SOC,and pH was inconsistent due to external and internal factors across the plots.Regarding the cross-validation results,the ordinary kriging method performed better than inverse distance weighted method for selected soil properties.This study suggests that the spatial variability of soil chemical properties revealed by geostatistics modeling will help decision-makers improve the management of soil properties.展开更多
Faced with the scarcity of surface water accentuated by climate change, particularly in many arid and semi-arid countries, the quality of groundwater used for irrigation is a concern to agronomists and hydrogeologists...Faced with the scarcity of surface water accentuated by climate change, particularly in many arid and semi-arid countries, the quality of groundwater used for irrigation is a concern to agronomists and hydrogeologists. When </span><span style="font-family:Verdana;">these waters are of deep origin, they may have high mineralization and</span><span style="font-family:Verdana;"> chemical compositions unsuitable for irrigation;in particular, they may alter soils and crops. It is therefore important to optimize the spatial estimation of the salinity of these waters and contribute to better knowledge of their quality, through an adapted and robust statistical and geostatistical approach. In the case of north-eastern Algeria, the objective of this study is to characterize the quality of deep waters and to test two interpolation methods (Inverse distance weight and ordinary Kriging) of their electrical conductivity (EC) as an indicator of their salinity and of the risk of damaging irrigated soils. 51 ground</span><span style="font-family:Verdana;">water samples were taken in this region where there are many thermal </span><span style="font-family:Verdana;">springs, the water of which is used for irrigation and often is highly mineralized (EC between 0.6 and 26.6 dS/m). The geology is composed of karstic rocks crossed by large faults that allow deep water to rise. Based on major elements contents, analysis of the hydrochemical facies of these waters shows that the main facies are hyperchlorinated sodium (38%) and sulfated calcium (32%). The RSC (Residual Sodium Carbonate) and SAR (Irrigation water salt) indexes were used to assess the water quality. The results indicate that the majority of the sampled</span><span style="color:red;"> </span><span style="font-family:Verdana;">groundwater present a risk for soils irrigated with these waters (almost 1/3 presents a strong risk). The risk for the soils seems to be explained by the positive value of the residual alkalinity, and the high risks of sodization and alkalinization. The geostatistical analysis reveals strong heterogeneity in electrical conductivity (salinity). The maps based on this analysis allow the identification of risk areas. The comparison of Inverse distance weight and ordinary Kriging methods indicates similar results being obtained through both methods. However, ordinary kriging appears to be more accur</span><span style="font-family:Verdana;">ate, less biased, and seemingly better represents the organization of the </span><span style="font-family:Verdana;">groundw</span><span style="font-family:Verdana;">ater resources, as NE-SW alignments are visible. With the proposed ap</span><span style="font-family:Verdana;">proach, it is possible to calculate the surface areas of the different salinity </span><span style="font-family:Verdana;">thresholds and then optimize the use of deep groundwater for irrigation.展开更多
A general regression neural network model,combined with an interative algorithm(GRNNI)using sparsely distributed samples and auxiliary environmental variables was proposed to predict both spatial distribution and vari...A general regression neural network model,combined with an interative algorithm(GRNNI)using sparsely distributed samples and auxiliary environmental variables was proposed to predict both spatial distribution and variability of soil organic matter(SOM)in a bamboo forest.The auxiliary environmental variables were:elevation,slope,mean annual temperature,mean annual precipitation,and normalized difference vegetation index.The prediction accuracy of this model was assessed via three accuracy indices,mean error(ME),mean absolute error(MAE),and root mean squared error(RMSE)for validation in sampling sites.Both the prediction accuracy and reliability of this model were compared to those of regression kriging(RK)and ordinary kriging(OK).The results show that the prediction accuracy of the GRNNI model was higher than that of both RK and OK.The three accuracy indices(ME,MAE,and RMSE)of the GRNNI model were lower than those of RK and OK.Relative improvements of RMSE of the GRNNI model compared with RK and OK were 13.6%and 17.5%,respectively.In addition,a more realistic spatial pattern of SOM was produced by the model because the GRNNI model was more suitable than multiple linear regression to capture the nonlinear relationship between SOM and the auxiliary environmental variables.Therefore,the GRNNI model can improve both prediction accuracy and reliability for determining spatial distribution and variability of SOM.展开更多
文摘The ash contents in coal particles were examined in the paper dependably on particle size and its density. So, the two-dimensional regressive function Z = Z（P, D） was the searched object, where Z is random variable describing ash contents, P---density and D---particle diameter. This dependence was determined based on experimental data concerning the coal of type 31. For this coal, the method of ordinary kriging was applied to calculate the values of random variable Z. This method required the proper selection of so-called variogram function, in which four forms were considered in this paper in purpose to select the best solution. The given results were then evaluated by the mean standard error value and compared with empirical data.
