Soil science
P. Kabiri Samani; M.H. Salehi; H.R. Motaghian
Abstract
Introduction In addition to the minerals, weathering in soil which depends on soil forming factors and processes, plants rhizosphere release components which affect soil minerals and finally their weathering. If the soil is polluted by heavy metals, root exudates will be influenced resulting in ...
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Introduction In addition to the minerals, weathering in soil which depends on soil forming factors and processes, plants rhizosphere release components which affect soil minerals and finally their weathering. If the soil is polluted by heavy metals, root exudates will be influenced resulting in decreasing microbial activity. Many studies showed minerals weathering in rhizospheric medium for both natural soils and pure clay minerals but information about the effect of pollution of rhizosphere on clay minerals weathering is limited. This study was conducted to investigate the effect of cadmium pollution on the transformation of clay minerals in wheat rhizosphere in a dominant soil of Shahrekord plain (Chaharmahal soil series).Materials and methods Soil samples were collected from 0-20 cm depth of Chaharmahal soil series based on the 1:50,000 scale soil map. A factorial experiment as completely randomized design with three replications and three cadmium levels (0, 5, and 10 mg kg-1 from cadmium) was performed in two environments including bulk soil and rhizospheric soil (18 samples in total) in greenhouse conditions for 16 weeks. Necessary care was taken during the growth period and the soil moisture was kept constant at the field capacity. At harvest time, the rhizosphere soil was separated from bulk soil. Then, the soil samples were air dried and passed through a 2 mm sieve. The mineralogy was examined by X-ray diffraction (XRD) in the studied soil after plant harvest (including rhizospheric soil and bulk soil) in unpolluted samples. Then, results were compared with minerals in polluted rhizosphere media. Dissolved organic carbon (DOC) and pH in the rhizosphere and bulk soils were also determined.Results and Discussion The results showed that the effect of contamination on soil pH was not significant but the pH value in rhizosphere soil was significantly lower than the bulk soil. The average pH in the soil was 7.8 and in the rhizosphere reduced to 7.5. The interaction of medium (rhizosphere and bulk soil) and contamination on the amount of dissolved organic carbon was significant (p < 0.01). The amount of dissolved organic carbon in the rhizosphere at 170.6 mg Kg-1 was significantly higher than the bulk soil (104.6 mg kg-1), which could be due to root secretions. In the rhizosphere, increasing the contamination level to 5 mg kg-1 decreased by 19% and contamination of 10 mg kg-1 caused a 21% decrease in dissolved organic carbon. The amount of dissolved organic carbon in the rhizosphere was 39% higher than the bulk soil. The average of dissolved organic carbon in the rhizosphere and bulk soil was 170.6 and 104.6 mg kg-1, respectively. Based on mineralogical results, mica, smectite, chlorite, kaolinite and palygorskite minerals were detected in the bulk soil. Comparison of clay minerals samples in the bulk soil and rhizosphere showed that the trioctahedral chlorite transformed to hydroxy-interlayer vermiculite (HIV) in the rhizosphere soil. The presence of HIV was identified by an increase in the intensity ratio of the 10 and 14 angstrom peaks after K-saturation. In rhizospheric soils, the intensity of the 14 angstrom peak decreases in K-550ºC treatment. Furthermore, in the rhizospheric soils, a clear increase in the intensity of the 10 angstrom peak was observed from K-air dried to K-550ºC treatments which can be related to the presence of HIV which can be attributed to the changing conditions of the rhizosphere, including reducing pH and increasing the dissolved organic carbon and the activity of microorganisms. Comparison of diffractograms for clay fraction of rhizospheric soil with different contamination levels after cultivation showed that the type of minerals in contaminated levels was similar to non-contaminated conditions, but the amount of trioctahedral chlorite was the highest in higher contaminated soil. The peak intensity of 14 angstrom in potassium saturated sample heated at 550°C was lower in non-contaminated soil. Also, at the level of 10 mg kg-1 cadmium contamination, the chlorite peak had the highest intensity which indicates less chlorite was transformed to HIV in the contaminated soils.ConclusionsThe results showed that DOC in the rhizosphere soil was significantly higher than the bulk soil, whereas pH significantly decreased in the rhizosphere soil compared to the bulk soil. In both the rhizosphere and the bulk soils, increasing the contamination caused a decreasing trend in dissolved organic carbon. Mineralogical results of the rhizospheric and the bulk soils showed that trioctahedral chlorite was transformed to hydroxy-interlayer vermiculite (HIV). In addition, rhizosphere contamination reduced the chlorite transformation. The results suggest that soil contamination with a negative impact on plant activity and soil could even prevent the availability of nutrients from the clay minerals structure.
M. Molaei Arpnahi; M.H. Salehi; M. Karimian Egbal; Z. Mosleh
Abstract
Introduction: The most important factor in environmental degradation and pressure on ecological resources is rapid population growth combined with unsustainable exploitation of resources. Soil is one of the most important and worthful natural resources of environment. Land use change and deforestation ...
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Introduction: The most important factor in environmental degradation and pressure on ecological resources is rapid population growth combined with unsustainable exploitation of resources. Soil is one of the most important and worthful natural resources of environment. Land use change and deforestation decrease soil quality. Land use change also causes destruction of the evolved soils and decrease soil quality which result in permanent destruction of land fertility. Therefore, studying land use management effects on the soil quality has got an attention in recent years. Destroying the vegetation especially in the last 50 years resulted in important problems like soil erosion, land slide as well as increasing flood in the Bazoft area. In this area, degradation of the forests and their convert to other land uses like pasture, agriculture and urban or rural land use, occurs annually at high extent, in which make high damages to natural resources. In this study, the effect of land use change on soil quality indices in this area located at Chaharmahal-Va-Bakhtiari province was investigated.
Materials and Methods: In this research, four different managements with relatively similar conditions in terms of the influence of soil producing processes were chosen. Then, 10 composite samples from 0-30 cm depth of each land use (40 samples in total) were taken and different soil properties including soil texture, mean weight diameter of aggregates (MWD), porosity, bulk density, soil acidity, electrical conductivity and calcium carbonate equivalent were determined. One-way ANOVA was used to analyze the dataset. Tukey HSD test was applied to compare the means at the probability level of 5%. The first land use includes the natural forest with predominant cover of Iranian oak and the highest density and cover with the least human interference. Another land use is the degraded forest, caused by deforestation over the last 50 years. The third land use is the agricultural land which transformed from forest land use by deforestation in the last 50 years. The fourth land use is the walnut garden which established from agricultural land about 20 years ago.
Results and Discussion: The results showed that land use change from natural forest to other uses had a significant effect on most of the studied parameters. The percentage of particle size distribution was affected by different land uses, so that the percentage of clay was significantly higher in the land use of natural forest and walnut orchard than other land uses. The results also showed that the mean weight diameter of aggregates was influenced by the land use change (P <0.001). Factors like soil compaction due to livestock grazing and machinery traffic, agricultural operations and reduced biological activity increased the bulk density in all land uses compared with the forest land use. Deforestation also resulted in 6.92%, 12.05% and 14.16% porosity reduction in walnut orchard, agricultural land and deforestation, respectively. Changing management from farmland to walnut orchards also improved soil porosity by 6 percent. In the study area, the problem of changing vegetation, grazing, planting and other mismanagement increased soil pH in other land uses compared with the forest land use. The comparison of means showed that degraded forest and agriculture land uses had the highest rate of electrical conductivity which showed significant difference with natural forest land use and walnut orchard. Analysis of variance indicated that the land use had a significant effect on calcium carbonate equivalent at the probability level of 0.001. The comparisons also showed that the equivalent calcium carbonate content in agricultural land was higher than the other land uses, and there was no significant difference between walnut orchard and natural forest.
Conclusion: The results of the present study showed that the soil physical and chemical properties were significantly affected by land use change. Overall, it can be stated that the rate of changes in soil quality under human management and different utilization systems indicates failure in sustainable management of soil resources in the study area. Some characteristics such as soil particle size distribution percentage, soil porosity and calcium carbonate equivalent shows that there is no significant difference between walnut orchard and natural forest. However, the walnut orchards can be selected as the best management in areas where it is impossible to restore natural forests. Also, the need for stopping deforestation in Zagros ecosystem is highly recommended.
