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Limited information is available on the distribution and origin of palygorskite in soils developed on Tertiary sediments as the major soil parent materials in central Iran and other Middle Eastern countries. The objectives of this study were to determine the distribution and origin of palygorskite in soils developed on Tertiary sediments, and to identify the major soil properties that influence palygorskite distribution in the soils studied. Sixteen soil profiles developed on Paleocene, Eocene, Oligocene, Oligocene-Miocene, Miocene and Pliocene sediments were studied by X-ray diffraction analysis, transmission electron microscope, and scanning electron microscopy. Physicochemical characteristics of the soils and sediments including particle size distribution, pH, electrical conductivity, organic carbon, gypsum, carbonates, and soluble Si, Ca and Mg were determined. The principal component analysis was used to establish the relationships between palygorskite and the physicochemical characteristics of the soils studied. Results showed that clay fraction of all the soils in the study area was dominated by palygorskite. The highest amount of palygorskite was found in horizons where simultaneous accumulation of both carbonates and gypsum occurred. Limited amount of palygorskite was found in salic and calcic horizons. Palygorskite seemed to be of eolian origin in the surface horizon of all the soils. Using principal component analysis, the soluble Mg/Ca ratio, pH, soluble Si and gypsum contents were identified as the most important factors affecting the distribution and genesis of palygorskite in the soils studied. Results might suggest the neoformation of palygorskite by precipitation from solutions in which evaporation fluxes were very high. However, palygorskite in soils developed on Tertiary sediments in central Iran seems to be of both inherited and pedogenic origins.

A study was made to determine the influence of pasture degradation on soil quality indicators that included physical, chemical, biological and micromorphological attributes, along the hillslope positions in Chaharmahal and Bakhtiari province, western Iran. Soil samples from different slope positions were collected from 0 to 30 cm depth for physical and chemical properties and from 0 to 15 cm depth for biological properties at two adjacent sites in the two ecosystems: natural pasture and cultivated land. Soil quality indicators including bulk density, mean weight diameter, soil organic carbon (SOC), particulate organic material (POM) in aggregate fractions, total nitrogen, available potassium, available phosphorus, cation exchange capacity, soil microbial respiration (SMR) and microbial biomass C and N were determined. The results showed that SOC decreased cultivation from 1.09 to 0.77 % following pasture degradation. The POM decreased by about 19.35 % in cultivated soils when compared to natural pasture; also, SMR and microbial biomass C and N decreased significantly following pasture degradation. Furthermore, aggregate stability and pore spaces decreased, and bulk density increased in the cultivated soils. Overall, our results showed that long-term cultivation following pasture degradation led to a decline in soil quality in all selected slope positions at the site studied in the semiarid region.

Magnetic susceptibility of loess–paleosol sequences is frequently used for paleoclimatic and paleoenvironmental studies. A penultimate loess–paleosol (Tappeh Salam section) from northeastern Iran was studied to determine i) morphologic, sedimentologic and magnetic characteristics of the section, ii) the effect of high amount of carbonates and gypsum on the magnetic susceptibility, and iii) if any recognizable relationship between magnetic susceptibility and paleoenvironmental conditions during periods of soil formation and loess deposition existed. The bulk magnetic susceptibility (χlfbulk) of genetic horizons was measured. To eliminate the effect of gypsum and carbonates, the minerogenic magnetic susceptibility (χlfminero) was calculated. Based on morphological characteristics, five distinct parts were recognized. Part 1 and 4 are composed of unaltered loess deposits with easily visible gypsum crystals. Part 2 includes a series of Bw, By and Bk horizons that ends to a last interglacial paleosol with a Btk horizon in part 3. At the base of the section, because of its extremely hard consistency, part 5 has an abrupt boundary. The χlfbulk values of different layers of the horizons change from 40.9 × 10− 8 m3 kg− 1 in the weakly developed part 1 to 75.6 × 10− 8 m3 kg− 1 in the Btk horizon. The amount of gypsum plus carbonates is 13.6–40.9%, making the interpretation of χlfbulk difficult. The χlfminero makes the difference clearer through the section. The χlfminero of part 1 is 108.9 × 10− 8 m3 kg− 1. This unexpectedly high value may be expressed by anthropogenic addition of magnetic particles. The χlfminero of Btk horizon exceeds 103 × 10− 8 m3 kg− 1 showing the effect of accumulation of iron oxides during warm and humid climate of the last interglacial period. The 70 × 10− 8 m3 kg− 1 value for χlfminero in part 4 can be attributed to parent materials. Part 5 has the lowest χlfminero of 50 × 10− 8 m3 kg− 1. Hydromorphic conditions in part 5 has induced the decomposition of iron oxide, resulting in a decline in magnetic susceptibility. The results of this study show the effectiveness of magnetic susceptibility properties for the interpretation of paleopedological and paleoenvironmental conditions of loess–paleosol sequence in northeastern Iran. It should be noted that in the arid regions, to avoid misinterpretation, the effect of high amount of gypsum and carbonates must be taken into account, by minerogenic magnetic susceptibility calculation.