文摘Application of geostatistical techniques when evaluating mineral deposits could reflect some geological characteristics which help through the stage of planning and production. In the present study<span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> an attempt has been done on two phosphate deposits at Elsebaiya area on both sides of the River Nile namely</span><span style="font-family:Verdana;">:</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> Um Tondoba mine at Elsebaiya East area and Western River Nile mine in Elsebaiya West area. Depending on the available data, statistical analysis illustrated differences in the distribution of P</span><sub><span style="font-size:12px;font-family:Verdana;">2</span></sub><span style="font-family:Verdana;">O</span><sub><span style="font-size:12px;font-family:Verdana;">5</span></sub><span style="font-family:Verdana;"> % and ore thickness within the studied areas. Geostatistics used to start with constructing variograms for P</span><sub><span style="font-size:12px;font-family:Verdana;">2</span></sub><span style="font-family:Verdana;">O</span><sub><span style="font-size:12px;font-family:Verdana;">5</span></sub><span style="font-family:Verdana;"> % and thickness for the two phosphate deposits to be used with ordinary kriging models, also constructing cross variograms between P</span><sub><span style="font-size:12px;font-family:Verdana;">2</span></sub><span style="font-family:Verdana;">O</span><sub><span style="font-size:12px;font-family:Verdana;">5</span></sub><span style="font-family:Verdana;"> % and thickness to be used with cokriging models where the difference in the variogram parameters reflected a specific variation for each deposit horizontally and vertically. The ordinary kriging models and cokriging models illustrated different distribution behavior through both the two kriging techniques.</span></span>
基金the National Natural Science Foundation of China (Grant Nos.50579040 and 50570941)
文摘The primary network of groundwater level observation wells aims at realizing a regional groundwater management policy. It may give a regional picture of groundwater level with emphasis on the natural situation. Observation data from the primary network can be used to estimate the actual state of groundwater system. Since the cost of the installation and maintenance of a groundwater monitoring network is extremely high, the assessment of effectiveness of the network becomes very necessary. Groundwater level monitoring networks are the examples of discontinuous sampling on variables presenting spatial continuity and highly skewed frequency distributions. Anywhere in the aquifer, ordinary kriging provides estimates of the variable sampled and a standard error of the estimate. In this article, the average Kriging standard deviation was used as a criterion for the determination of network density,and the GIS-based approach was analysized. A case study of groundwater level network simulation in the Chaiwopu Basin, Xinjiang Uygur Autonomous Region, China, was presented. In the case study, the initial phreatic water observation wells were 18, a comparison of the three variogram parameters of the three defferent variogram models shows that the Gaussian model is the best. Finally, a network with 55 wells was constructed.
文摘A geostatistical study was conducted with the objective of developing a better understanding of the sediments deposited in the tailings dam of an iron mine located in Brazil.The samples,derived from two drilling campaigns conducted in 2001 and 2010,were statistically evaluated and validated for the construction of both a 3D geological model and an estimated model.The geological body modeling process was performed using an implicit method,which was based on the interpretation and adjustments of vertical sections and considered the positions of the samples and the grades of the chemical components of interest.In addition,the primitive topography was also considered to determine the base and limits of the deposit,as well as the current topography.The ordinary kriging(OK)method was chosen to estimate the grades of the chemical components and the retained/passing percentages of the particle size fractions described in the samples.The kriging model was validated through two analyses:mean comparison and drift analyses.The total tonnage of the estimated model was 287.14 Mt,with an average Fe grade of 63.89%.
