Spatial data analysis methods have many applications in various fields‎, ‎such as agriculture‎, ‎mining engineering‎, ‎and meteorology‎. ‎In this study‎, ‎ordinary kriging and indicator kriging are considered to predict alumina grade in the Jajarm mine in Iran‎, ‎and the precision of the methods is computed‎. ‎A conditional simulation is carried out based on the data set for a more general comparison of ordinary and indicator kriging to interpolate Alumina grade in the mine‎. ‎In the case of monitoring possible variation related to sample size and type of variogram model‎, ‎simulations are performed with various sample sizes and different types of variogram models‎. ‎Then ordinary and indicator kriging methods are applied for every set of simulated data (concerning different sample sizes and types of variogram models)‎, ‎and root of standardized mean square error prediction is considered as a cross-validation criterion to compare the kriging methods‎. ‎The simulation results show that under the assumptions‎, ‎ordinary kriging has better performance than the indicator kriging method.

This study uses multiple indicator kriging estimator based on assayed data acquired from 48 exploration boreholes in Tabas coal mine in order to predict gas content of coal seams. Results of the estimated block models showed that approximately 12% of the total area has the gas content of less than 5 (m3/ton) (Low risk), 11% has 5-10 (m3/ton) (Medium Risk) and 15% has 10-15 (m3/ton) (High Risk), while about 62% of total area has the gas content of more than 15(m3/ton) which is of a high risk. Therefore, according to the experiences from mined panels, in the zones with lower to median gasification risk, it is possible to keep the mining operation running with management and optimization of the ventilation system. However, in the zones with higher gasification rate, demethanization process is mandatory.

Nitrate contamination is one of the main risks for groundwater in agricultural areas. The evaluation of the effect of agricultural practices on groundwater nitrate concentration, especially in highly sensitive areas, is crucial for a correct land planning, and a good agronomic intervention scheduling. Aim of this paper is to map the probability to exceed nitrate regulatory threshold applying a non-parametric geostatistical approach, the Indicator Kriging (IK). A study in the Fucino Plain (Abruzzo, Central Italy), characterized by highly profitable intensive agriculture with mainly irrigated horticultural and short rotation crops, was carried out. The Plain has a shallow and controlled groundwater table, and channels draining the surplus water during winter. Water samples were collected monthly from piezometers and analysed for nitrate. IK provided a model of spatial uncertainty, representing the probability that the threshold of 50 mg/L fixed by the European Nitrate Directive is exceeded, and results were transferred into a GIS. Maps obtained for each month showed how the probability to exceed the threshold changes during an average year. The methodology can provide an effective operative tool to support decision-makers for the identification and the designation of nitrate vulnerable zones.

Unethical and inequitable exploitation of groundwater resources has led to reduce the amount and the quality of these water. In this study Ordinary Kriging (OK) and Indicator Kriging (IK) methods were used as geostatistical approach for preparation of thematic maps of the groundwater quality in Bajestan plain for agricultural purposes. First each of the measured parameters was compared with the acceptable standard limits based on the FAO standard. Three parameters such as Na, SAR and EC were greater than their respective groundwater pollution cutoff value. First, data normality was investigated and Log-transformed was applied to some parameters. The variogram analysis for each parameter was calculated. The evaluation criteria were ME and RMSE with the Cross Validation method. Then OK was used to analyze the spatial variability and quantitative potential maps, whereas IK was used to analyze groundwater quality parameters equal to or greater than the pollution threshold values. The results showed that the parameters of EC, SAR, and Na in most wells were higher than the threshold value and the salinity and sodium adsorption ratio was high in most of the wells. Most of the groundwater in the study area is restricted to EC. More than 59 wells in which water quality is the most important factor in reducing and uncontrolled utilization of them for long time caused salinity and reduce soil permeability.

In mining areas, assessing toxic elements (e.g., arsenic) contamination in the soil and stream deposits is a critical issue. It is because mining activities release dangerous elements that enter the environment. In this paper, for modeling the spatial distribution of arsenic contamination in Sarduiyeh-Baft area, in Kerman Province, across an area of ca. 5000 km2, 1804 stream sediment samples were collected and analyzed. The recommended standard limit for arsenic in soil is 20 ppm, so samples showing arsenic concentration >20 ppm are contaminated samples, which need land reform processes. However, since the number of collected samples is limited, indicator Kriging method was used to identify the possibility of contamination. In the study area, there are 32 known occurrences of porphyry-Cu deposits. Thus, in order to estimate the arsenic contamination in the unsampled locations, indicator kriging method was used. The results indicate arsenic contaminations in north and northwest parts of the study area, which could be occurred by mining of the porphyry-Cu deposits. However, the results show that there is no arsenic contamination in the eastern part although there are several mining sites with high activities.