The objective of this study was to explore the slope position and land use change effects on the variability in magnetic susceptibility and 137Cs inventory as the soil redistribution indicators in a hilly semiarid calcareous area in Iran. The selected study area is located in a hilly region with pasture and cultivation land use of Fereydunshahr, Isfahan Province in west-central Iran. In the two mentioned dominant ecosystems, four slope positions including summit, shoulder, backslope and footslope were identified and in each land use and slope position, three cores were selected to collect 72 soil samples from three depths (0–10, 10–20, 20–30 cm) in an area of 15 × 15 cm. Additional 28 soil samples were collected from the reference site for soil loss and deposition calculations by using the Cs-137 measurement. The results of the study with the use of the Cs-137 technique showed that the average soil loss in the pasture land (46.4 t ha− 1 yr− 1) was significantly (p < 0.05) lower than the average soil loss in the cultivated land (80.4 t ha− 1 yr− 1). The highest soil loss in both land uses was obtained in the shoulder position, 60.1 and 84.4 t ha− 1 yr− 1, respectively, for the pasture and cultivated lands. Moreover, the highest rates of soil deposition was observed in a footslope position in both land uses and they were 34 and 32.4 t ha− 1 yr− 1 for the pasture and cultivated lands, respectively. Magnetic susceptibility was significantly (p < 0.05) greater in pasture (χlf = 41.51 × 10− 8 m3/kg) than in the cultivated land (χlf = 34.90 × 10− 8 m3/kg). The pasture land with a lower soil loss rate, indicated significantly higher magnetic susceptibility in all landform positions as compared to that in the cultivated land. The results of the correlation analysis showed that among the studied soil physico-chemical properties, χlf (r = 0.83, p < 0.01) in the pasture land had the highest correlation with the Cs-137 inventory. Throughout the non-linear regression analysis, χlf was introduced for relating soil parameters and the cesium inventory explained 68% and 79% of the total variability of 137Cs in the pasture and cultivated lands, respectively. The results implied that the variability in the magnetic susceptibility within the hillslope is consistent with the variation of the Cs-inventory; and the results thus demonstrate the slope and land use effects on soil redistribution.

Soil depth generally varies in mountainous regions in rather complex ways. Conventional soil survey methods for evaluating the soil depth in mountainous and hilly regions require a lot of time, effort and consequently relatively large budget to perform. This study was conducted to explore the relationships between soil depth and topographic attributes in a hilly region in western Iran. For this, one hundred sampling points were selected using randomly stratified methodology, and considering all geomorphic surfaces including summit, shoulder, backslope, footslope and toeslope; and soil depth was actually measured. Eleven primary and secondary topographic attributes were derived from the digital elevation model (DEM) at the study area. The result of multiple linear regression indicated that slope, wetness index, catchment area and sediment transport index, which were included in the model, could explain about 76 % of total variability in soil depth at the selected site. This proposed approach may be applicable to other hilly regions in the semi-arid areas at a larger scale.

This study was conducted to use soil and topographic attributes to predict the activity of three soil enzymes: L-asparaginase, L-glutaminase, and urease by artificial neural networks (ANNs) and multiple linear regression (MLR) approaches in a hilly region of central Iran. A total of surface (0–10 cm depth) soil samples were collected from the site under pasture. Sampling points were chosen in a stratified random manner from geomorphic surfaces, including summit, shoulder, backslope, footslope, and toeslope at the site. MLR and feed-forward back-propagation of ANNs were employed to develop models to predict soil enzymes activity (SEA). Results of the study showed that MLR models explained 37%–61%, and ANN models explained 96%–98% of the variability in the three SEA at the site studied. Overall, the results indicated that the ANN performed better in predicting the SEA than did MLR. Sensitivity analysis showed that topographic parameters as the easily accessible auxiliary variables were the most imp...