Anahid Salmanpour; Mohammad hasan Salehi; jahangard mohammadi
Abstract
Introduction: The heavy metal concentration in agricultural lands, due to the toxicity, persistence and their accumulation in the environment has become a major concern. Ophiolitic formations extend in southern part of central Iran and parallel to folds of the Zagros Mountains, is located in the north ...
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Introduction: The heavy metal concentration in agricultural lands, due to the toxicity, persistence and their accumulation in the environment has become a major concern. Ophiolitic formations extend in southern part of central Iran and parallel to folds of the Zagros Mountains, is located in the north of Neyriz town and in the west of Bakhtegan Lake. Rock weathering of these complexes forms sediments and soils with a large amount of Mn, Ni, Cr, Co, Mg and Fe. Laboratory analysis of Neyriz ophiolitic rocks indicates that they are a source of heavy metals as well, and may cause problems for the environment. However, there is no investigation in Neyriz area regarding contamination of the soils. The present study was conducted to assess soils pollution in Ghal-e Bahman area, 20 km from Neyriz which derived from ophiolitic formations of this area.
Materials and Methods: The study area located in the Ghal-e Bahman region, eastern part of Bakhtegan Lake. The soils of this region are affected from Neyriz ophiolite. In this region, three physiographic units including a hill, an alluvial fan and a lowland (playa) were separated. In each unit, some pedons were dug and classified according to American Soil Taxonomy. Soil samples were obtained from each genetic horizon and rock samples were also taken from ophiolitic formation. Then, chemical and physical properties were determined. Heavy metals were also extracted by nitric acid and amount of Cr, Ni, Co and Fe were calculated. Enrichment Factor (EF) and Geo-accumulation indices (Igeo) were also calculated and soils were classified according to their pollution level.
Results and Discussion: In general, soils on different landforms had different horizon properties and different classification. They are varied from a shallow, thin layer on hills to relative deep layer on lowland. These soils were classified in three different subgroups according to American Soil Taxonomy. Soils on ophiolitic hills classified as Lithic Torriothents because of a thin surface layer on a weathered bedrock. Soils developed on alluvial fan landform, with several alluvial subsurface horizons with different rock fragments percentage and size, was classified as Typic Torrifluvents; and the soils on lowland (Bakhtegan playa (was Gypsic Aquisalids because of salt and gypsum concentration in all layers and had redox color (chroma of less than 2) affected by high level of groundwater in the soil surface and subsurface layers.
The results showed that the amount of chromium with the average of 2200 mgkg-1, was 10 to 40 times higher than the Iran and Europe threshold levels (100 and 150 mgkg-1, respectively). The amount of nickel, with the average of 300 mgkg-1,were 10 fold higher than the threshold level and cobalt (19 mgkg-1) was lower than criteria defined by soils standards of Iran and Europe (40 mgkg-1).The amount of studied metals were the highest in ophiolitic hills, and playa soils were in second place in this respect. The amount of metals had a significant decrease in alluvial fan but didn’t drop under threshold level. The lowest amount of heavy metals in alluvial fan was probably because of the high percentage of sand, higher permeability and low soil water retention in all horizons. The negative significant correlation between the elements and sand also confirms this hypothesis. In addition, increasing elements at the depth of 70 cm of the soil in alluvial fan showed that land type (orchards) and long period of irrigation may cause leaching heavy metals from topsoil to the soil depth. However, no significance correlation was observed between the elements and soil organic carbon. The correlation coefficients between three elements revealed that all of them had the similar geologic origin and thus their spatial occurrence in soils can be attributed to the weathering of similar parent material.
Igeo showed an almost constant trend from ophiolitic hill (7.7-7.8) to alluvial fan (7.2-7.7) and a significant decrease in playa (3.9-6.2) for all metals. The variation of EF for nickel had an almost constant trend from ophiolitic hill (with the average of 0.6) to alluvial fan (with the average of 0.7) and a significant decrease in playa (with the average of 0.1). Also, a decreasing trend was observed from ophiolite hill (0.9 and 0.6 for chromium and cobalt, respectively) to alluvial fan (0.5 for both) and playa (0.3 and 0.1 for chromium and cobalt, respectively). A decreasing trend observed for indices can be due to the reduction of sediment transport processes and dilution effect of elements from hill to playa during the deposition and their formation .It seems that the EF index and the Igeo provide more useful information about hydrologic processes during formation of landform and development of soils than absolute values of heavy metals.
Conclusions: The present study showed that the amounts of chromium and nickel were higher than the threshold in studied soil. The soils derived from ophiolitic formation showed the highest values and the soils over alluvial fans had the lowest levels of heavy metals. Useful information was obtained from EF index and Igeo about the prominent geomorphic processes during landforms formation
Future studies should be focused on possible transfer of these elements into the groundwater and also trees of the orchards in Ghal-e Bahman region.
zohreh mosleh; Mohammad hasan Salehi; azam jafari; Abdolmohammad Mehnatkesh; Isa Esfandiarpoor Borujeni
Abstract
Introduction: There is a concern with assessment of land performance when used for specific purposes. Land evaluation analysis is considered as an interface between land resources and land use planning and management. However, the conventional soil surveys are usually not useful for providing quantitative ...
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Introduction: There is a concern with assessment of land performance when used for specific purposes. Land evaluation analysis is considered as an interface between land resources and land use planning and management. However, the conventional soil surveys are usually not useful for providing quantitative information about the spatial distribution of soil properties that are used in many environmental studies. Development of the computers and technology lead to digital and quantitative approaches have been developed. These new techniques rely on finding the relationships between soil and the auxiliary information that explain the soil forming factors or processes and finally predict soil patterns on the landscape. Different types of the machine learning approaches have been applied for digital soil mapping of soil classes, such as the logistic and multinomial logistic regressions, neural networks and classification trees. To our knowledge, most of the previous studiesapplied land suitability evaluation based on the conventional approach. Therefore, the main objective of this study was to assess the performance of digital mapping approaches for the qualitative land suitability evaluation in the Shahrekord plain of Chaharmahal-Va- Bakhtiari province.
Materials and Methods: An area in the Shahrekord plain of Chaharmahal-Va-Bakhtiari Province, Iran, across 32º13′ and 32º 23′N, and 50º 47′ and 51º 00′E was chosen. The soils in the study area have been formed on Quaternary shale and foliated clayey limestone deposits. Irrigated crops such as wheat, potato, maize and alfalfa are the main land uses in the area. According to the semi-detailed soil survey, 120 pedons with approximate distance of 750 m were excavated and soil samples were taken from different soil horizons. Soil physicochemical properties were determined. The average of soil properties was determined by considering the depth weighted coefficient up to 100 and 150 centimeters for annual and perennial crops, respectively. Qualitative land suitability evaluation for main crops of the area including wheat, maize, alfalfa and potato was determined by matching the site conditions (climatic, hydrology, vegetation and soil properties) with studied crop requirement tables presented by Givi (5). Land suitability classes were determined using parametric method. Land suitability classes reflect degree of suitability as S1 (suitable), S2 (moderately suitable), S3 (marginally suitable) and N (unsuitable). Different machine learning techniques, namely artificial neural networks (ANNs), boosted regression tree (BRT), random forest (RF) and multinomial logistic regression (MLR) were used to test the predictive power for mapping the land suitability evaluation. Terrain attributes, normalized difference vegetation index (NDVI), clay index, carbonate index, perpendicular vegetation index (PVI), geology map, existing soil map (1:50000 scale) and geomorphology map were used as auxiliary information. Finally, all of the environmental covariates were projected onto the same reference system (WGS 84 UTM 39 N) and resampled to 50 * 50 m since the soil samples were collected with approximate distance of 750 m (1:50,000 scale). According to the suggested resolutions for digital soil maps, the pixel size 50 *50 m fits to a 1:50,000 cartographic scale. Training the models was done with 80% of the data (i.e., 96 pedons) and their validation was tested by the remaining 20% of the dataset (i.e., 24 pedons) that were split randomly. The accuracy of the predicted soil classes was determined using error matrices and overall accuracy.
Results and Discussion: The results showed that climatic conditions are suitable (S1) for wheat and potato whereas the most important limiting factors for maize and alfalfa were the average of minimum temperature and average temperature, respectively. Results demonstratedthat among the studied models, random forest showed the highest performance to predict the land suitability classes and subclasses. However, different models had the same ability for prediction. In addition, the overall accuracy decreased from class to subclass for all of the crops. The terrain attributes and remote sensing indices (normalized difference vegetation index and perpendicular vegetation index) were the most important auxiliary information to predict the land suitability classes and subclasses.
