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In recent years, due to the expansion of industrial activities, the concentration of heavy metals in the environment as well as foods has increased. Heavy metals are dangerous because of their bioaccumulation. Regarding the importance of contamination of heavy elements of the soil, the present study aimed to provide the spatial distribution of heavy metals and its relationship with land use in the Yazd-Ardakan plain, Iran. First, 201 soil samples from depths of 0 to 20 cm were sampled using the hypercube method, and the total concentration of iron, manganese, nickel, lead, and zinc elements were determined using Analytical Jena-novAA300 atomic absorption device. Then, to convert point data to surface data, geostatistical methods of IDW, GPI, RBF, LPI, and Kriging were used. The land cover/use map of the Yazd-Ardakan plain in 2016 was mapped using an object-oriented classification method. Results of the relationship between heavy metals concentration and land cover/use showed that the agricultural lands and gardens and sand dunes with the mean of 0.950 and 0.836 ppm had the highest and lowest iron concentrations. The highest mean concentration of manganese was related to the residential land (1.821 ppm) and the lowest mean of rocky terrains (1.083 ppm), the most average for poor rangelands and bare land was (0.302 ppm), Residential areas had the lowest nickel concentration (0.192 ppm). The highest mean of lead metal in agricultural land and gardens, as well as residential areas (1.465 and 1.373 ppm, respectively) and the lowest, mean in rocky terrains (0.925 ppm). Agricultural and gardens areas, and residential lands, have the highest mean of zinc concentration (0.583 and 0.552 ppm, respectively), and the rocky terrain has the lowest zinc concentration (0.342 ppm).

Introduction: In recent years, due to the reduction in surface water, utilization of groundwater has been increased to meet the growing demand of irrigation water. The quality of these water resources is continually changing, due to the geological formations, the amount of utilization, and climatic parameters. In many developing countries, the irrigation water is obtained from poor quality groundwater resources, which in turn, creates unfavorable circumstances for plant growth and reduces the agricultural yield. Providing adequate water resources for agricultural utilization is one of the most important steps needed to achieve the developmental targets of sustainable agriculture. Thus, this necessitates the assessment and evaluation of the quality of irrigation water. There are many proposed methods to determine the suitability of water for different applications, such as Piper, Wilcox, and Schoeller diagrams. Zoning of quality and suitability of irrigation water could represent the prone and critical areas to groundwater exploitation. Garmsar alluvial fan is one of the most sensitive areas in the country where traditional agriculture practices had turned into modern techniques and excessive exploitation of groundwater has caused an intensepressure on aquifers and increased water salinity. The aim of this study is to evaluate the suitability of groundwater for irrigation in a 10-year period (2002-2012) and its changes in this basin. Materials and Methods: Garmsar alluvial fan is located in the North-West of Semnan Province. Semnan is situated in the Southern hillside of the Alborz Mountains, in North of Iran. The study area includes the agricultural land on this alluvial fan and covers over 3750 hectares of this basin. In order to evaluate the quality of groundwater in this area, the electrical conductivity and sodium absorption ratio of 42 sample wells were calculated. The raster maps of these indicators were obtained using Geo-statistical techniques. The suitability of irrigation water was determined by Wilcox diagram. Upon evaluating the data distribution and testing the data from Klomogrov-Smirnov normality test, normalization of the data was performed in SPSS software. Spatial correlation and spatial structure of variables were analyzed by drawing their semi-variograms in GS+ software. The most accurate variogram model was selected according to the lowest Residual Sums of Squares (RSS) and the highest correlation coefficient (R2). Interpolation and zoning of the indicators were performed in ArcGIS software and the Quality classes were determined. Results and Discussion: According to the results of Kolmogorov-Smirnov test, none of the data series had normal distribution. Therefore, they were normalized through calculating the logarithm of variables. Fitting and the selection of variograms were performed in GS+ software and after the calculation of errors, kriging method with Guassian model was determined as the best fitting model. The correlation coefficient was 0.896 for electrical conductivity and 0.99 for sodium absorption ratio. Interpolation of indicators in ArcGIS implied fewer measurements of these indicators in north of the study area (Hableh-Rood inlet). The maximum measurement of indicators was observed on the western edge of the alluvial fan. In total, the values of both electrical conductivity and a sodium absorption ratio indicators in the western half of the area, in the vicinity of the third period domes, were more than the eastern half. The result of the water classification using Wilcox diagram represented the unsuitability of groundwater for irrigation in all of the study area. The area with unusable groundwater for irrigation has increased over the 2005 – 2009 period. Conclusion: In this study, relying on the use of GIS and Geo-statistical methods, the quality of Garmsar basin groundwater has been evaluated. The electrical conductivity was applied to monitor water salinity, and Sodium absorption ratio was used to monitor alkalinity. The interpolation of these indicators was performed by Kriging method and Guassian fitting model. Likewise, in other studies, the Kriging method was introduced as an appropriate method for the interpolation of chemical parameters of the groundwater. The accuracy of various fitting models in the prediction of interpolated values differed according to the number and the distribution of sample points. In the current study, the Guassian fitting model was determined as the best model to interpolate both of the indicators. According to the maps, it seems that the third period domes in the western margin of the study area have a great influence on the quality of Garmsar’s surface water and groundwater. In total, the groundwater of Garmsar basin didn’t poss high suitability for irrigation, and was classified into two unsuitable and unusable classes. Moreover, according to the maps, the maximum area of unusable groundwater for irrigation in the area was observed in 2008.

More than 85 percent of current ground water resources extractions are supplying agriculture water demands in Birjand Plain. Because of the importance of water quality for irrigation, 47 samples collected from piezometric wells in Birjand Plain, to determine ground water quality suitability for agriculture. pH and EC values measured at filed campaign beside laboratory analysis of water samples for major ions concentrations. After chemical analysis of water samples, different geo-statistical models had used to model Cl, HCO3, SAR, pH and EC water qualities parameters. Then the error of each simulation was calculated. Finally, the best method was performed to prepare spatiality maps of Cl, HCO3, SAR, pH and EC parameters in Birjand aquifer based on FAO classification. The interpolation errors assessment highlighted Kriging as the most accurate method for all investigated parameters, in compare to Inverse Distance weighting (IDW) and Radial Basis Functions (RBF). The spatiality maps based on FAO classification show that ground water resources in Birjand plain are not applicable for agriculture due to extremely high values of SAR, Cl, and HCO3, where its usage has limited a little for agriculture by EC and its quality has a suitable range of pH.