In order to contribute to the understanding of carbonate enrichment and clay illuviation in loess-derived soils of subhumid to humid regions, the development of soils was studied along a climate gradient with xeric and udic soil moisture regimes (SMR) and thermic and mesic soil temperature regimes (STR), respectively, in the Golestan Province, Northeastern Iran. Six representative pedons along a climate gradient were investigated. Soils were classified mainly as Hapludalfs and Haploxeralfs. Stability of the geomorphic surface under forest vegetation associated with high leaching conditions has provided appropriate conditions for decalcification followed by clay migration through the profile and formation of argillic horizons in all the studied soils. Clay content of the Bt horizons, soil organic carbon concentration of the A horizons, and depth of the Bk horizons increased significantly with increasing precipitation and decreasing temperature. There was a considerable decrease in silt content with soil development. The main pedofeatures observed in the Bt horizons were clay coatings and decalcified zones. Nodules, coatings and hypocoatings were the main calcitic pedofeatures observed in the Bk horizons. Occurrence and preservation of clay coatings were more pronounced in the udic regions with illite and vermiculite as the dominant clay minerals. Type of clay minerals, shrink/swell properties, and precipitation rate are factors affecting the abundance and preservation of clay coatings. In the strongly developed horizons of the udic SMR, the occurrence of vermiculite clay minerals could reduce the shrink/swell potential and increase the amount of clay coatings. The presence of crystallitic b-fabrics and the high carbonate contents (CaCO 3 ) in the lower horizons (Bk) were mainly related to decalcification processes under descending water flow in the overlying horizons.

The study was conducted to investigate the effects of slope gradient and land use change on soil structural stability, and soil organic carbon (SOC) and total nitrogen (TN) pools in aggregate-size fractions in western Iran. Three land uses in the selected site were natural forest (NF), disturbed forest (DF) and cultivated land (CL); and three classes of slope gradient (0–10%, S1; 10–30%, S2; and 30–50%, S3) were used as a basis for soil sampling. The results showed that DF and CL treatments significantly decreased soil structural stability indices in the three slope classes. The highest percentages of macro-aggregates (i.e. 2.00–4.75 mm) and meso-aggregates (0.25–2.00 mm) were found in the lowest slope class (S1) which was related to high SOC stock in this position. The highest percentage of macro-aggregates was observed in the NF soil; but the highest percentages of micro-aggregates (0.053–0.25 mm) were observed in the CL treatment. Micromorphological observations confirmed that topsoil under natural forest mainly consisted of highly-porous crumb microstructure, excremental pedo-features or passage features, which are indicators of enhanced SOC and biological activity. The lowest values of SOC and TN were observed at the steep slope class (S3) presumably coincided with accelerated soil erosion. Overall, enhanced aggregation and aggregate-associated organic carbon pools were observed in the forest soils on the steep slopes indicating the importance of land management on C sequestration in natural environments.

Surface soil shear strength can be a useful dynamic index for soil erodibility and thus a measure of soil resistance to water erosion. In this study, we evaluated the predictive capabilities of artificial neural networks (ANNs) and an adaptive neuro-fuzzy inference system (ANFIS) in estimating soil shear strength from measured particle size distribution (clay and fine sand), calcium carbonate equivalent (CCE), soil organic matter (SOM), and normalized difference vegetation index (NDVI). The results showed that the ANN model was more feasible in predicting the soil shear strength than the ANFIS model. The root mean square error (RMSE), mean estimation error (MEE), and correlation coefficient (R) between the measured soil shear strength and the estimated values using the ANN model were 0.05, 0.01, and 0.86, respectively. In ANFIS analysis, the RMSE was 0.08 and a lower correlation coefficient of 0.60 was obtained in comparison with the ANN model. Furthermore, the ANN and ANFIS models were more accurate in predicting the soil shear strength than was the conventional regression model. Results indicate that the ANN model might be superior in determining the relationships between index properties and soil shear strength.