Conclusion: Results suggest that the DSM approaches have enough accuracy for prediction of the land suitability classes that affecting land use management. Although digital mapping approaches increase our knowledgeabout the variation of soil properties, integrating the management of the sparse lands with different owners should be considered as the first step for optimum soil and land use management.
reza mohajer; MOHAMMAD HASSAN Salehi
Abstract
Introduction: Increasing demand for an international classification system as a unique language in soil science has caused development of different classification systems. Soil classification is a useful tool for understanding and managing soils. In recent decades, the role of human in soil formation ...
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Introduction: Increasing demand for an international classification system as a unique language in soil science has caused development of different classification systems. Soil classification is a useful tool for understanding and managing soils. In recent decades, the role of human in soil formation has become a matter of great concern among soil scientists. Human is now considered as a soil-forming factor and anthrosolization is recognized as a soil-forming process that consists of a collection of geomorphic and pedological processes resulting from human activities. Industrial developments, mines and their activities and intensive agriculture led to soil changes in urban areas. One of the important missions of soils classification is to identify important properties which have effect on management purposes. In recent years, the importance of human impact on soil properties considered in soil classification systems like American Soil Taxonomy (2014) and World Reference Base (2015) and some revisions and changes have been made in this regard. In this study, the efficiency of American Soil Taxonomy and WRB soil classification systems soils were compared to describe the pollution of soils to heavy metals in Lenjanat region of Isfahan, Iran.
Materials and Methods: Agricultural lands located in Lenjanat region of Isfahan province were selected as the study area. Lenjanat is an industrial region in which intensive agriculture surrounded by different industries like steel and cement making factories and lead mining. Agricultural lands which consisted of five soil map units (Khomeini Shahr, Nekooabad, Isfahan, Lenjan and Zayandehroud) were selected and 400 topsoil samples were randomly collected. Six soil profiles were excavated in each map unit (totally 30 soil profiles) and after describing soil, the classification of soils was determined in the field. Then, representative pedons were chosen for each unit and routine soil morphological, physical and chemical properties were determined using common methods. Finally, the soil profiles were classified according to criteria of Soil Taxonomy up to family level and (WRB) at the second level. The amount of heavy metals was studied in some agricultural crops of the region and livestock muscles in the region. Total Cd and Pb were extracted from the soil samples using concentrated HNO3. Cadmium and lead of plant samples were prepared according to the procedure of Dry-ashing. Heavy metals were extracted by 3 N HCl. The metal contents of soil and plant samples were determined by flame atomic absorption spectrometry (FAAS). Descriptive statistics including mean, variance, maximum, minimum, and coefficient of variation (CV) were calculated using STATISTICA 6.0 software.
Results and Discussion: According to WRB (2015) classification, the soils were classified as 3 reference groups: Cambisols, Gleysols and Calcisols. The soils were also categorized as Aridisols and Inceptisols in Soil Taxonomy system. In this study, the environmental standards based on Swiss Federal Office of Environmental, Forest and Landscape were used for the threshold values of heavy metals pollution in the soils (VBBo). The results also indicate that the amount of cadmium in most of the soil samples was higher than the threshold limit. The amount of lead in soils was below the threshold limit. The results also indicated that all the crops had a lead average higher than the maximum of tolerance. The average of lead in cow and sheep livestock was also above Iran and Europe Union’s permissible limit. Despite American soil taxonomy classification system in the last version has a class (Anthraltic, Anthraquic, Anthrodensic, Anthropic) to show human impacts on soils at family level, it could not show the contamination of soils to heavy metals. However, WRB soil classification system defined qualifier “toxic” (Anthrotoxic, Ecotoxic, Phytotoxic, Zootoxic) which can be used in these conditions. Both systems had serious shortcomings to show poor drained soils in this area. Defining the Aquids suborder for Aridiosols in American Soil Taxonomy and revision of the definition of Gleysols, Anthrosols and also aquic conditions in WRB soil classification system are highly recommended.
Conclusion: The results indicated that WRB soil classification system could explain the soils pollution and also their effects on human health for the studied soils. Definition of some quantitative sub qualifiers for toxic can be useful to improve the efficiency of WRB for classifying polluted soils. Incorporating some criteria for pollution hazards in American Soil Taxonomy should be considered in early future.
Materials and Methods: To find out the effect of geological feature on delineation of homogeneous regions, 73 hydrometric stations at North-East of Iran with arid and semi-arid climate covering an average of 29 years of record length were considered. Initially, all data were normalized. Watersheds were clustered in homogeneous regions adopting Fuzzy c-mean algorithm and two different scenarios, considering and not considering a criterion for geological feature. Three validation criteria for fuzzy clustering, Kwon, Xie-Beni, and Fukuyama-Sugeno, were used to learn the optimum cluster numbers. Homogeneity approval was done based on linear moment’s algorithm for both methods. We adopted 4 common distributions of three parameter log-Normal, generalized Pareto, generalized extreme value, and generalized logistic. Index flood was correlated to physiographic and geographic data for all regions separately. To model index flood, we considered different parameters of geographical and physiological features of all watersheds. These features should be easily-determined, as far as practical issues are concerned. Cumulative distribution functions for all regions were chosen through goodness of fit tests of Z and Kolmogorov-Smirnov.
Results and Discussion: Watersheds were clustered to 6 homogenous regions adopting Fuzzy c-mean algorithm, in which fuzziness parameter was 1.9, under the two different scenarios, considering and not considering a criterion for geological feature. Homogeneity was approved based on linear moment’s algorithm for both methods, although one discordant station with the lowest data was found. For the case with inclusion of genealogic feature, 3-parameter lognormal distribution was selected for all regions, which is a highly practical result. On the other hand, for not considering this feature there were no unique distribution for all regions, which fails for practical usages. As far as index flood estimation is concerned, a logarithmic model with 4 variables of average watershed slope, average altitude, watershed area, and the longest river of the watershed was found the best predicting equation to model average flood discharge. Determination coefficient for one of the regions was low. For this region, however, we merged this region to other regions so that reasonable determination coefficient was found; the resulting equation was used only for that specific region, however. By comparing the distributions of stations and also two evaluation statistics of median relative error and predicted discharge to estimated discharge ration corresponding to 5 different return periods (5, 10, 20, 50, and 100 years). Both perspectives showed acceptable results, and including geological feature was effective for flood frequency studies. With considering the geological feature for regionalization, Besides, Log normal 3 parameters distribution was found appropriate for all of the regions. From this point of view, geological feature was useful. Median of relative error was lower for small return periods and gradually increased as return period was increased. Median of relative error was between 0.21 to 00.45 percentages for the first method, while for the second method it varied between 0.21 to 0.49 percentages. These errors are quite smaller than those reported in literature under the same climatic region of arid and semi-arid. The probable reason may due to the fact that we made a satisfactory regionalization via fuzzy logic algorithm., We considered another mathematical criterion of “predicted discharge to the observed discharge”. The optimum range for this criterion is between 0.5 and 2. While under-estimation and over-estimation are found if this criterion is lower than 0.5 and higher than 2, respectively. Based on this premise, 75 to 95 percentages of stations were categorized as good estimation under the first method of analysis. On the other hand, 78 to 97 percentages of stations were considered good for the second approach.
zohreh mosleh; mohammad hassan salehi; azam jafari; Isa Esfandiarpoor Borujeni
Abstract
Introduction: Effective and sustainable soil management requires knowledge about the spatial patterns of soil variation and soil surveys are important and useful sources of data that can be used. Prior knowledge about the spatial distribution of the soils is the first essential step for this aim but ...