文摘Purpose: There is a significant rise in mortality rates from breast and cervical cancers in Low- and Middle-Income Countries. In Ghana, approximately 4482 women are diagnosed with these diseases at advanced stages. Unfortunately, the early detection rate for these cancers is low compared to other women’s health services. This situation underscores the need to identify the locations of reproductive-age women who have not been screened for these cancers, to implement targeted public health interventions. This study aims to pinpoint these women’s locations for tailored interventions. Method: Bivariate analysis assessed the relationship between the independent and outcome variables. Hot spot analysis and Kriging Ordinary interpolation were employed to pinpoint the locations of these women. Results: Breast cancer examination and cervical cancer test rates were low, with a strong association between the two screening services. Several significant variables were identified: place of residence (p Conclusion: Low participation in these screening services was related to women’s age and the outreach efforts of fieldworkers. Breast and cervical cancer screenings are interconnected and could be combined to improve attendance rates. The Community-based Health Planning and Services (CHPS) implementation strategy could be cost-effective for screening women through targeted interventions, especially in identified clusters.
基金Supported by National 973 Program(2010CB951500)National 863 Program(2006AA-120103)~~
文摘[Objective] The aim was to explore evaluated precision on quality of soil environment polluted with zinc in agricultural production areas and to provide references for verification of production area.[Method] In Shulan City in Jilin Province,soils were sampled and analyzed in a laboratory using single-factor pollution index and GIS based spatial interpolation.The quality of environment polluted with zinc was assessed and related methods were compared according to Environment Quality Standard of Green Food Production Area.[Result] Spatial interpolation of zinc in soils based on GIS proved more precise than traditional methods;cokriging method with co-factors was higher in precision than common cokriging;cokriging method with zinc and organic matter was higher in precision than cokriging with zinc alone.[Conclusion] Quality assessment on environment polluted with zinc based on GIS interpolation is more scientific and reasonable than traditional methods.
基金Project supported by the National Key Basic Research Support Foundation of China (No. G1999011801) the Knowledge Innovation Program of Chinese Acacemy of Sciences (Nos. KZCX2-413 and ISSASIP0110).
文摘In global change research, changes of soil organic carbon (SOC) reservoirs intropical and subtropical regions are still unknown. The temporal-spatial variability of SOC stockswas determined in a basin of over 579 km^2 in subtropical China from 1981to 2002. ArcGIS8.l softwarewas utilized for spatial analysis of semivariance, ordinary kriging (OK), and probability kriging(PK). Grid and hierarchical approaches were employed for the sampling scenario in 2002 with 106Global Position System (GPS) established spots sampled. Bulk topsoil samples (0—30 cm) werecollected at three random sites on each spot. The SOC content for 1981 came from the SOC map of theSecond National Soil Survey. Geostatistical results of the nugget to sill ratio (0.215-0.640)in therehabilitating ecosystem indicated a moderate spatial dependence for SOC on this large scale. Therange of SOC changed from 2.04 km in 1981 to 7.15 km in 2002. The mean topsoil SOC increased by 4.6%from 10.63 g kg^(-1) (1981) to 11.12 g kg^(-1)(2002). However, during this 21-year period 25.2% ofthe total basin area experienced a decrease in SOC. Also, the probability kriging results showedthat the geometric mean probabilities of SOC <= 6.0 g kg^(-1), <= 11.0 g kg^(-1) and > 15.0 gkg^(-1) were 0.188, 0.534 and 0.378, respectively in 2002, comparing to 0.234, 0.416 and 0.234 inthat order in 1981, respectively. The SOC storage in the topsoil increased by 17.0% during this timewith the main increase occurring in forests and cultivated land,which amounted to 82.5% and 17.0%of the total increase, respectively.