Summary The main objectives of this study were to compare binary logistic regression as an indirect approach and multinomial logistic regression as a direct approach to produce soil class maps in the Zarand region of southeast Iran. With indirect prediction, the occurrence of relevant diagnostic horizons was first mapped, and subsequently, various maps were combined for a pixel-wise classification by combining the presence or absence of diagnostic horizons. In direct prediction, the dependent variable was the great group itself, so the probability distribution of the great soil groups was directly predicted. Among the predictors, the geomorphology map was identified as an important tool for digital soil mapping approaches as it helped to increase the accuracy. The results of prediction showed larger mean probability values for each great soil group in the areas actually covered by the great soil groups compared with other areas, indicating the reliability of the prediction. In most predictions, the global purity was slightly better than the actual purity for the models; however, both models provided poor predictions for Haplocambids and Calcigypsids. The results showed that soils with better prediction were those much influenced by topographical and geomorphological characteristics and soils with very poor accuracy of prediction were only slightly influenced by topographical and geomorphological characteristics. An advantage of the indirect method is that it gives insight into the causes of errors in prediction at the scale of diagnostic horizons, which helps in the selection of better covariates.

No comprehensive study has yet been conducted to determine the chronostratigraphic distribution of palygorskite in the Tertiary sediments of Iran. Thirty sediment samples of different Tertiary epochs were taken, based on the field observations and geological maps. The clay fraction of samples was then investigated by X-ray diffraction (XRD), transmission and scanning electron microscopy (TEM and SEM), and inductively coupled plasma mass spectrometry (ICP-MS). Results showed that sediments of the Miocene and Pliocene had large amounts of palygorskite whereas no trace of this mineral was found in the sediments from the Palaeocene, Eocene and Oligocene. Geochemical analyses revealed that sediments younger than the Oligocene had greater amounts of soluble Mg and H4SiO4and a higher pH than those of the Palaeocene and Eocene. The stability diagram of the smectite-palygorskite system suggests that smectite is unstable and transforms to palygorskite in Neogene sediments. The SEM micrographs showed palygorskite as interwoven fibrous mats, coatings, pore-fillings and pore-bridging material in Neogene sediments. This textural evidence suggests a direct chemical precipitation of palygorskite by dissolution of silicates under the alkaline conditions. The results also suggest that geochemical conditions in the Early Tertiary era, represented by deep-sea conditions in central Iran, were not apparently favourable for palygoskite formation until the Late Oligocene.

Anthropogenic activities have caused the accumulation of heavy metals in the soil environment. Pollution of the soils significantly reduces environmental quality and affects human health. In many recent studies, magnetic susceptibility measurements have been used for pollution monitoring. The objective of this research was to determine the spatial variability of magnetic properties and selected heavy metals and the effect of land use on their variability in the surface soils of the Isfahan region, Central Iran. A total of 158 composite surface (0–5 cm) samples of calcareous soils were collected from an area of about 700 km 2 , located along a cross-border transect from Isfahan City to a steel plant, covering urban, industrial, agricultural, and uncultivated land uses. Concentrations of copper (Cu), zinc (Zn), lead (Pb), manganese (Mn), iron (Fe), nickel (Ni), chromium (Cr), and cobalt (Co) and magnetic parameters, magnetic susceptibility at low frequency (χlf), natural remanent magnetization (NRM), saturation isothermal remanent magnetization (SIRM), and isothermal remanent magnetization at the field of 100 mT (IRM 100mT ) and the backfield of 100 mT (IRM- 100mT ), were measured in all the soil samples. Results showed that magnetic susceptibility in the urban and industrial land topsoils (0–5 cm) samples was significantly higher than that in the agricultural and uncultivated land soils in the study area. Concentrations of Cu, Zn, Pb, Mn, and Fe were positively correlated with magnetic properties (χlf, IRM 100mT , SIRM, IRM- 100mT , and NRM), which could be attributed to their inputs from traffic emissions and industrial activities at the study sites. Ni and Cr concentrations showed significant negative correlations with magnetic properties. No significant correlation was found between Co concentration and magnetic parameters. The Tomlinson pollution load index (PLI) showed significant correlation with the magnetic properties (χlf, IRM 100mT , SIRM, IRM- 100mT , and NRM). The spatial distribution of the selected heavy metals and χlf in the study area suggested that activities at the urban and industrial land sites caused greater pollution as compared to that at the study sites of other land uses. The concentrations of Cu and Zn seemed to have been affected by anthropogenic sources, whereas Ni, Cr, and Co were mainly controlled by natural sources in the study area. Moreover, the concentrations of soil Pb and Fe in the study area could be affected by both lithologic and anthropogenic sources. The magnetic parameters appeared to be a proxy measure for the degree of heavy metal contamination and could be a potential method for the detection and mapping of contaminated soils.