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Introduction: Effective and sustainable soil management requires knowledge about the spatial patterns of soil variation and soil surveys are important and useful sources of data that can be used. Prior knowledge about the spatial distribution of the soils is the first essential step for this aim but this requires the collection of large amounts of soil information. However, the conventional soil surveys are usually not useful for providing quantitative information about the spatial distribution of soil properties that are used in many environmental studies. Recently, by the rapid development of the computers and technology together with the availability of new types of remote sensing data and digital elevation models (DEMs), digital and quantitative approaches have been developed. These new techniques relies on finding the relationships between soil properties or classes and the auxiliary information that explain the soil forming factors or processes and finally predict soil patterns on the landscape. Different types of the machine learning approaches have been applied for digital soil mapping of soil classes, such as the logistic and multinomial logistic regressions, neural networks and classification trees. In reality, soils are physical outcomes of the interactions happening among the geology, climate, hydrology and geomorphic processes. Diversity is a way of measuring soil variation. Ibanez (9) first introduced ecological diversity indices as measures of diversity. Application of the diversity indices in soil science have considerably increased in recent years. Taxonomic diversity has been evaluated in the most previous researches whereas comparing the ability of different soil mapping approaches based on these indices was rarely considered. Therefore, the main objective of this study was to compare the ability of the conventional and digital soil maps to explain the soil variability using diversity indices in the Shahrekord plain of Chaharmahal-Va- Bakhtiari province.
Materials and Methods: The soils in the study area have been formed on Quaternary shale and foliated clayey limestone deposits. Irrigated crops such as wheat, barley and alfalfa are the main land uses in the area. According to the semi-detailed soil survey, 120 pedons with approximate distance of 750 m were excavated and described according to the “field book for describing and sampling soils”. Soil samples were taken from different genetic horizons and soil physicochemical properties were determined. Based on the pedons description and soil analytical data, pedons were classified according to the Soil Taxonomy (ST) up to subgroup level. Using aerial photo interpretation, geology map, google earth image and field observations primary soil map was created. With considering the taxonomic level, the representative pedons were determined and soil map was prepared. Multinomial logistic regression was used to predict soil classes at great group and subgroup levels. The map units that have the highest frequency were selected as indicator to calculate diversity indices in the conventional soil map at each taxonomic level. The selected map units were overlay to digital soil map and further diversity indices were calculated. Diversity indices including the Shannon’s diversity, evenness and richness index. In order to know whether the means of Shannon’s diversity for two approaches are significantly different, means comparison was done.
Results and Discussion: The results confirmed that the Shannon's diversity index was higher in the digital soil map than the conventional soil map for most soil map units. At great group and subgroup levels, a significant difference was observed for the Shannon's diversity index at 0.05 and 0.001 probability levels, respectively. Comparing the conventional and the digital soil maps showed the numbers of soil map units with significant difference regarding the Shannon's diversity index decreased from great group to the subgroup level. Although the conventional soil map did not show a good efficiency to explain the soil variability in this region considering more soil information to select the representative pedons at subgroup level in the conventional soil mapping could increase the ability of this approach.
Conclusion: A significant difference for the Shannon's diversity index between the conventional and the digital soil maps demonstrated that conventional soil mapping has not enough ability to explain the soil variability. It is recommended to test the effect of soil mapping approaches on explanation of the soil variability in other areas. Despite the deficiencies of traditional soil survey, it is still difficult to state about their replacement by digital methods.
nargess keyvani; Mohammad hasan Salehi; jahangard mohammadi; Abdolrahman Mohammadkhani
Abstract
Introduction: Soils form from the interplay of five main factors namely parent material, time, climate, relief (topography) and organisms. Topography is one of the local factors that has direct and indirect effects on soil formation, physical and chemical properties of soils. To understand the mutual ...
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Introduction: Soils form from the interplay of five main factors namely parent material, time, climate, relief (topography) and organisms. Topography is one of the local factors that has direct and indirect effects on soil formation, physical and chemical properties of soils. To understand the mutual relationship between topographic properties, soil properties and plant community (phytocoenosis), it is necessary to decide on the appropriate method for properly managing the soil resources. In addition to the soil properties, topography may affect the soil production indices as well. Soil production index and consequently its productivity will in turn affect the growth and fruiting. Insight about the pattern the spatial variability of soil properties can be used to manage the lands properly. This study was performed to investigate the spatial variability of soil properties regarding aspect and also the relationship of these changes with the quality and quantity of peach production in Saman region in Chaharmahal-Va-Bakhtiari province, Iran.
Materials and Methods: The study area contained 1.5 hectare of 200-hectare peach gerdens belong to BaghGostaran Company located in Saman, Chaharmahal-Va-Bakhtiari Province. The soil moisture and temperature regimes are xeric and mesic, respectively. 136 soil samples were collected from 0-30 and 30-60 cm depths. Two peach trees around the soil samples were also selected. Then, soil physical and chemical properties including soil texture, percentage of calcium carbonate equivalent, organic carbon, plant available potassium, phosphorous, iron and zinc, pH and electrical conductivity were determined and fruit properties including branch length and diameter in the current year, number of fruits, total yield, average of fruit weight, TSS, tissue strength, pH, acid and extract percentage were measured. Finally, the dataset were analyzed using Statistica 6.0 software. Analysis of spatial data was calculated via variogram and performed using Variowin, 2.2 software package. After determination of the best model, kriging maps of the soil and fruit properties were prepared by Surfer 8 software.
Results and Discussion: The statistical results revealed that among the soil properties, pH of the surface and subsurface horizons in both aspects had the lowest CV. Plant available phosphorous and iron showed the highest CV at surface and subsurface horizons of eastern aspect, respectively. Among the soil variables, plant available iron showed the highest CV for both horizons at western aspect. Regarding peach properties, the tissue strength showed the highest and pH showed the lowest variation in both slopes, respectively. The results of mean comparisons revealed that the soil of eastern slope has more clay percentage, silt, organic carbon, plant available potassium, phosphorous, and iron in comparison with western aspect. Peach yield was higher in eastern aspect than the western one. Correlation coefficient among soil and peach propertied did not show a similar trend for two aspects. Amount of clay and plant available potassium in subsurface horizon showed a positive significant correlation with yield in western and eastern aspects, respectivelty. Variography showed that all variables except pH of subsurface horizon have spatial structure. The pattern of spatial variability of the yield and the number of fruits was also approximately the same as that of clay particles and organic carbon, plant available potassium, phosphorous and iron in both depths. The spatial variability of the branch length and diameter in the current year was similar to the spatial variability of clay particles percentage and the plant available potassium. The results suggested the significant effect of soil properties, especially clay particles percentage and the plant available potassium on the performance and vegetative properties of peach. However, the peach qualitative properties showed no significant correlation with the soil properties.
Conclusion: The results suggest that the significant effect of aspect on the soil and fruit properties. It seems that the aspect caused the formation of soil with different properties. Significant differences observed among some soil properties including texture components, the amount of organic carbon and nutrients in both aspects. The trees on the eastern slope had higher yield due to having more organic carbon and nutrients and consequently higher soil quality, while the trees on the western slope had fruits with higher quality which may be due to the climatic factors such as receiving more light, or other soil properties like the mount of available nitrogen. More investigation is needed to understand the effect of NPK and iron fertilizers and climate properties on peach properties in the orchards of the area. The effect of climatic factors on the peach qualitative and quantitative characteristics should be investigated as well.
Mina Kiyani; Mohammad hasan Salehi; jahangard mohammadi; Abdolrahman Mohammadkhani
Abstract
Introduction: The spatial variability of soil properties and its importance in production is a matter-of-debate. Insight about the variability of soil properties as well as the yield of orchards is necessary to achieve higher productivity and better management. Orange is one of the most important export ...
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Introduction: The spatial variability of soil properties and its importance in production is a matter-of-debate. Insight about the variability of soil properties as well as the yield of orchards is necessary to achieve higher productivity and better management. Orange is one of the most important export products in our country and to sustainable production of this product, it is necessary to identify the factors affecting its growth. This study was performed to examine the statistical and geo-statistical relationship of some soil properties with the quantitative, qualitative and vegetative properties of Valencia orange in Kazerun area, Fars province.