基金Supported by the Italian Ministry of Agricultural, Food and Forestry Policies (No. DM 19366)
文摘Soil organic matter (SOM) content is one of the main factors to be considered in the evaluation of soil health and fertility. As timing, human and monetary resources often limit the amount of available data, geostatistical techniques provide a valid scientific approach to cope with spatial variability, to interpolate existing data and to predict values at unsampled locations for accurate SOM status survey. Using geostatistical and geographic information system (GIS) approaches, the spatial variability of some physical and chemical soil parameters was investigated under Mediterranean climatic condition in the Abruzzo region of central Italy, where soil erosion processes accelerated by human induced factors are the main causes of soil degradation associated with low SOM content. Experimental semivariograms were established to determine the spatial dependence of the soil variables under investigation. The results of 250 soil sampling point data were interpolated by means of ordinary kriging coupled with a GIS to produce contour maps distribution of soil texture, SOM content related to texture, and C/N ratio. The resulting spatial interpolation of the dataset highlighted a low content of SOM in relation with soil texture in most of the surveyed area (87%) and an optimal C/N ratio for only half of the investigated surface area. Spatial location of degraded area and the assessment of its magnitude can provide decision makers with an accurate support to design appropriate soil conservation strategies and then facilitate a regional planning of agri-environmental measures in the framework of the European Common Agricultural Policy.
基金supported by the Swedish Foundation for International Cooperation in Research and High Education through a grant to D.L.Chen.C.-H.Ho is supported by CATER 2006-4204
文摘Climate research relies heavily on good quality instrumental data; for modeling efforts gridded data are needed. So far, relatively little effort has been made to create gridded climate data for China. This is especially true for high-resolution daily data. This work, focuses on identifying an accurate method to produce gridded daily precipitation in China based on the observed data at 753 stations for the period 1951-2005. Five interpolation methods, including ordinary nearest neighbor, local polynomial, radial basis function, inverse distance weighting, and ordinary kriging, have been used and compared. Cross-validation shows that the ordinary kriging based on seasonal semi-variograms gives the best performance, closely followed by the inverse distance weighting with a power of 2. Finally the ordinary kriging is chosen to interpolate the station data to a 18 km× 18 km grid system covering the whole country. Precipitation for each 0.5°×0.5° latitude-longitude block is then obtained by averaging the values at the grid nodes within the block. Owing to the higher station density in the eastern part of the country, the interpolation errors are much smaller than those in the west （west of 100°E）. Excluding 145 stations in the western region, the daily, monthly, and annual relative mean absolute errors of the interpolation for the remaining 608 stations are 74%, 29%, and 16%, respectively. The interpolated daily precipitation has been made available on the internet for the scientific community.
文摘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.
文摘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.
基金supported by the project entitled ‘‘Establishment of monitoring network and mathematical model study to assess salinity intrusion in groundwater in the coastal area of Bangladesh due to climate change’’ implemented by Bangladesh Water Development Boardsponsored by Bangladesh Climate Change Trust Fund, Ministry of Environment and Forest
文摘Southern Bangladesh＇s irrigation and drinking water is threatened by saline intrusion. This study aimed to establish an irrigation water quality index （IWQI） using a geostatistical model and multivariate indices in Gopalganj district, south-central Bangladesh. Groundwater samples were taken randomly （different depths） in two seasons （wet-monsoon and dry-monsoon）. Hydrochemical analysis revealed groundwater in this area was neutral to slightly alkaline and dominating cations were Na^＋, Mg^2＋, and Ca^2＋ along with major anions Cl^- and HCO3^-. Principal component analysis and Gibbs plot helped explain possible geochemical processes in the aquifer. The irrigation water evaluation indices showed： electrical conductivity （EC） 〉750 μS/cm, moderate to extreme saline; sodium adsorption ratio （SAR）, excellent to doubtful; total hardness （TH）, moderate to very hard; residual sodium bicarbonate, safe to marginal; Kelly＇s ratio 〉1; soluble sodium percentage （SSP）, fair to poor; magnesium adsorption ratio, harmful for soil; and IWQI, moderate to suitable. In addition, the best fitted semivariogram for IWQI, EC, SAR, SSP, and TH confirmed that most parameters had strong spatial dependence and others had moderate to weak spatial dependence. This variation might be due to the different origin/sources of major contributing ions along with the influence of variable river flow and small anthropogenic contributions. Furthermore, the spatial distribution maps for IWQI, EC, SSP, and TH during both seasons confirmed the influence of salinity from the sea; low-flow in the major river system was the driving factor of overall groundwater quality in the study area. These findings may contribute to management of irrigation and/or drinking water in regions with similar groundwater problems.
