Review of the Kriging Technique Applications to Groundwater Quality

Kriging, a geostatistical technique, has been used for many years to evaluate groundwater quality. The best estimation data for unsampled points were determined by using this method depending on measured variables for an area. The groundwater contaminants assessment worldwide was found through many kriging methods. The present paper shows a review of the most known methods of kriging that were used in estimating and mapping the groundwater quality. Indicator kriging, simple kriging, cokriging, ordinary kriging, disjunctive kriging and lognormal kriging are the most used techniques. In addition, the concept of the disjunctive kriging method was explained in this work to be easily understood.

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Mapping The Distribution of Iron Content in Nickel Laterite Deposits Using Indicator Kriging and Ordinary Kriging Interpolation Method

PROMINE ◽

10.33019/promine.v9i1.2316 ◽

2021 ◽

Vol 9 (1) ◽

pp. 29-36

Author(s):

Hendro Purnomo

Keyword(s):

Root Mean Square ◽

Iron Content ◽

Ordinary Kriging ◽

Interpolation Method ◽

Indicator Kriging ◽

Kriging Interpolation ◽

Mean Square ◽

Kriging Method ◽

Nickel Laterite ◽

Kriging Interpolation Method

Beside containing nickel (Ni), nickel laterite deposits also contain other elements, including iron (Fe) which have varying levels in each layer. In this study, the distribution of Fe content in the limonite layers was carried out using the indicator kriging method to analyze the probability distribution of iron levels and ordinary kriging to analyze the variability of iron levels spatially. Fitting the variogram was undertaken by using spherical, exponential and gaussian models. The selection of the best variogram model was carried out based on the smallest root mean square error (RMSE) value, while the estimation of resource potential was calculated by the polygon extended area method. The results of the interpolation show that the distribution of iron anomaly occupies ± 83,3% of the research area with a potential resource of ±64.522.110 ton of iron. The evaluation of the interpolation results base on the root mean square standardized prediction error (RMSP) indicates that the estimation results of iron content using the ordinary kriging method are underestimated.

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Assessing groundwater quality for irrigation using indicator kriging method

Applied Water Science ◽

10.1007/s13201-014-0230-6 ◽

2014 ◽

Vol 6 (4) ◽

pp. 371-381 ◽

Cited By ~ 9

Author(s):

Masoomeh Delbari ◽

Meysam Amiri ◽

Masoud Bahraini Motlagh

Keyword(s):

Groundwater Quality ◽

Indicator Kriging ◽

Kriging Method

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COMPARISON ANALYSIS OF INTERPOLATION TECHNIQUES FOR DEM GENERATION USING CARTOSAT-1 STEREO DATA

International Journal of Remote Sensing and Earth Sciences (IJReSES) ◽

10.30536/j.ijreses.2012.v9.a1829 ◽

2014 ◽

Vol 9 (2) ◽

Author(s):

Andie Setiyoko ◽

Anil Kumar

Keyword(s):

Ordinary Kriging ◽

Interpolation Method ◽

Indicator Kriging ◽

Stereo Image ◽

Single Frequency ◽

Polynomial Method ◽

Data Sets ◽

Differential Mode ◽

Simple Kriging ◽

Interpolation Techniques

Digital Elevation Model (DEM) can be generated using several techniques such as photogrammetric technique, interferometry, Lidar, etc. In photogrammetric technique, a DEM generation using stereo images, accuracy of generated DEM is also dependent on interpolation techniques. The process of interpolation is conducted to generate DEM as a continuous data from the point map that contained height information as a discrete data. In this research, point map was extracted from Cartosat-1 stereo image and from geodetic single frequency GPS in differential mode. Different interpolation techniques were applied on these data sets with different combination within these data sets. In this study, analysis of DEM interpolation was conducted with deterministic interpolators such as inverse distance weighted (IDW), global polynomial, local polynomial, and radial basis functions (RBF); and probabilistic interpolators such as simple kriging, ordinary kriging, universal kriging, indicator kriging, probabilistic kriging, disjunctive kriging, and cokriging. The accuracy of generated DEMs through different interpolation techniques were evaluated with ground point data collected from geodetic single frequency GPS in differential mode. Based on the analysis, the range error of DEMs generated was between 1.29 m to 2.96 m. Interpolation method with the least error was ordinary kriging using point map data and GPS points, while the highest error was obtained from global polynomial method.

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Prediction concentration of PM2.5 in Surabaya using ordinary Kriging method

10.1063/5.0042284 ◽

2021 ◽

Author(s):

Derbi W. Fitri ◽

Nurul Afifah ◽

Siti M. D. Anggarani ◽

Nur Chamidah

Keyword(s):

Ordinary Kriging ◽

Kriging Method

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Interpolation of groundwater quality parameters with some values below the detection limit

Hydrology and Earth System Sciences ◽

10.5194/hess-15-2763-2011 ◽

2011 ◽

Vol 15 (9) ◽

pp. 2763-2775 ◽

Cited By ~ 16

Author(s):

A. Bárdossy

Keyword(s):