Materials and methods: The study area contained 1 hectare (Valencia orange crop) of 205-hectare orchards of Rashnabad on the west of Kazerun, Fars province which is 860 meters above the sea level. 120 soil samples were collected from two depths of 0-40 cm and 40-80 cm (according to the root distribution) in order to investigate the statistical and geo-statistical relationship of some soil properties with the properties of Valencia orange. The sampling in the shade and with a minimum distance of one meter from the trunk of the tested tree was performed (It should be noted that orange trees have been planted as row planting with a distance of 5 meters from each other). In addition to the soil samples were collected for statistical studies from the depths 0-40 and 40-80 cm, the combined sampling of two trees that had less distance to the selected points was performed to measure the performance and quality of orange. It should be noted that all the Valencia trees, their age (about eight years) and management approach were similar. Soil samples were then transferred to the laboratory and air dried, the separately packed and passed through 2 mm sieve.Then, different soil and orange properties including soil texture, pH, EC, %OM, %CaCO3, solution potassium and available phosphorous, iron, zinc and manganese, branch length and branch diameter, trunk perimeter, trunk diameter and tree height, total soluble solids, acid percentage, Vitamin C, number of fruits,orange yield,average fruit weight and average fruit size were determined and the data set were analyzed using Statistica 6.0 software.Variograms of the data were drawn using variowin 2.2 and after determining the best fitted model, kriging maps of soil and fruit were prepared using Surfer9 software.
Results and Discussion: The results of correlation coefficient showed the significant and positive relationship between organic matter and available manganese of topsoil with total yield and number of fruits. According to the results of fitness of standard models to the empirical exponent change, all the properties had spatial structure. Soil properties including the percentage of clay, the percentage of organic matter, soluble potassium, phosphorous, available zinc and manganese in both depths in the eastern and south-eastern direction of the study area were higher than that of the others. These maps had the same spatial distribution pattern in terms of orange properties including the diameter and length of the current year branch, performance, number of fruits, average fruit size, acid percentage and total soluble solids.
Conclusion: The variability coefficient of soil and fruit properties did not show a consistent trend in the study. According to the correlation coefficients, in a few cases, a positive significance correlation was observed as an example, it can be referred to the positive significant correlation of orange yield with the organic matter and manganese in the depth of 0-40 cm. All the studied variables have spatial structure. Among the studied variables, the percentage of organic matter, clay particles percentage, soluble potassium, phosphorous, and available manganese in both depths showed the same spatial distribution pattern as that of the vegetative, qualitative and yield properties of orange including the total performance, fruit number, fruit size, the diameter and length of the current year branch. The proximity of the ranges of soil and fruit properties supports this result and is in line with the results of correlation coefficient. The results also showed that the spatial distribution and pattern of soil and crop variables may be different in a short distance with the same management. The study of the effect of NPK fertilizers on vegetative, qualitative and quantitative properties of orange in the region orchards is recommended. It is also suggested to study the effect of climatic factors on the orange qualitative properties.
zohreh mosleh; mohammad hassan salehi; azam jafari; Isa Esfandiarpoor Borujeni
Abstract
Introduction: Soil classification generally aims to establish a taxonomy based on breaking the soil continuum into homogeneous groups that can highlight the essential differences in soil properties and functions between classes.The two most widely used modern soil classification schemes are Soil Taxonomy ...
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Introduction: Soil classification generally aims to establish a taxonomy based on breaking the soil continuum into homogeneous groups that can highlight the essential differences in soil properties and functions between classes.The two most widely used modern soil classification schemes are Soil Taxonomy (ST) and World Reference Base for Soil Resources (WRB).With the development of computers and technology, digital and quantitative approaches have been developed. These new techniques that include the spatial prediction of soil properties or classes, relies on finding the relationships between soil and the auxiliary information that explain the soil forming factors or processes and finally predict soil patterns on the landscape. These approaches are commonly referred to as digital soil mapping (DSM) (14). A key component of any DSM mapping activity is the method used to define the relationship between soil observation and auxiliary information (4). Several types of machine learning approaches have been applied for digital soil mapping of soil classes, such as logistic and multinomial logistic regressions (10,12), random forests (15), neural networks (3,13) and classification trees (22,4). Many decisions about the soil use and management are based on the soil differences that cannot be captured by higher taxonomic levels (i.e., order, suborder and great group) (4). In low relief areas such as plains, it is expected that the soil forming factors are more homogenous and auxiliary information explaining soil forming factors may have low variation and cannot show the soil variability.
Materials and Methods: The study area is located in the Shahrekord plain of Chaharmahal-Va-Bakhtiari province. According tothe semi-detailed soil survey (16), 120 pedons with approximate distance of 750 m were excavated and described according to the “field book for describing and sampling soils” (19). Soil samples were taken from different genetic horizons, air dried and grounded. Soil physicochemical properties were determined. Based on the pedon description and soil analytical data, pedons were classified according to the ST (20) and WRB (11). Terrain attributes, remote sensing indices, geology, soil and geomorphology map were considered as auxiliary information. All of the auxiliary information were projected onto the same reference system (WGS 84 UTM 39N) and resampled to 50×50 m according to the suggested resolution for digital soil maps (14). Four modeling techniques (multinomial logistic regression (MLR), artificial neural networks (ANNs), boosted regression tree (BRT) and random forest (RF)) were used for each taxonomic level to identify the relationship between soil classes and auxiliary information in each classification system. The models were trained with 80 percent of the data (i.e., 96 pedons) and their validation was tested by remaining 20 percent of the dataset (i.e., 24 pedons) that split randomly. The accuracy of the predicted soil classes was determined by using overall accuracy and Brier score.For each classification system, the model with the highest OA and the lowest BS values were considered as the most accurate model for each taxonomic level.
Results and Discussion: The results confirmed that ST showedmore accessory soil properties compared to WRB. The ST described the cation-exchange activity, soil depth classes, temperature and moisture regime. The different models had the same ability for prediction of soil classes across all taxonomic levels based on ST. Among the studied models, MLR had the highest performance to predict soil classes based on WRB. For all the studied models and both classification system, OA values showed a decreasing trend with increasing the taxonomic levels. Predicted soil classes based on the ST had the higher accuracy. Different models selected different auxiliary information to predict soil classes. For most of the models and both classification systems, the terrain attributes were the most important auxiliary information at each taxonomic level.
Conclusion: Results demonstrated that although ST showed more accessory soil properties compared to WRB, the DSM approaches have not enough accuracy for prediction of the soil classes at lower taxonomic levels. More investigations are needed in this issue to make a firm conclusion whether DSM approaches are appropriate for prediction of soil classes at the levels that are important for soil management. Prediction accuracy of soil classes can be influenced by the target taxonomic level and classification system, soil spatial variability in the study area, soil diversity, sampling density and the type of auxiliary information.
shahrokh fatehi; jahangard mohammadi; Mohammad Hassan Salehi; aziz momeni; Norair Toomanian; Azam Jafari
Abstract
Introduction: Spatial scale is a major concept in many sciences concerned with human activities and physical, chemical and biological processes occurring at the earth’s surface. Many environmental problems such as the impact of climate change on ecosystems, food, water and soil security requires not ...
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Introduction: Spatial scale is a major concept in many sciences concerned with human activities and physical, chemical and biological processes occurring at the earth’s surface. Many environmental problems such as the impact of climate change on ecosystems, food, water and soil security requires not only an understanding of how processes operates at different scales and how they can be linked across scales but also gathering more information at finer spatial resolution. This paper presents results of different downscaling techniques taking soil organic matter data as one of the main and basic environmental piece of information in Mereksubcatchment (covered about 24000 ha) located in Kermanshah province. Techniques include direct model and point sampling under generalized linear model, regression tree and artificial neural networks. Model performances with respect to different indices were compared.