This study was conducted to explore the effects of topography and land use changes on particulate organic carbon (POC), particulate total nitrogen (PTN), organic carbon (OC) and total nitrogen (TN) associated with different size primary particle fractions in hilly regions of western Iran. Three popular land uses in the selected site including natural forest (NF), disturbed forest (DF) and cultivated land (CL) and three slope gradients (0-10 %, S1, 10-30 %, S2, and 30-50%, S3) were employed as the basis of soil sampling. A total of 99 soil samples were taken from the 0-10 cm surface layer in the whole studied hilly region studied. The results showed that the POC in the forest land use in all slope gradients was considerably more than the deforested and cultivated lands and the highest value was observed at NF-S1 treatment with 9.13%. The values of PTN were significantly higher in the forest land use and in the down slopes (0.5%) than in the deforested and cultivated counterparts and steep slopes (0.09%) except for the CL land use. The C:N ratios in POC fraction were around 17-18 in the forest land and around 23 in the cultivated land. In forest land, the silt-associated OC was highest among the primary particles. The enrichment factor of SOC, EC,was the highest for POC. For the primary particles, EC of both primary fractions of silt and clay showed following trend for selected land uses and slope gradients: CL> DF> NF and S3 > S2> S1. Slope gradient of landscape significantly affected the OC and TN contents associated with the silt and clay particles, whereas higher OC and TN contents were observed in lower positions and the lowest value was measured in the steep slopes. Overall, the results showed that native forest land improves soil organic carbon storage and can reduce the carbon emission and soil erosion especially in the mountainous regions with high rainfall in west of Iran.

This study was conducted to evaluate the weathering intensity of the major soils developed on igneous rocks in semiarid region of northwestern Iran. Eight parent materials were selected including monzodiorite , alkali granite , granodiorite, syenite , pyroxene diorite , hornblend e andesite , pyroxene andesite , and dacite . Representative soil profiles were described and soil samples were collected and analyzed for selected chemical and physical properties and total concentrations of major elements and Zr, V, Ti and Y. Bulk densities as well as Ti, Zr and V concentrations were used to estimate the strain factors and mass balance equations were used to quantify the net result of pedogenic weathering, i.e. elemental loss and gain. The results of clay content and pedogenic iron variability as well as index of compositional variability (ICV), chemical index of alteration (CIA) and, A-CN-K and MFW ternary plots showed that the soils developed on volcanic rocks (hornblende andesite> pyroxene andesite> dacite) were more weathered than those on the plutonic parent rocks (alkali granite, granodiorite, monzodiorite, syenite, pyroxene diorite) . The results of mass balance calculations based on the strain factors revealed that the Ca and Na depleted during weathering progress mostly from plagioclase grains. In the semiarid regions Ca is precipitated as pedogenic calcite in the soil horizons. K and Mg depletion is less than Ca and Na especially in the profiles on the hornblende andesite with the highest clay and LOI content. The results of this study clearly suggest that the behavior of K and Mg during the weathering can not only be explained by the disintegration of the primary minerals, since they are fixed on the secondary clay minerals. Iron did not change in the soils compared to the parent material and was precipitated as the pedogenic iron and conserved in the soil horizons. Overall, the results on the weathering indicators and major elements mass balance enrichment/depletion in the study area confirmed that the soil profiles developed on volcanic rocks are more weathered than those on the plutonic igneous rocks.

Sustainable land resource management depends on the good assessment and planning of current landscapes. This may be possible with application of multidisciplinary researches, as this study presented a multidisciplinary approach in a spatial database frame work using Geographic Information System. �Agroecological zones� concept is used to integrating and characterizing homogenous spatial units. This approach combine theme layers include of available water resources, climate, terrain and soil conditions, associated with land use and settlement patterns. Climatic indices layers, including of growing degree days, aridity index, length of growing period and freezing period were created using the correlation between climatic parameter and digital elevation model. Using this approach the Borujen watershed was divided in 28 �agroecological zones� which defined 3 landscapes or agricultural regions. The most important constraints for developing agriculture in landscape I has topographic, climatic and soil constrains, landscape II has topographic and soil constrains and landscape III has the some limitations of soil. Landscape I and II are much less attractive from an agricultural perspective. Landscape III is suitable for agriculture but, the potential for rainfed cropping system is limited by a lack of growing period during which neither temperature nor moisture is limiting to plant production. In general, the case study of the Borujen watershed indicated that this approach can be used for different scales and adaptive to the particular planning.