基金supported by the Knowledge Innovation Program of Chinese Academy of Sciences(No.KZCX2-YWJC402)the Hundred Talents Program of Chinese Academy of Sciences(No.A0815)+1 种基金the National Natural Science Foundation of China(No.41371474)supported by the Chinese Academy of Sciences Visiting Professorships for Senior International Scientists in 2011(No.2011T2Z18)
文摘Integrating land use type and other geographic information within spatial interpolation has been proposed as a solution to improve the performance and accuracy of soil nutrient mapping at the regional scale. This study developed a non-algorithm approach, i.e., applying inverse distance weighting （IDW） and ordinary kriging （OK）, to individual land use types rather than to the whole watershed, to determine if this improved the performance in mapping soil total C （TC）, total N （TN）, and total P （TP） in a 200-km2 urbanizing watershed in Southeast China. Four land use types were identified by visual interpretation as forest land, agricultural land, green land, and urban land. One hundred and fifty soil samples （0-10 cm） were taken according to land use type and patch size. Results showed that the non-algorithm approach, interpolation based on individual land use types, substantially improved the performance of IDW and OK for mapping TC, TN, and TP in the watershed. Root mean square errors were reduced by 3.9% for TC, 10.770 for TN, and 25.9% for TP by the application of IDW, while the improvements by OK were slightly lower as 0.9% for TC, 7.7% for TN, and 18.1% for TP. Interpolations based on individual land use types visually improved depiction of spatial patterns for TC, TN, and TP in the watershed relative to interpolations by the whole watershed. Substantial improvements might be expected with denser sampling points. We suggest that this non-algorithm approach might provide an alternative to algorithm-based approaches to depict watershed-scale nutrient patterns.
文摘An attempt to estimate the reserves in the High Phosphorous stockpile （HP） at the Choghart Iron mine of Iran was carded out using geostatistical modeling. Grade and tonnage estimates of ore stockpiles can help convert them into a valuable ore reserve. This is valuable in consideration of increasing metal demand, and the depletion of in situ ore reserves, around the world. Estimation of reserves in stockpiles is difficult partly because of geological and grade discontinuities created during the dumping of the ore piles. Data input for the HP stockpile at Choghart was performed based upon pre-existing information gathered during extraction from the various mining benches. After establishing the input data files the reserve estimates were found using geostatistical methods aided by the international mining software SURPAC. The stockpile was divided in to three domains and the reserves in each domain were estimated separately. A grade block model was used to compute the reserve. Fe% and P% were estimated using the Ordinary Kriging method. The results showed that the total tonnage of the HP stockpile is 4.5 million tons with an average zrade of 55% Fe and 1.03% P.
基金substantially supported by the National Natural Science Foundation of China(Grant No.42072302)Shuguang Program from Shanghai Education Development Foundation and Shanghai Municipal Education Commission(Grant No.19SG19)Fundamental Research Funds for the Central Universities.
文摘To consider the complex soil-structure interaction in a pile-slope system,it is necessary to analyze the performance of pile-slope systems based on a three-dimensional(3D)numerical model.Reliability analysis of a pile-slope system based on 3D numerical modeling is very challenging because it is computationally expensive and the performance function of the pile failure mode is only defined in the safe domain of soil stability.In this paper,an efficient hybrid response surface method is suggested to study the system reliability of pile-reinforced slopes,where the support vector machine and the Kriging model are used to approximate performance functions of soil failure and pile failure,respectively.The versatility of the suggested method is illustrated in detail with an example.For the example examined in this paper,it is found that the pile failure can significantly contribute to system failure,and the reinforcement ratio can effectively reduce the probability of pile failure.There exists a critical reinforcement ratio beyond which the system failure probability is not sensitive to the reinforcement ratio.The pile spacing affects both the probabilities of soil failure and pile failure of the pile-reinforced slope.There exists an optimal location and an optimal length for the stabilizing piles.