Materials and Methods: legacy soil data is used in this research, 320 observation points were randomly selected. Soil samples were collected from 0-30 cm of the soil surface layer in 2008 year. After preliminary data processing and point pattern analysis, spatial structure information of organic carbon determined using variography. Then, the support point data were converted to block support of 50 m by using block ordinary kriging. Covariates obtained from three resources including digital elevation model, TM Landsat imagery and legacy polygon maps. 23 relief parameters were derived from digital elevation model with 10m × 10m grid-cell resolution. Environmental information obtained from Landsat imagery included, clay index, normalized difference vegetation index, grain size index. The image data were re-sampled from its original spatial resolution of 30*30m to resolution of 10m*10m. Geomorphology, lithology and land use maps were also included in modelling process as categorical auxiliary variables. All auxiliary variables aggregated to 50*50 grid resolutions using mean filtering. In this study Direct and point sampling downscaling techniques were used under different statistical and data mining algorithms, including generalized linear models, regression trees and artificial neural networks. The direct approach was implemented here using generalized linear models, regression trees and artificial neural networks in following three steps, (i) creating the spatial resolution of 50m*50m averaged over 10m*10m grid resolution environmental variables within each coarse grid resolution, (ii) establishing relationships between these coarse grid resolutions of 50m*50m environmental variables and soil organic carbon using GLMs, regression tree and neural networks and (iii) using parameter values gained in step 2 in combination with the original 10m*10mgrid resolution environmental variables to produce predictions of soil organic carbon with10m*10m grid resolution. In point sampling approach, within each coarse resolution (50m*50m), a fixed number of fine grid resolution (10m*10m) were randomly selected to calibrate models at high resolution. In this study, 5 fine grid resolutions (20% fine grid cell within each coarse grid cell) randomlywere sampled at. Then, each selected point overlied on an underlying fine-resolution grid and recorded its environmental variables and averaged fine grid resolution (10m*10m) within their corresponding coarse grid resolution (50m*50m). To calibrate model parameters, these averaged environmental variables were used. The calibrated parameters applied to fine-resolution environmental data in order to predict soil organic carbon at spatial resolution of 10m*10m. The prediction accuracy of the resulting soil organic carbon maps was evaluated using a K-fold validation approach. For this purpose, the entire dataset was divided into calibration (n = 240) and validation (n = 80) datasets four times at random. Prediction of soil organic carbon using calibration datasets and their validation was conducted for each split, and the average validation indices are reported here. The obtained values of the observed and predicted SOC were interpreted by calculating Adjusted R2 and the root mean square error (RMSE).
Results and Discussion: Point pattern analysis showed the sampling design is, generally, representative relative to geographical space .A semi-variogram was used to drive the spatial structure information of soil organic carbon. We used an exponential model to map soil organic carbon using block kriging. Grid resolution block kriging map was 50m*50m. Since the distribution of organic carbon variable and covariates were normal or close to normal for run generalized linear models selected Gaussian families and identity link function. The validation results of this model in point sampling was slightly (Adjusted R2=0.57 and RMSE=0.22) better than the direct method (Adjusted R2 =0.47 and RMSE=0.26).The results of modelling using regression tree in point sampling approach (Adjusted R2 =0.57and RMSE=0.22) is very close to the direct method (Adjusted R2 =0.57 and RMSE=0.23).In implementation of neural networks, the combination of the number of neurons and learning rate for direct downscaling method were obtained 10 and 0.10, respectively and for point sampling downscaling method were, 20 and 0.1 The results of validation obtained from the implementation of this model in point sampling approach (Adjusted R2 =0.45 and RMSE=0.27) is very close to the direct method (Adjusted R2 =0.47 and RMSE=0.28).Validation results indicated that in both downscaling approaches, regression tree (Adjusted R2=0.57, root mean square root (RMSE) =0.22-0.23) has higher accuracy and efficiency better than generalized linear models (Adjusted R2=0.49-0.57, RMSE=0.22-0.26) and neural network (Adjusted R2=0.45-0.47, RMSE=0.27-0.28).
Conclusion: In general, the results showed that the efficiency and accuracy of the sampling point approach is slightly better than the direct approach. Validation results indicated that in both downscaling approaches, regression tree has higher accuracy and performed better than neural network and generalized linear models. However, it is required to perform more research on the different ways of downscaling digital soil maps in the future.
Anahid Salmanpour; Mohammad hasan Salehi; jahangard mohammadi
Abstract
Introduction: Soil organic matter is considered as an indicator of soil quality, because of its role on the stability of soil structure, water holding capacity, microbial activity, storage and release of nutrients. Although changes and trends of organic matter are assessed on the basis of organic carbon, ...
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Introduction: Soil organic matter is considered as an indicator of soil quality, because of its role on the stability of soil structure, water holding capacity, microbial activity, storage and release of nutrients. Although changes and trends of organic matter are assessed on the basis of organic carbon, it responds slowly to changes of soil management. Therefore, identifying sensitive components of organic carbon such as carbon labile lead to better understanding of the effect of land use change and soil management on soil quality.
The main components of sustainable agriculture in arid and semi-arid regions are the amount of water; and soil and water salinity. Water deficit and irrigation with saline water are important limiting factors for cropping and result in adverse effects on soil properties and soil quality. Soil carbon changes is a function of addition of plant debris and removal of it from soil by its decomposition. If the amount of organic carbon significantly reduced due to the degradation of the soil physical and chemical properties and soil quality, agricultural production will face serious problems. To this end, this study was done to evaluate soil quality using soil labile carbon and soil carbon management indices in some agricultural lands of Neyriz area, Fars province, Iran.
Materials and Methods: Five fields were selected in two regions, Dehfazel and Tal-e-mahtabi, consisted of irrigated wheat and barley with different amount of irrigation water and water salinity levels. Three farms were located in Dehfazel and two farms in Tal-e-Mahtabi region. In each farm, three points were randomly selected and soil samples were collected from 0-40 cm of the surface layer. Plant samples were taken from a 1x1 square meter and grain crop yield was calculated per hectare. Water samples were obtained in each region from the wells at the last irrigation. Physical and chemical characteristics of the soil and water samples were determined. Soil labile carbon and carbon management indices also were calculated. In carbon management index calculation, a reference farm was chosen at the vicinity of two regions which were abandoned for years. Statistical analysis like analysis of variance and correlation coefficients was done using SPSS 16.0 software.
Results and discussion: Results revealed that the highest crop yield (with the average of 5.7 tonh-1) was related to the farm which was irrigated with saline water (water EC 8.1 dSm-1) with enough water crop requirement. As this farm received the highest amount of water (with thw volume of 1039.5 mm), it seems that much more irrigation water probably provided the leaching fraction and prevented salt accumulation in the the root zone. Therefore, water salinity could not be a limiting factor for crop growth in this farm. This farm also had the highest content of organic carbon but it didn’t have the highest labile organic carbon and carbon management index (the value of 161.5).
On the other hand, the farm containing the highest labile carbon and carbon management indices (the value of 284), didn’t have the highest crop yield (with the average of 2.6 tonha-1) although it has recieved enough amount of water as well as non-saline irrigation water (water EC 2.28 dSm-1). The more carbon management index represents the higher soil carbon lability and soil quality and it demonstrates that soil have better condition for living microorganisms. Therefore, it can be concluded from the results that the higher soil quality not necessarily resulted in higher crop yield. Many researchers reported that better soil properties are not always resulted in the higher productivity.
Taking everything into account, carbon management index is not related to crop yield, but since it indirectly is related to microbial activity and calculated easily, it could be a useful indicator for rapid assessment of soil quality. Meanwhile, this indicator may be associated with qualitative properties of the crops such as grain protein, which is recommended for future investigations.
Conclusion: Results showed that labile organic carbon is more sensitive to crop management than total organic carbon. Amount of irrigation water and its salinity can influence the labile organic carbon content and thus the soil quality even in the fields with the same crop yield and management. Although, a higher amount of carbon management index does not result in higher yield production, it may be associated with crop quality attributes. More investigation is needed to give better idea in this regard.
N. Namazi; M.H. Salehi; jahangard mohammadi
Abstract
Introduction: Heavy metals released from stationaryand mobile origins can be transported in water, air and soil and can be even absorbed by plants, animals and human bodies. Trace elements are currently of great environmental concern. Nowadays, one of the most important environmental problems is pollution ...
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Introduction: Heavy metals released from stationaryand mobile origins can be transported in water, air and soil and can be even absorbed by plants, animals and human bodies. Trace elements are currently of great environmental concern. Nowadays, one of the most important environmental problems is pollution of agricultural soils occurs by heavy metals due to human activities. Atmospheric subsidence is one of the main sources of these elements which can result from industrial activities, fertilizers, sewage sludge, compost and pesticides. Heavy metals mapping of the atmosphere dusts indicates the status of pollution and its intensity in industrial regions. This information can also be used as a guideline for better management and pollution control. This study was performed to investigate the spatial and temporal availability of heavy metals in atmospheric dusts of Lenjanat region, Isfahan where agricultural land is extensively surrounded by industrial activities like steel making factory (Esfahan), cement making factory (Sepahan and Esfahan) and Bamalead mine.