Heavy metals’ origin, accumulation, and distribution in soil have been the focus of much attention by many researchers. The objective of this study was to recognize the sources of heavy metals in surface soils in Hamadan Province in western Iran using multivariate geostatistical techniques. A total of 263 surface (0–10 cm) soil samples and 18 rock samples from major parent materials were collected. Cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) contents of the samples were determined. Selected soil physical and chemical characteristics were also measured. A multivariate geostatistical analysis was performed to identify the common source of heavy metals. The quantities of Co, Cr, and Ni were found to be associated with parent rocks, corresponding to the first factor termed the “lithologic component.” The second factor was mainly attributed to Cu, which also comprised the first and third factors, indicating a mixed source both from lithologic and anthropogenic inputs. Zn and ...

Limited information is available about the use of magnetic susceptibility property to determine soil redistribution in hilly areas of the semi-arid regions. This study was conducted to evaluate the use of magnetic properties to determine soil redistribution along a hill slope following deforestation. The study area is located in the Quaternary hilly region of Lordegan district in west Iran. Ten transects were established in two land uses that included natural Querqus forested and cultivated lands. Soil samples were collected at different positions along the slope and magnetic properties (χlf, χhf, SIRM, ARM, and χfd) and selected physico-chemical properties were determined. The results (based on the χfd, SIRM/ARM) showed that the magnetic susceptibly in the calcareous materials is pre-dominantly derived during the pedogenic processes and the superparamagnetic particles which were transported to lower positions of hill slope following deforestation. The results confirmed that this methodology could be applied for monitoring soil redistribution along the slope in calcareous hilly areas in the semi-arid regions.

In this study artificial neural network (ANN) models were designed to predict the biomass and grain yield of barley from soil properties; and the performance of ANN models was compared with earlier tested statistical models based on multivariate regression. Barley yield data and surface soil samples (0–30 cm depth) were collected from 1 m2 plots at 112 selected points in the arid region of northern Iran. ANN yield models gave higher coefficient of determination and lower root mean square error compared to the multivariate regression, indicating that ANN is a more powerful tool than multivariate regression. Sensitivity analysis showed that soil electrical conductivity, sodium absorption ratio, pH, total nitrogen, available phosphorus, and organic matter consistently influenced barley biomass and grain yield. A comparison of the two methods to identify the most important factors indicated that while in the ANN analysis, soil organic matter (SOM) was included among the most important factors; SOM was exclude...

Recently methods dealing with magnetometry have been proposed as a proper proxy for assessing the heavy metal pollution of soils. A total of 113 topsoil samples were collected from public parks and green strips along the rim of roads with high-density traffic within the city of Isfahan, central Iran. The magnetic susceptibility (χ) of the collected soil samples was measured at both low and high frequency (χlf and χhf) using the Bartington MS2 dual frequency sensor. As, Cd, Cr, Ba, Cu, Mn, Pb, Zn, Sr and V concentrations were measured in the all collected soil samples. Significant correlations were found between Zn and Cu (0.85) and between Zn and Pb (0.84). The χfd value of urban topsoil varied from 0.45% to 7.7%. Low mean value of χfd indicated that the magnetic properties of the samples are predominately contributed by multi-domain grains, rather than by super-paramagnetic particles. Lead, Cu, Zn, and Ba showed positive significant correlations with magnetic susceptibility, but As, Sr, Cd, Mn, Cr and V, had no significant correlation with the magnetic susceptibility. There was a significant correlation between pollution load index (PLI) and χlf. PLI was computed to evaluate the soil environmental quality of selected heavy metals. Moreover, the results of multiple regression analysis between χlf and heavy metal concentrations indicated the LnPb, V and LnCu could explain approximately 54% of the total variability of χlf in the study area. These results indicate the potential of the magnetometric methods to evaluate the heavy metal pollution of soils.

We show with the results of a study conducted in the Hamadan Province, Iran as to how the use of composite sampling for estimating mean zinc concentration in the soil can help reduce analytical costs by reducing the number of analysis required. We also introduce post-stratification methodology in the composition step to take advantage of possible spatial dispersion. We speculate that the zinc concentration value depends on the sample location, we first stratified the sample set and then composite units from different strata randomly. The results of a simulation study show that the use of this approach not only reduces the total costs but also increases the precision of the estimator.

