Ehsan Ghojehpour; Vahidreza Jalali; Azam Jafari; Majid Mahmoodabadi
Abstract
Introduction Spatial and temporal variations of soil characteristics occur in large and small scales. Investigating the variability of soil parameters is considered as one of the requirements for proper management of fertilizer resources in a sustainable agricultural system. Studying of these variation ...
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Introduction Spatial and temporal variations of soil characteristics occur in large and small scales. Investigating the variability of soil parameters is considered as one of the requirements for proper management of fertilizer resources in a sustainable agricultural system. Studying of these variation is very time-consuming and costly especially in large scales. In order to the fast and reliable determination of the soil properties, various interpolation techniques have been developed and applied. The most widely used interpolation technique is the different Kriging types. The copula function is one of the new interpolation techniques that are recently used in sciences such as hydrology. Thus, the aim of this research was to evaluate the spatial variation of some soil chemical properties using the copula function and comparisons with geostatistics techniques. Materials and Methods Sampling by regular networking was done in an area of 484 ha located in 10 km far from the west of Baft city, located in Kerman province, central Iran (latitude of 29° 15′ N and longitude of 56° 29′ E). In the studied area, three agricultural, pasture and industrial sites are located nearby. The common crops of the region are wheat, barley, alfalfa, legumes and orchards of walnuts, pomegranates, almonds and grapes. The average height of the studied area is 2270 meters above sea level, the average annual temperature of the area is 16 degrees Celsius, and the average annual precipitation of the area is 247 mm. The soil used for the experiment was collected from 0 to 20 cm depth of the field. 121 soil samples were air-dried and, some physical and chemical properties were measured. In order to fit the Copula function to the data, first the appropriate marginal distribution function should be fitted to the data. For this purpose, three tests were used: Kolmogorov-Smirnov, Anderson-Darling and Chi-Square. The mentioned tests were carried out in the EasyFit 5.5 statistical software. By fitting the best marginal distribution function, the cumulative value of the marginal distribution function is calculated for each data. After calculating the above values, detailed functions can be fitted to the data. Finally, the accuracy of each interpolation method was evaluated according to the root mean square Error (RMSE), coefficient of determination (R2), mean absolute error (MAE) and mean biass error (MBE) indices. Results and Discussion In all types of geostatistical methods, the first step in interpolation is to fit the semivaiogram to the measured data, so after normalizing the data and validating the models, the appropriate model was selected for fitting the semivaiogram. Among the measured parameters, Pava and Kava semivaiogram followed spherical model and the interpolation of the above variables was done on the basis of this model. Copula analysis showed that the available phosphorous and potassium variables followed from the Wakeby and gamma distribution function, respectively. Also, based on the Pearson correlation coefficient, the correlation between pairs of points was less than 2000 m and the distance more than 2000 m was known as an independent distance. Based on the validation criteria for Pava parameter, Median copula function, Average copula function, IDW, Ordinary Kriging, Disjunctive Kriging, Universal Kriging and Simple Kriging have better estimates, respectively, and in the same way, the best interpolator for Kava parameter Median copula function, Average copula function, Ordinary Kriging, Universal Kriging, Disjunctive Kriging, Simple Kriging and IDW were determined, respectively. The estimation performance based on the coefficient of determination (R2) showed that value of this coefficient for copula function for available phosphorous and potassium were 5% and 4% greater than conventional geostatistics techniques. Also, the error of estimation was less for copula function indicating the better performance of copula to estimate the mentioned soil propertiesConclusion This study was performed to investigate the Feasibility study of Copula function in predicting some soil nutrients and comprising this method with widely used methods of geostatistics. Our results demonstrated that the copula function method is more capable than the classical geostatistical methods in estimating soil properties due to the non-dependence of this method on the normality of the data distribution and outlier data. Therefore, with the help of this method, having a reliable and high-quality data bank of soil characteristics, acceptable maps of other soil characteristics can be presented at various scales.
Shohreh Moradpour; MOjgan Entezari; Shamsollah Ayoubi; Salman Naimi
Abstract
Impacts of land use and geomorphology on some heavy metal concentrations in a part of Zayandehroud dam watershed IntroductionWith the rapid development of industry and urbanization, soil pollution with heavy metals as a result ecosystem destruction has attracted global attention. Pollutants are considered ...
