aliasghar jafarzadeh

Determining the soil moisture and thermal regimes, is an important subject in agroclimatology and soil management. Considering the time-consuming process of in situ soil measurements, a pedoclimate modeling approach using Newhall models was applied. The mean monthly precipitation and temperature of 52 metrological stations across East Azerbaijan province, northeast of Iran during a 30 years period (1991-2021) were obtained and used for Pedoclimate zoning of the study area by Thiessen method. Trend analysis of the two climatic variables by Mann-Kendall test confirmed a significant increase in the annual mean temperature (Z= +3.18) and a non-significant decrease in the annual mean precipitation (Z=-0.56). According to pedoclimate modeling of different regions, ranked based on covered area, the soils of the province have Aridic and Xeric moisture regimes as well as Mesic, Thermic, and Frigid thermal regimes, respectively. Assessing the prepared maps showed that the northwestern and western regions of the province have drier and hotter pedoclimate conditions than other regions. The largest pedoclimate zone of the province is the Weak Aridic-Mesic class and the Dry Xeric-Frigid has the smallest area. Comparing the generated maps with older ones indicated changes in the extent of pedoclimates and different soil classes over study decades, which might be attributed to climate change in the region. In general, the findings of this study, would be useful in recognition pedoclimates, soil classification and adjusting cropping pattern to adapt with climate change.

Soil crusting is one of the degradation features which causes to decrease the land quality. To fix the crises due to soil crusting, it is therefore needed to identify the degraded areas and improve soil resource management. Since the soil properties have a spatial continuity, providing the digital maps using environmental covariates could be an interesting issue to study the spatial distribution. For this, a total of 107 soil samples were randomly taken over the East Azerbaijan Province, subsequently soil crusting index was calculated based on FAO method. To predict the soil crusting index across the study area, two models i.e., random forests (RF) and multiple linear regression (MLR) within the R programming environment using the data derived from digital elevation model (DEM) (18 indices) as well as remote sensing (eight indices) were evaluated. Results showed that the calculated soil crusting index for the entire study area varied from 0.07 to 2.25. Based on the results, RF was superior to MLR when using DEM-derived data, while MLR was distinguished as a parsimonious model when using RS data. It is concluded that selection of the best-fit model mainly depends on the available soil and covariates data used in modelling. Despite somewhat differences in pixel values between provided maps by the relevant models, the final maps demonstrated a similar trend. Generally, based on the results, the highest soil crusting index was found for west and central part of province, followed by south-eastern and north-eastern areas. The provided maps show that the forest and pasture areas have low value of crusting index, while the cultivated and miscellaneous lands were in the following orders which was consistent with field observations. This research further supports the importance of the digital soil mapping (DSM) technique in soil resources management.

The surface seal formation can have destructive agricultural, hydrological and environmental effects. Seal formation is a complex mechanism that controlled by a wide range of factors such as soil properties, rainfall characteristics, and flow conditions. The present research was conduct in order to identify an efficient index to determine the sensitivity of soil to the seal formation in the soil of Kowar plain region of Fars province.

In the present study, according to the area of the region, 160 sampling points selected, then according to the characteristics of the studied area and type of land use, to achieve the goals of the research, first, the land use, geology and topography maps of the area is prepared and by doing several times of field work in different seasons of the year, the topographies and shapes in the maps and pictures were adapted to the environmental conditions. To carry out this research, 80 composite soil samples (0-20 cm) were prepared from the Kovar plain of Fars province. Then the parameters of soil particle size distribution, mass moisture, organic matter, electrical conductivity and pH of saturated mud extract measured. Then the parameters of soil particles size distribution, volume wetness, organic matter, electrical conductivity and pH of saturated mud extract, measured. Also, mean weight diameter(MWD), geometric mean diameter(GMD), calcium carbonate equivalent, fractal dimensions, saturation percentage, sodium, calcium, magnesium, sodium absorption ratio (SAR), saturated hydraulic conductivity (Ks) and bulk density were determined. Assessing the sensitivity of the soil to the surface seal formation by comparing the regression equations of seven different indices, including the soil structural stability index (SSI), crusting index (CI), water aggregate stability (WAS), crusting susceptibility index (CSI), consistency index (C5 - C10), penetration resistance (PR) and relative sealing index (RSI) carried out in data preprocessing, Descriptive statistics of variables such as mean, maximum, minimum and variance, data distribution diagram and data distribution obtained using Minitab- 19 software. In addition, in case of remote data or mistakes in entering the data, appropriate measures taken and a table of descriptive information was prepared. The normality of the frequency distribution of these features evaluated using the significance test of skewness. To explain the ability of indicators and statistics in seal formation, First, linear correlation between variables determined by SPSS-22 software and by using Pearson's correlation coefficient (r), the correlation relationship between the indices and early characteristics of the soil was obtained and for data analysis, Pearson's correlation method and ridge multiple linear regression were used by stepwise backward method and using Statistica, SPSS-26 and Minitab-19 software.