Materials and Methods: Sampling was done from 60 points with the same altitude(three to six meters from the ground)and their location was recorded by GPS. Glass traps (1×1 m2) covered by plastic mesh (2 × 2 cmvents) were used to trap the dusts for four seasons of the year. Collected dust samples were passed through a 200 mm mesh screen size and the total weight of the dusts and the heavy metals content of Cd, Zn, Cu, Ni and Pbwere determined(with HNO3 60%). Data analysis was performed using Statistical 6.0 software. Analysis of spatial data via variogram was calculated and performed using Variowin, 2.2 software packages. After determination of the best fitting model, kriged maps of the total concentration of heavy metals were prepared by Surfer 8 software.
Results and Discussion: The average concentrations of Zn, Pb and Cd in dust in most parts of the study area were much higher than the soil standard values and the maximum value was around the Zn and Pb mines. However, the concentrations of Cu and Ni were higher than the standard values only in some parts of the area. Comparison of the averages for different seasons showed that in most cases there were significant differences between the concentrations of the various elements. A significant correlation was observed among Pb, Zn and Cd concentrations in all seasons indicating similar origin of these elements. The average dust deposition rate in the summer was more than the other seasons. Moreover, in all seasons except the spring and fall, there was a significant difference between the average dust deposition rates. Kriged maps of Zn, Cd, and Pb showed that the maximum concentrations of these elements occurred near the Pb and Zn Bama mine and the concentrations of these elements decreased with increasingthe distance from the mine. The contamination was lower in the spring and higher in the summer. Based on the kriged maps, samplingfrom one seasononly can be used to assess the trend of element contamination but if the objective focuses on absolute heavy metals values, season strongly influences the results and interpretation from one season can be misleading. The determination of the amounts of dust and their heavy metal contents in different wind directions is recommended to identify the source of dusts and heavy metals.
Conclusion: Results showed a significant difference among the mean values of dusts for the different seasons except for the spring and fall. The mean values of Pb and Cd in all seasons and Zn except for the spring were higher than the threshold values reported for the soils. A significant correlation was observed among the concentrations of some elements which may suggest their same origin. Interpretation of kriged maps showed that zinc and lead Bamamine in the region could be the main source of the contamination of Zn, Pb and Cd. According to quantitative calculations, a low accordance was observed for the pattern and the values of each element in different seasons. This can be related to the wind velocity and its direction, intensity of industrial and mining activities and also the amount of humidity of soil and air during the year. Interpretation of atmospheric data based on one season may be considerably misleading.
Keywords: Atmosphericdusts, Heavy metals, Season
R. Karimi; M.H. Salehi; Z. Mosleh
Abstract
Nowadays, changing the rangelands to agriculture and garden is common. To investigate the impact of land use change on the soils type and clay mineralogy, four land uses including rangeland with poor vegetation, agricultural land, new and old apple orchards were selected in Safashahr area, Fars province. ...
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Nowadays, changing the rangelands to agriculture and garden is common. To investigate the impact of land use change on the soils type and clay mineralogy, four land uses including rangeland with poor vegetation, agricultural land, new and old apple orchards were selected in Safashahr area, Fars province. In each land use, three soil profiles were excavated and described and one profile was considered as representative. After required physical and chemical analyses, they were classified according to Soil Taxonomy (ST) and the World Reference Base for Soil Resources (WRB). Selected surface and subsurface samples were also collected for clay mineralogy studies. Results showed that changing land use did not have significant effect on soil type and clay minerals and all soils consist of mica, chlorite, smectite, kaolinite and mixed layer minerals. Results demonstrated that ST is more efficient compared to WRB to classify the studied soils.
sh. jorkesh; Mohammad hasan Salehi; I. Esfandiarpour
Abstract
One of the most important soil contaminants are heavy metals. Chemical analysis of the samples can be used to evaluate the contamination but these methods are expensive and time consuming. Thus, for rapid evaluation, other techniques such as magnetic susceptibility are considered. The aim of this study ...
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One of the most important soil contaminants are heavy metals. Chemical analysis of the samples can be used to evaluate the contamination but these methods are expensive and time consuming. Thus, for rapid evaluation, other techniques such as magnetic susceptibility are considered. The aim of this study was to compare the spatial distribution of magnetic susceptibilityand cadmium, lead, nickel and copper in soil series of Isfahan, Khomeinishahr and Zayanderood in Lenjan at region, Isfahan province. Estimation of heavy metals via pedotransfer functions using magnetic susceptibility was also investigated. Total concentration of Cd, Pb, Ni and Cu in soil samples was determines and the magnetic susceptibility of the samples was also measured. Results showed magnetic susceptibility does not have high accuracy for estimation of heavy metals contents in the soils of this region. On the other hand, similar trends of continuous maps for heavy metals and magnetic susceptibility suggest that magnetic susceptibility can be a good indicator for trend of soil contamination in this area.
nargess hoseinzadeh; Mohammad hasan Salehi; jahangard mohammadi
Abstract
Now a day, performing soil surveys by minimum time and budget as well as enough accuracy is one of the soil scientists' interests. The present study was investigated to study the effect of sampling density on statistical and geostatistical accuracy of estimation for some of soil properties in Shahrekord ...
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Now a day, performing soil surveys by minimum time and budget as well as enough accuracy is one of the soil scientists' interests. The present study was investigated to study the effect of sampling density on statistical and geostatistical accuracy of estimation for some of soil properties in Shahrekord plain. For this purpose, 240 soil samples (horizon A) with 125 m interval were collected. Then, the physical and chemical analysis included bulk density, soil texture, volume percent gravel, percentage of calcium carbonate equivalent, organic matter, pH and electrical conductivity were determined. The second (120 samples) and third (60 samples) sampling densities were randomly selected the first samplings (240 samples) by considering uniform distribution throughout the region. Results showed that there are no significant differences among the studied soil properties for three sampling intervals. Also, by reducing the number of samples, no regular increase or decrease was observed for coefficient of variation, mean estimation error and root mean square error. The cross validation showed that mean estimation error was close to zero and the root mean square error was low which indicate the acceptable accuracy of estimations. Visual and quantitative interpretation of kriging maps showed high accordance for three sampling densities. Therefore, semi-detailed soil surveys can be replaced for detailed ones which allow saving time and budget.
M. Bagheri-Bodaghabadi; M.H. Salehi; J. Mohammadi; N. Toomanian; I. Esfandiarpour Borujeni
Abstract
Abstract
Limitations of traditional (conventional) soil surveys and improvement of information technology have lead soil surveyors to invent new methods which are generally called digital soil mapping (DSM). The aim of these methods is the prediction of soil classes or soil properties based on easily-available ...
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Abstract
Limitations of traditional (conventional) soil surveys and improvement of information technology have lead soil surveyors to invent new methods which are generally called digital soil mapping (DSM). The aim of these methods is the prediction of soil classes or soil properties based on easily-available or measuring environmental variables. The objective of this investigation is to study the efficiency of digital elevation model and its derivates for soil mapping using Soli-Land Inference Model (SoLIM) and credibility of its results in the Borujen area, Chaharmahal-va-Bakhtiari province. Eighteen terrain attributes including height, slope (angle), aspect, curvature, minimum curvature, maximum curvature, tangent curvature, profile curvature, planform curvature, flow direction, flow accumulation, direct radiation, diffuse duration, diffuse radiation, area solar radiation, power index, sediment index and wetness index, were derived from the DEM. These derivates as well as three dominant soil subgroups and seven soil families of the region were used to construct the input data matrix of the model. Results showed an accuracy of 65% and 40% for interpolation and extrapolation of the soils at subgroup level, respectively. The accuracy decreased to half when soil families were considered for credibility of the model. Because of using crisp limitations in American Soil Taxonomy system, assessing soil survey results can be miss-leading partially, whereas using SoLIM model shows well the reality of the soils in the field.
Keywords: SoLIM, Fuzzy logic, Digital soil mapping, Digital elevation model
F. Noruzi Fard; M.H. Salehi; H. Khademi; A.R. Davoudian Dehkordi
Abstract
چکیده
ماده مادری از مهمترین فاکتورهای خاک سازی در مناطق خشک و نیمهخشک محسوب میگردد. هدف از این مطالعه، بررسی تأثیر مواد مادری آذرین، دگرگونی و رسوبی بـر روی برخی ...
