Selection of appropriate interpolation methods for the conversion of discrete samples into continuous maps is a controversial issue in the environmental researches. The main objective of this study was to analyze the suitability of three interpolation methods for the discrimination of groundwater with respect to the water quality index (WQI). The groundwater quality data consisted of 17 variables associated with 65 wells located in Andimeshk-Shush Plain. Three spatial interpolation methods including ordinary kriging (OK), empirical Bayesian kriging (EBK), and inverse distance weighting (IDW) were utilized for modeling the groundwater contamination. In addition, different cross-validation indicators were applied to assess the performance of different interpolation methods. The results showed that the performance differed slightly among different methods, although the best performed interpolation method in this study was the empirical Bayesian kriging. Among the interpolation methods, IDW with weighting power of 4 estimated the most contaminated area, while OK estimated the lowest contaminated area. The weighting power of IDW had a significant influence on the estimation, meaning that the estimated contaminated area was increased when a greater weighting power was selected. The subtraction results indicated that there are slightly spatial differences among the contamination assessment results. Results of both standard deviation (SD) and coefficient of variation (CV) also showed that uncertainty was highest in the southern part of the study area, where the distribution of wells were more intensive than that of the northern part.

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There is an increasing demand for the development of brick kilns area in Iran, which emit a considerable amount of pollutants to environment. The present study aimed to investigate the extent of soil contamination by heavy metals around the brick kiln area in Aran-o-Bidgol city. The correlation coefficients, analysis of variance, principal component analysis, cluster analysis, soil contamination indices and interpolation technique were utilized to investigate the soil contamination and pinpoint the possible sources of contamination. The Results showed the average concentration of all heavy metals were greater than background values and soils were contaminated by heavy metals to some extent. Results also indicated that copper, nickel and zinc had simultaneously emanated from anthropogenic including agricultural activities and urban emissions while the sources of cadmium and lead could mostly be attributed to different anthropogenic activities including brick kilns and related transportation. The distribution maps revealed that the brick kilns emissions had only affected the concentrations of cadmium and lead to some degree.

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The maximum entropy (Maxent) model was used to predict the distribution of Persian leopards and wild sheep in the Tang-e-Sayad protected area in Iran. For this purpose, eight variables, as well as 30 occurrence points of leopard and 98 points of wild sheep, were used. Two techniques, density-based occurrence points thinning and performance-based predictor variables selection were used to improve the results of the model. The model results were analyzed based on four threshold limit-based statistics (sensitivity, specificity, kappa and true skill statistics) and area under the curve (AUC), followed by determining the relative importance of variables based on the jackknife procedure. The results of threshold limit-based statistics revealed that the success of the model for distribution prediction of leopard and wild sheep were good and relatively good, respectively. According to the jackknife procedure, for wild sheep and for leopard, slope and distance to road, respectively, were the most important predictor variables. The results also indicated that the efficiency of the model did not improve by reducing the density of occurrence points for the wild sheep (AUC=0.784–0.773). However, the selection of predictor variables slightly improved the performance of the model (AUC=0.794–0.819). The results of the study also showed overlapping habitat for two species due to both human and ecological reasons for which we proposed some conservation actions such as excluding domestic grazing, controlling illegal poaching and restoration of old migratory corridors.

The main objective of this study was to determine the concentration of cadmium, chromium, copper, nickel, lead, and zinc in surface soils of two land uses including agricultural and urban green space in Semnan Province, Iran. For this purpose, the soil samples of 27 urban green space and 47 agricultural fields were collected and analyzed. The correlation coefficients, analysis of variance, principal component analysis, cluster analysis, and geoaccumulation index were utilized to compare the mean values in the two land uses and pinpoint the possible sources of contamination in the study area. The average contents of Cd, Cu, Cr, Ni, Pb, and Zn in green space soils were 0.1, 24.9, 78.7, 28.2, 22.1, and 82.1 mg/kg, respectively, while the mean concentrations of Cd, Cu, Cr, Ni, Pb, and Zn in agricultural soils were 0.3, 24.3, 83.7, 33.3, 18.1, and 80.4 mg/kg, respectively. The mean concentrations of lead, copper, and zinc were higher in urban green space in comparison with those of agricultural fields, while it was vice versa for chromium, cadmium, and nickel. In general, significant, but weak, correlations were observed between Zn with Pb (r = 0.53) and Cu (r = 0.61) and Ni with Cr (r = 0.55) and Cu(r = 0.51). The main sources of contamination turned out to be both natural and anthropogenic as the results of correlation coefficients, principal component analysis, and cluster analysis showed. That is to say, chromium and nickel had emanated from natural while the sources of cadmium, lead, and zinc could be attributed to anthropogenic activities. For the case of copper, both natural and anthropogenic activities were influential; however, the role of human activities was more effective. The results of contamination assessment showed that heavy metal contamination in agricultural land use was higher than green space indicating the role of human activities in this respect.

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Heavy metals usually accumulate and migrate in soil environment due to human activities and this in return poses potential ecological and health risks. A total of 135 surface soil samples were collected from Aran-o-Bidgol City, Iran and were analyzed for their Cd, Pb, Ni and Cu concentrations to determine these elements' spatial distribution and potential ecological risks. To this end, interpolation mapping was conducted using Ordinary Kriging. The mean concentrations of Cd, Pb, Ni and Cu in the samples were 0.72, 11.41, 29.87 and 14.82 mg kg(-1), respectively, which were all higher than their background values. The spatial variation in the concentration of heavy metals could be attributable to point sources and vehicle emissions. Considering the severity of the potential ecological risks of metals, the descending order of contaminants' concentrations was Cd > Cu > Ni > Pb. The Potential Ecological Risk Index (RI) suggested that approximately 40 % and 59 % of the samples posed high and significantly high potential ecological risks, respectively. Moreover, ecological risk decreased progressively going from southwest to northeast over the under-study area. Considering the background values and RI, this area presented a relatively high level of contamination.