The spatial pattern of soil redistribution rate was investigated using cesium-137 ((137)Cs) within a cultivated complex hillslope in western Iran. The relationship between soil redistribution rate and soil organic carbon and total nitrogen pattern were studied using co-regionalization analysis. Ninety-one soil cores were sampled for (137)Cs, total nitrogen, and soil organic carbon measurements. The simplified mass balance model estimated a gross erosion rate of 29.8 t ha(-1) yr(-1) and a net soil deposition rate of 21.8 t ha(-1) yr(-1); hence, a net soil loss rate of 8 t ha(-1) yr(-1). This magnitude of soil erosion rate is higher than the acceptable rate in semiarid regions. Co-regionalization analysis and co-dispersive coefficients among the selected variables showed that only a small fraction of the variability in total nitrogen and soil organic carbon could be explained by soil redistribution and that the remaining might be the result of different management practices by local farmers.

Terrain attributes and soil properties are the major parameters to be considered for sustainable agricultural productivity and landscape management in dry farming. The objectives of this study were to predict the biomass, grain yield, and grain protein in wheat grown in hilly regions using an artificial neural network model and to identify the most important topographic attributes and soil properties affecting the variability of the wheat-yield components under rainfed conditions in the semiarid and hilly regions of western Iran. Wheat-yield data and surface-soil samples (0–30 cm depth) were collected from 1-m2 plots at 100 selected points. The sampling points were chosen in a stratified random manner on given geomorphic surfaces including summit, shoulder, backslope, footslope, and toeslope at the site. Primary and secondary terrain attributes were calculated using the digital elevation model. Selected soil physical and chemical properties were measured for the collected soil samples. Prediction...

Conversion of natural land resources into croplands, which is triggered by the rapid population growth, causes serious soil degradation. A loess hillslope located in eastern Golestan province of Iran was selected to study the role of deforestation and slope position on soil quality attributes. Surface (0–30 cm) and subsurface (30–60 cm) soil samples were taken from five slope positions (summit, SU, shoulder, SH, backslope, BS, footslope, FS and toeslope, TS) of forest (FO) and adjacent deforested cultivated land (DEF) in a factorial trial with completely randomized design. Ten pedons were also investigated and undisturbed soil samples were taken from different horizons for micromorphological studies. The texture of the original loess is silt loam. The soil textural class varies from silty clay loam in FO to silt loam in DEF, mainly due to the loss of finer particles as a result of soil erosion followed by deforestation and long-term cultivation. Mean weight diameter (MWD) of aggregates decreased following deforestation (0.88 mm compared to 1.49 mm in FO), as a result of considerable losses of organic carbon (OC) and breakdown of aggregates. Bulk density (BD) increased and soil infiltration rate decreased by about 50% in DEF. Reduction of annual organic matter input to soil as a result of deforestation and also rapid oxidation of organic matter in DEF were responsible for a significant decrease (>70%) in OC and total nitrogen (TN). Soil microbial respiration (SMR) also decreased significantly, following deforestation. Carbon, and N contents and population of fungi were significantly higher in all hillslope positions of the FO than the DEF. Changes in soil quality attributes were not significant in different slope positions of FO, which might be related to the stability of forest landscape. Effect of different slope positions on soil quality attributes was more pronounced in the DEF. The SH and BS were found as the most susceptible positions to erosion in DEF. Soils of the FO were mainly classified as Alfisols and Mollisols with evidences for clay illuviation compared to the weakly developed Inceptisols formed in the DEF. Micromorphological investigations revealed that the FO soils had strong granular and crumb microstructure with a high porosity indicating the presence of high amount of organic matter. The high microbial and faunal activity was confirmed through the presence of excremental pedofeatures in the topsoil of the FO. Lower organic matter and consequently microbial activity in the topsoil of the DEF have resulted in the massive microstructure with little porosity.