Estimation of ore reserves is one of the most critical aspects of mining geology. The accurate assessment of the tonnage and grade of run of mine may be the difference between a healthy profitable operation and an expensive early mine closure. The first step in ore reserve estimation is to determine the boundary of ore body or ore/waste contacts. This paper presents a specific mining application to estimate ore/waste boundaries, which uses usual chemical variables. In the suggested procedure, the geostatistical method of Indicator Kriging (IK) was used to determine the boundary of ore body in Choghart iron mine of Iran. Assuming a cutoff grade in terms of the iron content mode, all data values transformed to either 1 or 0. An IK estimation of transformed data was performed. These values must always lie in the interval [0, 1], and can be interpreted as the probability that the grade is above the specified indicator. Then, the estimated probability plans were compared to the extracted plans. Results showed that blocks with the estimated probability of equal to or more than 0.85 are laid within the ore body boundary and blocks with the probability less than 0.15 should be considered as waste. This rule was then applied to the remaining ore deposit and its reserve was estimated to be about 75 million tons.

Yazd Province is one of the most arid regions of Iran and its agriculture particularly pistachio cultivation depends on groundwater resources. In the recent decades, natural factors (drought and severe evaporation) and human activities (over-exploitation of groundwater) caused a sharp decline in the quality and quantity of groundwater in this province. In the present study, the spatial and temporal variations in groundwater salinity (EC) were evaluated using geostatistical methods and ArcGIS software. For this purpose, ordinary kriging and indicator kriging were used to prepare zoning and probabilistic maps, respectively. Zoning and probabilistic maps showed an increase of groundwater salinity towards higher than 8 dS/m from 2003 to 2012. It was also found that groundwater of Ardakan, Bafgh, Taft, and Abarkouh cities has a very bad condition in terms of salinity and using it for pistachio orchards irrigation can reduce seriously the yield of this plant and its cultivation in the province will be questionable. So as to avoid lowering the quality of groundwater resources in the province, appropriate management measures such as well volumetric water gauge installation and banning both well water extraction and new well water allocation are required.

Using normal Kriging in the evaluation of groundwater quality can not specify the areas susceptible to pollution. In this study, to determine the extent of exceeded nitrate pollution (50 mg/L) as well as identifying the areas susceptible to pollution, nitrate data of 287 wells within an area of 320 square kilometers in Mashhad and the statistical range of 2002 to 2011 was analyzed by R software. The process of evaluation and analysis included re-arranging data sheets, detection of outliers, removing the trend, studying the isotropy, determination of the optimum variogram models for each year, and formulating the spatial and temporal Indicator Kriging. The results showed that Matern semivariogram was the best model for explaining the spatial structure data in each year. Also, in the statistical range respectively 7.1, 5.8, 7.2, 8.5, 8.6, 9.4, 10.4, 2.1, and 2.4 percent of the studied area has passed the pollution allowed limit. It seems that more polluted areas have been controlled since 2009 by some strategies such as shutting down the polluted wells, preventing new well digging, transferring water from Doosti Dam, using appropriate agricultural wells for drinking section and implementation of wastewater collection network. In addition, respectively 10.4, 11.7, 12.4, 9.4, 14.3, 12.2, 6, 11.6 and 11.5 percentage of total area was prone to pollution during these years. Therefore, these areas need more attention for monitoring and controlling the source of pollution.

Due to the importance of groundwater resources in arid and semi arid regions, the qualitative assessment of these resources is so important. Pressurized irrigation as a suitable method for increasing irrigation efficiency and reducing water consumption, requires water quality analysis. Despite many activities of researchers in the preparation of groundwater quality maps by using geostatistical methods, most of these studies have focused on the use of conventional kriging techniques that are not suitable for the preparation of vulnerable zones of contamination, In this study spatial variations of aquifer quality parameters and especially suitable areas for pressurized irrigation were investigated by using indicator Kriging method. For this purpose groundwater quality data from 27 wells in Birjand aquifer were studied during 2016. Qualitative parameters were evaluated including pH (acidity), EC (electrical conductivity), SAR (sodium absorption ratio), Na, NaCl, Cl and ClCO and HCO3, respectively. The allowed thresholds for use of these parameters were considered in pressurized irrigation with the proposed FAO limitaion. On the other hand, due to the importance of LangelierSaturation Index in sedimentation of drip irrigation system, this index was also evaluated for aquifer wells and unsuitable areas for pressurized irrigation in the aquifer were determined using the geostatistical indicator kriging method and ArcGIS software. The results indicate suitable irrigation region are located in the eastern and central parts of the plain.

Probability mapping of soil proprieties Including soil organic carbon and nutrients based on threshold values play important role in optimum land management and sustainable agriculture development. In order to map based on critical limits need to use non parametric geostatistics methods such as kriging indicator. In this study, using indicator kriging, probability map of deficiency or excess of soil available phosphorus and organic carbon was prepared in part of Eslamabad-e Gharb agriculture research station in Kermanshah province. The soil legacy data including 217 surface soil samples on an almost regular grid, about 50 m apart is used to perform research. After preliminary statistical processing, indicator variogram was drawn based on threshold values 1.2% and 15ppm for soil organic carbon and available phosphorus, respectively. Exponential model as the best model fitted to indicator variogram is selected based on minimum residual sum of squares. The necessary data for validation was achieved through leave-one-out cross-validation (LOOCV).For assessing the performance of indicator kriging is used the area under the curve (AUC) of receiver operating characteristic (ROC). Area under the ROC curve was calculated for phosphorus and soil organic carbon was 0.796 and 0.800, respectively. These results indicated that the indicator kriging to predict these variables have relatively good performance. In general, it can be said that using fertilizer based on probability maps of soil fertility properties lead to reduce cost and increase sustainable food production.