Detection Limit ◽

Maximum Likelihood ◽

Groundwater Quality ◽

Likelihood Estimation ◽

Quality Parameters ◽

Indicator Kriging ◽

West Germany ◽

Marginal Distributions ◽

Copula Models ◽

Measuring Device

Abstract. For many environmental variables, measurements cannot deliver exact observation values as their concentration is below the sensitivity of the measuring device (detection limit). These observations provide useful information but cannot be treated in the same manner as the other measurements. In this paper a methodology for the spatial interpolation of these values is described. The method is based on spatial copulas. Here two copula models – the Gaussian and a non-Gaussian v-copula are used. First a mixed maximum likelihood approach is used to estimate the marginal distributions of the parameters. After removal of the marginal distributions the next step is the maximum likelihood estimation of the parameters of the spatial dependence including taking those values below the detection limit into account. Interpolation using copulas yields full conditional distributions for the unobserved sites and can be used to estimate confidence intervals, and provides a good basis for spatial simulation. The methodology is demonstrated on three different groundwater quality parameters, i.e. arsenic, chloride and deethylatrazin, measured at more than 2000 locations in South-West Germany. The chloride values are artificially censored at different levels in order to evaluate the procedures on a complete dataset by progressive decimation. Interpolation results are evaluated using a cross validation approach. The method is compared with ordinary kriging and indicator kriging. The uncertainty measures of the different approaches are also compared.

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Estimating the Recoverable Reserves of Gold Deposits: Comparison Between Disjunctive Kriging and Indicator Kriging

Quantitative Geology and Geostatistics - Geostatistics Tróia ’92 ◽

10.1007/978-94-011-1739-5_84 ◽

1993 ◽

pp. 1053-1064 ◽

Cited By ~ 5

Author(s):

Jean-Paul Chilès ◽

Hong-Tao Liao

Keyword(s):

Indicator Kriging ◽

Gold Deposits ◽

Disjunctive Kriging ◽

Recoverable Reserves

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Improvement of Spatial Modeling of Cr, Pb, Cd, As and Ni in Soil Based on Portable X-ray Fluorescence (PXRF) and Geostatistics: A Case Study in East China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16152694 ◽

2019 ◽

Vol 16 (15) ◽

pp. 2694 ◽

Cited By ~ 9

Author(s):

Xia ◽

Hu ◽

Shao ◽

Xu ◽

Zhou ◽

...

Keyword(s):

Heavy Metals ◽

Hot Spots ◽

Ordinary Kriging ◽

Eastern China ◽

Indicator Kriging ◽

Polluted Water ◽

X Ray ◽

Soil Heavy Metals ◽

Metals Pollution ◽

Heavy Metals Pollution

To verify the feasibility of portable X-ray ﬂuorescence (PXRF) for rapidly analyzing, assessing and improving soil heavy metals mapping, 351 samples were collected from Fuyang District, Hangzhou City, in eastern China. Ordinary kriging (OK) and co-ordinary kriging (COK) combined with PXRF measurements were used to explore spatial patterns of heavy metals content in the soil. The Getis-Ord index was calculated to discern hot spots of heavy metals. Finally, multi-variable indicator kriging was conducted to obtain a map of multi-heavy metals pollution. The results indicated Cd is the primary pollution element in Fuyang, followed by As and Pb. Application of PXRF measurements as covariates in COK improved model accuracy, especially for Pb and Cd. Heavy metals pollution hot spots were mainly detected in northern Fuyang and plains along the Fuchun River in southern Fuyang because of mining, industrial and traffic activities, and irrigation with polluted water. Area with high risk of multi-heavy metals pollution mainly distributed in plain along the Fuchun River and the eastern Fuyang. These findings certified the feasibility of using PXRF as an efficient and reliable method for soil heavy metals pollution assessment and mapping, which could contribute to reduce the cost of surveys and pollution remediation.

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Spatial Interpolation on Rainfall Data over Peninsular Malaysia Using Ordinary Kriging

Jurnal Teknologi ◽

10.11113/jt.v63.1912 ◽

2013 ◽

Vol 63 (2) ◽

Cited By ~ 1

Author(s):

Suhaila Jamaludin ◽

Hanisah Suhaimi

Keyword(s):

Spatial Analysis ◽

Ordinary Kriging ◽

Spatial Interpolation ◽

Rainfall Intensity ◽

Peninsular Malaysia ◽

Rainfall Data ◽

Kriging Method ◽

Intensity Index ◽

Dry Conditions ◽

Two Indices

This study presents the spatial analysis of the rainfall data over Peninsular Malaysia. 70 rainfall stations were utilized in this study. Due to the limited number of rainfall stations, the Ordinary Kriging method which is one of the techniques in Spatial Interpolation was used to estimate the values of the rainfall data and to map their spatial distribution. This spatial analysis was analysed according to the two indices that describe the wet events and another two indices that characterize dry conditions. Large areas at the east experienced high rainfall intensity compared to the areas in the west, northwest and southwest. The small value that has been obtained in Aridity Intensity Index (AII) reflects that the high amount of rainfall in the eastern areas is not contributed by low-intensity events (less than 25th percentile). In terms of number of consecutive dry days, Northwestern areas in Peninsular Malaysia recorded the highest value. This finding explains the occurrence of a large number of floods and soil erosions in the eastern areas.

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