基金Supported by Forest Management Key Subject Construction Project of Southwest Forestry University(XKZ200901)
文摘[Objective] The aim was to study the spatial information of temperature and precipitation data in Hengduan mountains. [Method] Considering GIS spatial interpolation and numerical statistics theory, spatial prediction were carried out to the ten years average temperature and precipitation flux observation data in 109 sparse meteorological stations in Hengduan Mountains. Based on the spatial range of geographic position of Hengduan Mountains, and 1∶1 000 000 scale DEM as data sources, and using trend surface simulation and residual ordinary Kriging interpolation correction method, the spatial continuous surface for annual average temperature and precipitation were studied. [Result] It was scientific and reasonable to use certain unevenly distributed sparse climate observation station value, and by dint of trend simulation and residue interpolation method to get climate consecutive spatial result. This method can not only accurate the temperature and precipitation spatial distributions to grid point, but also can reflect macro and micro geography factors and topographic influence factor of variation. Furthermore, it can be predicted error term trend surface reasonable spatial distribution. Simulation results were basically in accordance with the objective law, and can be used for the region climate data spatial informatization simulation. [Conclusion] The study provided scientific spatial basic data for the further study of ecological and vegetation in Hengduan Mountains.
文摘Among spatial interpolation techniques,geostatistics is generally preferred because it takes into account the spatial correlation between neighbouring observations in order to predict attribute values at unsampled locations.A doline of approximately 15 000 m 2 at 1 900 m above sea level (North Italy) was selected as the study area to estimate a digital elevation model (DEM) using geostatistics,to provide a realistic distribution of the errors and to demonstrate whether using widely available secondary data provided more accurate estimates of soil pH than those obtained by univariate kriging.Elevation was measured at 467 randomly distributed points that were converted into a regular DEM using ordinary kriging.Further,110 pits were located using spatial simulated annealing (SSA) method.The interpolation techniques were multi-linear regression analysis (MLR),ordinary kriging (OK),regression kriging (RK),kriging with external drift (KED) and multi-collocated ordinary cokriging (CKmc).A cross-validation test was used to assess the prediction performances of the different algorithms and then evaluate which methods performed best.RK and KED yielded better results than the more complex CKmc and OK.The choice of the most appropriate interpolation method accounting for redundant auxiliary information was strongly conditioned by site specific situations.
基金The work was supported by the National Key Research and Development Program of China:High Efficiency Cultivation and Monitoring Technology for Timber Bamboo(Grant No.:2018YFD0600103).
文摘This study investigates the spatial variability of soil organic matter(SOM),soil organic carbon(SOC)and pH in the upper 20-cm layer and 20-40 cm layer in Moso bamboo(Phyllostachys pubescens Pradelle)forests using a geostatistics model.Interpolation maps of SOM,SOC,and pH were developed using ordinary kriging(OK)and inverse distance weighted(IDW)methods.The pH,SOC,and SOM of the two soil layers ranged from 4.6 to 4.7,from 1.5 to 2.7 g kg^(-1)and from 20.3 to 22.4 g kg^(-1),respectively.The coefficient of variation for SOM and SOC was 29.9-43.3%while a weak variability was found for pH.Gaussian and exponential models performed well in describing the spatial variability of SOC contents with R^(2)varying from 0.95 to 0.90.The nugget/sill values of pH are less than 25%,which indicates a strong spatial correlation,while the nugget/sill values of SOC and SOM fall under moderate spatial correlation.Interpolation using ordinary kriging and inverse distance weighted methods revealed that the spatial distribution of SOM,SOC,and pH was inconsistent due to external and internal factors across the plots.Regarding the cross-validation results,the ordinary kriging method performed better than inverse distance weighted method for selected soil properties.This study suggests that the spatial variability of soil chemical properties revealed by geostatistics modeling will help decision-makers improve the management of soil properties.