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چکیده
ماده مادری از مهمترین فاکتورهای خاک سازی در مناطق خشک و نیمهخشک محسوب میگردد. هدف از این مطالعه، بررسی تأثیر مواد مادری آذرین، دگرگونی و رسوبی بـر روی برخی از ویژگیهای فیزیکی، شیمیـایی، کانیشناسی و ردهبندی خاکها در شمال استان چهارمحال و بختیاری است. پس از انتخاب هفت نوع سنگ مادری شامل گرانیت، بازالت، سنگ آهک، شیل، میکـاشیست، گنیس و آمفیبـولیت، بر روی هر یک از آنها سه خاکرخ، حفر و تشریح گردید و یک خاکرخ از هر سنگ بستر به عنوان خاکرخ شاهد برای تجزیههای فیزیکی، شیمیایی و کانیشناسی رس موجود در سنگ بستر و افقهای خاک انتخاب گردید. نتایج نشان داد ویژگیهای فیزیکوشیمیایی خاک، کانیشناسی و ردهبندی خاکها به میزان قابل ملاحظهای توسط مواد مادری، کنترل میشود. اغلب خاکها تنها دارای دو افق A و BC بودند و در راسته انتیسولز طبقهبندی گردیدند و تنها خاکهای موجود بر روی شیل و گنیس، به دلیل وجود افق مشخصه B، در راسته اینسپتیسولز ردهبندی شدند. تفاوت در ردهبندی خاکهای موجود در یک راسته نیز از سطح زیر گروه یا فامیل خاک مشاهده شد که نشاندهنده لزوم ردهبندی خاک در سطوح پایین برای اهداف مدیریتی است. نتایج کانیشناسی بخش رس نشان داد در همه خاکها و ماده مادری آنها کانیهای کلریت، کائولینیت، کوارتز و میکا (بجز افق سطحی خاک تشکیل شده بر روی سنگ بازالت و نمونه سنگ شیل) وجود دارد و منشأ آنها در خاکها توارثی است. منشأ اسمکتیت در خاکهای حاصل از گرانیت و بازالت، پدوژنیکی و در خاک حاصل از سنگ آهک، توارثی تشخیص داده شد در حالی که در خاک به وجود آمده از سنگ گنیس، دو منشاء توارثی و پدوژنیکی بهنظر میرسد. وجود ورمیکولیت در خاک به وجود آمده از آمفیبولیت ناشی از به ارث رسیدن از ماده مادری و در خاکهای تشکیل شده بر روی میکاشیست و شیل بهدلیل تشکیل در محیط خاک میباشد.
واژه های کلیدی: ماده مادری، ویژگیهای فیزیکی و شیمیایی خاک، کانی شناسی رس، رده بندی
F. Khayamim; H. Khademi; M.H. Salehi
Abstract
Abstract
The association between Neotyphodium spp. endophytes and cool-season grasses, particularly tall fescue (Festuca arundinacea, Schreb), represents a widespread type of mutualism in nature. Numerous researches were performed about positive effect of symbiosis on plant resistance to different stresses ...
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Abstract
The association between Neotyphodium spp. endophytes and cool-season grasses, particularly tall fescue (Festuca arundinacea, Schreb), represents a widespread type of mutualism in nature. Numerous researches were performed about positive effect of symbiosis on plant resistance to different stresses but the role of symbiosis on nutrients uptake particularly potassium uptake and K-bearing mineral transformation is not well recognized. The objective of this research was to investigate the effect of endophyte-tall fescue symbiosis on the transformation of clay-sized micaceous minerals. A pot experiment under green house conditions was carried out in a completely randomized design with factorial combinations and three replicates. The culture medium was a mixture of quartz sand (as filling material) and phlogopite or muscovite. Tall fescue 75B genotype either infected by the natural endophyte Neotyphodium or non-infected isoline was chosen for cultivation. Pots were irrigated with distilled water and complete or K-free nutrient solutions during a period of 140 days. At the end of the experiment, shoots and roots were harvested. Plant samples were prepared with dry ashing method and their K concentration was determined with flame photometer. The clay-sized particles in each pot were mineralogically studied using an X-ray diffractometer. The results showed the vermiculitization of phlogopite under both nutrient solutions conditions, but with a much higher rate in pots treated with K-free nutrient solution. In addition to vermiculite, smectite and chlorite were also detected as newly formed minerals in phlogopite amended pots. Also, a very weak vermiculitization was observed in muscovite treated media. Under the K-free nutrient solution and in phlogopite amended treatments, the 1.4/1.0 nm peak ratio for endophyte infected plants was 4 times greater than that under non-infected plants. Such a significant difference in phlogopite vermiculitization is attributed to endophyte symbiosis and its positive effects on the type and quantity of tall fescue roots secretions. A significant decrease in pH values under the rhizosphere of infected plants further confirmed this hypothesis.
Keywords: Endophyte fungi, Phlogopite, Muscovite, Vermiculite, Mineral transformation
I. Esfandiarpour Borujeni; N. Toomanian; M.H. Salehi; J. Mohammadi
Abstract
Abstract
Geopedology is a systematic approach of geomorphic analysis for soil mapping which focuses the field operation mainly on sample area. The purpose of this study is to determine the credibility of generalization of the results of geopedological approach for similar landforms in the Borujen region, ...
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Abstract
Geopedology is a systematic approach of geomorphic analysis for soil mapping which focuses the field operation mainly on sample area. The purpose of this study is to determine the credibility of generalization of the results of geopedological approach for similar landforms in the Borujen region, using diversity and similarity indices in a soil taxonomic hierarchical structure. After a primary interpretation of the study area on air photos (1:20000 scale), the largest delineation of Pi111 geomorphic unit was selected and 19 pedons with an approximate 125 m interval were excavated, described and sampled. The credibility of generalizing the results of the geopedological approach for the studied unit was tested by comparison with 15 pedons in a similar unit outside the sample area, named the validation area. Results showed that as the category decreases from order to soil family, the Shannon's diversity index increases in both the sample and validation areas. A significant difference at 95% confidence level was observed for pedodiversity mean values of two areas at family level. Soil diversity also remains high through the soil taxonomic hierarchy when we change the understanding level and consider the horizon/genetic diversity in both the sample and validation areas. Jaccard index and proportional similarity also indicated that up to subgroup level, the geopedological approach can be used for generalization of the similar geomorphic unit results and it does not have a good efficiency for lower soil taxonomic levels (family and series). Therefore, the use of landform phases and also phases of soil families and/or series for each of landform phases is recommended to increase the accuracy of geopedological results.
Key words: Geopedology, Pedodiversity, Similarity index, Sample area, Validation area
H. Afshar; M.H. Salehi; J. Mohammadi; A. Mehnatkesh
Abstract
Abstract
The quality of soil maps depends upon their ability to show the soils variability. Thus, the accuracy of the maps used for crop recommendations is due to the accuracy of soil maps. This study was performed to investigate the amount of soil properties and crop yield spatial variability in S ...
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Abstract
The quality of soil maps depends upon their ability to show the soils variability. Thus, the accuracy of the maps used for crop recommendations is due to the accuracy of soil maps. This study was performed to investigate the amount of soil properties and crop yield spatial variability in S 2 and S3 units of a semi-detailed quantitative suitability map (1:50000 scale) for irrigated wheat in Shahr-e-Kian area, Chaharmahal-Va-Bakhtiari province. Eighty soil samples were collected in each land unit at 0-30 cm depth using multi-scale sampling method to determine available P, K, total N, %O.M., %CaCO3 equivalent, soil texture and particle size distribution, EC and pH. A 0.5×0.5 m plot of wheat was harvested at each of 160 sites previously sampled to determine crop biomass, 1000 seeds weight and harvest index. The highest CV was related to available potassium (47.43 for S2 and 46.46 for S3 units, respectively) and the lowest one was related to pH (1.07 for S2 and 0.925 for S3 units, respectively). Variography showed a good spatial structure for all variables in both land units. Ranges for variograms were from 17.75 for N to 61.06 m for EC in S2 unit and from 17.47 for P to 62.93 m for 1000 seeds weight in S3 unit. Kriging maps showed high spatial variability of soil properties as well as biomass, wheat yield and harvest index within two land units. This indicates that suitability maps have not enough credibility for precision agriculture. Using information of all pedons as well as representative pedons in land units and combining the information of suitability maps with geostatistical data can be a choice way to improve the accuracy and quality of land suitability maps.
Keywords: Kriging, Precision agriculture, Soil properties, Spatial variability, Suitability map, Wheat yield