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Impacts of land use and geomorphology on some heavy metal concentrations in a part of Zayandehroud dam watershed IntroductionWith the rapid development of industry and urbanization, soil pollution with heavy metals as a result ecosystem destruction has attracted global attention. Pollutants are considered environmental threats and among pollutants, heavy metals are known for their non-degradability and physiological effects on living organisms even at low concentrations. The close correlation of magnetic properties and heavy metals shows that magnetic measurement is an efficient and cheap tool to detect heavy metal contamination in soils affected by heavy industries and traffic pollution. Magnetic minerals in soil may be inherited from parent rocks (lithogenic origin), pedogenesis (pedogenic origin), or may result from human activities (secondary ferromagnetic materials). The concentration of metals can be influenced by geomorphology and various soil properties such as organic carbon, electrical conductivity. Land use directly or indirectly affects the geochemical behaviors of heavy metals through regulating soil properties. The main objectives of this study were to investigate the effect of land use change on magnetic receptivity and the concentration of some heavy metals including zinc, copper, iron, nickel, chromium, cobalt and manganese in the 20 cm soil surface layers, and to explore spatial distribution of magnetic receptivity and heavy metals under different types of land use and geomorphological units in the studied area.Materials and MethodsThe present research was conducted in Isfahan province in the center of Iran with an area of 227 Km2. This area has an average temperature of 9.8 oC and an average annual rainfall of 324 mm and an altitude of 2380 meters a.s.l. Based on Kopen's classification, the climate was classified as semi-arid with cold winters. Geologically, it belongs to the Sanandaj-Sirjan zone, the dominant rocks of the area include limestone, shale limestone, slate and Quaternary sediments. The most important land uses in the region included pasture, rainfed and irrigated agriculture, and in terms of geomorphology, the region comprised river plains and pediments. Soil sampling was done by stratified random method. A total of 100 samples were collected from the surface layer (0-20 cm depth) in the summer of 2021. Magnetic susceptibility was measured at high and low frequencies using Bartington MS2 dual frequency sensor. The concentration of heavy metals including iron, zinc, manganese, nickel, copper, chromium and cobalt were measured by atomic absorption spectroscopy. pH, organic carbon, calcium carbonate, electrical conductivity were measured in all samples. Spearman's correlation coefficient was used to check the correlation between different parameters. Analysis of variance was applied to evaluate the effects of geomorphology and land use on heavy metals and magnetic susceptibility. Spatial analysis was performed for heavy metals and magnetic susceptibility, and the maps were prepared in ArcGIS v.10.7 software.Results and DiscussionThe results showed that there was a negative and significant correlation between calcium carbonate, heavy metals and geomorphology. There was no significant correlation between organic carbon and heavy metals in land uses. But there was a negative correlation in the river plains and alluvium. There is a significant negative correlation between electrical conductivity, copper, manganese, and nickel. In the use of agricultural lands and river plains, there is a positive correlation between low-frequency magnetic susceptibility and high-frequency magnetic receptivity with electrical conductivity. Also, pH showed a significant negative correlation with magnetic susceptibility in pasture land and had no relationship in other land uses. There is a positive correlation between calcium carbonate and frequency-dependent magnetic susceptibility in agricultural land use and river plains. There is a significant positive correlation between heavy metals and magnetic susceptibility in pediments and some land uses, especially in rainfed lands. The results of analysis of variance showed significant difference (p*<0.05) in land use regarding heavy metal concentrations. In this analysis, there was a significant difference between cobalt, nickel and manganese elements according to land use, and the magnetic susceptibility among the studied geomorphic surfaces. According to the results of the test, there was a significant difference for heavy metals in various geomorphic surfaces. The content of iron, chromium, cobalt, nickel and manganese in river plains and pediment had significant differences with hills.ConclusionThe present study was conducted with the aim of clarifying the effect of land use and geomorphology on magnetic susceptibility and concentration of heavy metals in a part of the Zayandeh River watershed in Isfahan province. The average of nickel and manganese in the soils of the study area is higher than the normal range, due to parent materials effects and agricultural activities (plowing and irrigation) accelerate the soil formation processes and increase the amount of these elements in the soil. The highest concentration of cobalt, iron, zinc, copper, nickel and chromium elements were observed in dryland farming. In addition, investigating the spatial distribution of magnetic receptivity values and heavy metals in different places are significantly different. Higher values of magnetic susceptibility were seen in the center of the studied area. Spatial distribution of heavy metals iron and chromium are concentrated in the center of the region and other metals are concentrated in the west and northwest. Probably, parent materials such as shale, dolomite, limestone and sandstone and weathering and release of elements in the soil increase the concentration of these elements in the region.Keywords: Geomorphology, land use, LSD test, kriging