文摘Faced with the scarcity of surface water accentuated by climate change, particularly in many arid and semi-arid countries, the quality of groundwater used for irrigation is a concern to agronomists and hydrogeologists. When </span><span style="font-family:Verdana;">these waters are of deep origin, they may have high mineralization and</span><span style="font-family:Verdana;"> chemical compositions unsuitable for irrigation;in particular, they may alter soils and crops. It is therefore important to optimize the spatial estimation of the salinity of these waters and contribute to better knowledge of their quality, through an adapted and robust statistical and geostatistical approach. In the case of north-eastern Algeria, the objective of this study is to characterize the quality of deep waters and to test two interpolation methods (Inverse distance weight and ordinary Kriging) of their electrical conductivity (EC) as an indicator of their salinity and of the risk of damaging irrigated soils. 51 ground</span><span style="font-family:Verdana;">water samples were taken in this region where there are many thermal </span><span style="font-family:Verdana;">springs, the water of which is used for irrigation and often is highly mineralized (EC between 0.6 and 26.6 dS/m). The geology is composed of karstic rocks crossed by large faults that allow deep water to rise. Based on major elements contents, analysis of the hydrochemical facies of these waters shows that the main facies are hyperchlorinated sodium (38%) and sulfated calcium (32%). The RSC (Residual Sodium Carbonate) and SAR (Irrigation water salt) indexes were used to assess the water quality. The results indicate that the majority of the sampled</span><span style="color:red;"> </span><span style="font-family:Verdana;">groundwater present a risk for soils irrigated with these waters (almost 1/3 presents a strong risk). The risk for the soils seems to be explained by the positive value of the residual alkalinity, and the high risks of sodization and alkalinization. The geostatistical analysis reveals strong heterogeneity in electrical conductivity (salinity). The maps based on this analysis allow the identification of risk areas. The comparison of Inverse distance weight and ordinary Kriging methods indicates similar results being obtained through both methods. However, ordinary kriging appears to be more accur</span><span style="font-family:Verdana;">ate, less biased, and seemingly better represents the organization of the </span><span style="font-family:Verdana;">groundw</span><span style="font-family:Verdana;">ater resources, as NE-SW alignments are visible. With the proposed ap</span><span style="font-family:Verdana;">proach, it is possible to calculate the surface areas of the different salinity </span><span style="font-family:Verdana;">thresholds and then optimize the use of deep groundwater for irrigation.
基金The article is supported by National Key Research and Development Projects of P.R.China(No.2018YFD0600100).
文摘A general regression neural network model,combined with an interative algorithm(GRNNI)using sparsely distributed samples and auxiliary environmental variables was proposed to predict both spatial distribution and variability of soil organic matter(SOM)in a bamboo forest.The auxiliary environmental variables were:elevation,slope,mean annual temperature,mean annual precipitation,and normalized difference vegetation index.The prediction accuracy of this model was assessed via three accuracy indices,mean error(ME),mean absolute error(MAE),and root mean squared error(RMSE)for validation in sampling sites.Both the prediction accuracy and reliability of this model were compared to those of regression kriging(RK)and ordinary kriging(OK).The results show that the prediction accuracy of the GRNNI model was higher than that of both RK and OK.The three accuracy indices(ME,MAE,and RMSE)of the GRNNI model were lower than those of RK and OK.Relative improvements of RMSE of the GRNNI model compared with RK and OK were 13.6%and 17.5%,respectively.In addition,a more realistic spatial pattern of SOM was produced by the model because the GRNNI model was more suitable than multiple linear regression to capture the nonlinear relationship between SOM and the auxiliary environmental variables.Therefore,the GRNNI model can improve both prediction accuracy and reliability for determining spatial distribution and variability of SOM.