Understanding the variability of soil properties and their effects on crop yield is a critical component of site-specific management systems. The objective of this study was to employ factor and multiple regression analyses to determine major soil physical and chemical properties that influence barely biomass and grain yield within a field in the arid region of northern Iran. For this purpose, soil samples and crop-yield data were collected from 108 sites, at regular intervals (20 30 m) in a 5.6 ha field. Soil samples were analysed for total nitrogen (TN), available phosphorus (Pava), available potassium (Kava), cation-exchange capacity(CEC), electrical conductivity (EC), pH, mean weight diameter of aggregates (MWD), water-stable aggregates (WSA), field capacity volumetric (FC), available water-holding capacity (AWHC), bulk density (BD), and calcium carbonate equivalent (CCE). Results of the factor analysis, followed by regression of biomass and grain yield of barley with soil properties, showed that the regression equations developed accounted for 78 and 73% of the total variance in biomass and grain yield, respectively. Study of covariance analysis among soil variables using factor analysis indicated that some of the variation measured could be grouped to indicate a number of underlying common factors influencing barley biomass and grain yields. These common factors were salinity and sodicity, soil fertility, and water availability. The most effective soil variables to barley production in the study area identified as EC, SAR, pH, TN, Pava, AWHC, and FC. In this study, factor analysis was effective to identify the groups of correlated soil variables that were significantly correlated with the within field variability in the yield of the barley crop. Our results also suggest that the approach can be applied to other crops under similar soil and agroclimatic conditions.

A comparison study was carried out with the purpose of verifying when the adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), generalized linear model (GLM), and multiple linear regression (MLR) models are appropriate for prediction of soil wet aggregate stability (as quantified by the mean weight diameter, MWD) in a highly mountainous watershed (Bazoft watershed, southwestern Iran). Three different sets of easily available properties were used as inputs. The first set (denoted as SP) consisted of soil properties including clay content, calcium carbonate equivalent, and soil organic matter content. The second set (denoted as TVA) included topographic attributes (slope and aspect) and the normalized difference vegetation index (NDVI). The third set (denoted as STV) was a combination of soil properties, slope, and NDVI. The ANN and ANFIS models predicted MWD more accurately than the GLM and MLR models. Estimation of MWD using TVA data set resulted in the lowest model efficiency values. The observed model efficiency values for the developed MLR, GLM, ANN, and ANFIS models using the SP data set were 60.76, 62.98, 77.68 and 77.15, respectively. Adding slope and NDVI to soil data (i.e. STV data set) improved the predictions of all four methods. The obtained correlation coefficient values between the predicted and measured MWD for the developed MLR, GLM, ANN, and ANFIS models using STV data set were 0.24, 0.35, 0.84 and 0.73, respectively. In conclusion, the ANN and ANFIS models showed greater potential in predicting soil aggregate stability from soil and site characteristics, whereas linear regression methods did not perform well., Catena, 111, ISSN:0341-8162, ISSN:1872-6887

Erosion is a natural process, but it has been dramatically increased by human activities; and this adversely influences soil productivity and environmental quality. For quantification of soil erosion, several techniques including the use of Cs-137 have been employed. This study was conducted to explore the relationships of Cs-137 inventory with magnetic properties in calcareous soils in western Iran. Ten transects were selected in the hilly region in Chelgerd district of Iran. Soil samples from 0 to 30 and 30-50 cm depths were collected from fifty points to determine Cs-137 inventory, magnetic measures and selected physico-chemical properties (in total there were 100 soil samples). The results showed that simple mass balance model (SMBM) estimated a gross erosion rate of 29.6 t ha(-1) yr(-1) and a net soil deposition of 21.8 t ha(-1) yr(-1); hence, a net soil loss of 9.6 t ha(-1) yr(-1) and a sediment delivery ratio of 31.4%. Simple linear regression and non-linear regression analysis showed that mass magnetic susceptibility (χ(lf)) explained only 33.64% and 45% of variability in Cs-137 in the transects studied. The results of multiple linear regression analysis of (137)Cs with magnetic parameters and physico-chemical properties indicated that extractable potassium and χ(lf) explained approximately 61% of the total variability in (137)Cs in the area studied. Overall, the results suggest that further research is needed for the use of magnetic characteristics as an alternative technique in place Cs-137 methodology for calcareous soils.

Concern over global problems induced by rising CO2 has prompted attention on the role of forests and pastures as carbon ‘storage’ because forests and pastures store a large amount of carbon in vegetation biomass and soil. Soil organic matter (SOM) plays a critical role in soil quality and has the potential to cost-effectively mitigate the detrimental effects of rising atmospheric CO2 and other greenhouse gas emissions that cause global warming and climate change(Causarano-Medina, 2006). SOM, an important source of plant nutrients is itself influenced by land use, soil type, parent material, time, climate and vegetation (Loveland &Webb, 2003). Important climatic factors influencing SOM include rainfall and temperature. Within the same isotherm, the SOM content increases with increase in rainfall regime. For the same isohyet, the SOM content