In terms of the soil structural stability index, the studied area was in the danger range of aggregate destruction, which can considered relevant to the high percentage of silt in the region. The sodium surface absorption ratio of the majority of soil samples in the study area, had a non-sodium rating. 95% of the samples with agricultural land use in terms of organic matter were located in the weak to medium with structure and structure stability group. The majority of samples had more than 20% clay. Most of the measured variables had a low coefficient of variation and in terms of data distribution and dispersion, had a relatively favorable situation. Clay was the common variable in five regression equations of the indices, which refers to the importance and dual role of clay in the aggregates stability and reducing the sensitivity to compaction. The relatively low value of the standard deviation in the soil structural stability index indicated the greater accuracy of this model in estimating the coefficients. In the present study, the best-fitted regression model, to describe the sensitivity of the soil to the surface seal formation, compared to other models, belong to the soil structural stability and crusting indices.

Based on the results obtained, the soil aggregate stability index with the modified coefficient of explanation R2=0.92 had a high capability in predicting the sensitivity of the soil to the seal formation and is the most effective index in expressing the changes in soil aggregate stability and the surface sealing. The results of the data analysis expressing the extreme limitation class of the mean weight diameter was in the soil of the region.

Considering the climate suitability in cropping pattern selection is vital in maintaining food security. In this study, the climate suitability of East Azerbaijan Province, north east of Iran, for the cultivation of strategic crops of wheat and barley during four decades 1980 to 2000s was evaluated. Land units were classified based on the covered area of each synoptic weather station using Thiessen method. Climate suitability for rainfed and irrigated wheat and barley was evaluated according to their climatic requirements using the square root-parametric method. Results revealed that during the recent four decades, the climate suitability class for irrigated studied crops was very suitable across the province, but in case of rainfed cultivation, various suitability classes including moderate to unsuitable were observed in different regions. The results confirmed that despite of some unfavorable effects of climate change on suitability of region for both crops cultivation, these impacts might be compensated, to some extent, by technology or management improvements. According to this study, determination of an optimum cropping pattern, adjusting agronomic practices and changing of rainfed wheat to barley in this province may be recommended.

Urmia Lake is the largest saltwater in the Middle East, which has been located in the northwest of Iran. Nowadays, various factors have exposed it to dryness and wind erosion, the result of which is the increase in soil salinity, the thinning of solute crystals, and the occurrence of dust storms. Identifying the nature of these dusts specially the mineralogy of them is important in providing solutions to deal with the crisis. Investigating the characteristics and mineralogy of dusts in the region are useful in predicting and controlling ways to reduce their damages, and dust mineralogy is a practical method to determine their origin. In other words, the deposition of dust in different areas can affect the nearby ecosystems by making changes in the texture, composition of elements and even the acidity of the soils of the affected areas. The source of dust is very important in the mineralogy of sedimentary particles and depends on various factors such as geology and soil characteristics as well as climatic conditions. Also, the height of atmosphere which the dusts are there can be useful in studying the affect of mineralogy in this height.

For this purpose, three flat sites without vegetation and prone to fine dust production were selected from the eastern shore of Urmia Lake, and each site was divided into 3 layers based on the height from sea level, but the first layer was omitted from the studying areas because of the high soil moisture due to low distance to lake, which results in decreasing dust production by this layer, and eventually 2 random samples (0-5 cm) were picked up from each layer. This research work carried out based on 12 selected soil samples from 3 sites and their layers. The soil samples from 0 to 5 cm depth as a surface soil of layers were transferred to trays with dimensions of 3 x 40 x 30 cm in the wind tunnel of agriculture faculty of Tabriz University, with 370cm length, 50cm width and 70cm height, and wind erosion was simulated by applying the maximum wind speed of 45 meters per second to it was done for 15 minutes at each height. Then, the dust particles released at 2 heights of the wind tunnel (10 and 30 cm from the floor of the device) and the control soil sample were subjected to XRD analysis and the obtained diffractions were interpreted using High Score software. Finally, statistical analysis was performed using a nested design to find the effect of factors such as the location, layer and height of the wind tunnel on the content of minerals in windblown dust.

The obtained results showed that the dominant minerals in the most dust samples, were quartz, calcite, halite and gypsum with the highest average percent of quartz, because of the widespread occurrences of this mineral in the earth crust. The statistical analysis results revealed the significant effect of layer on quartz at the p<0.01 level, but the effect of site on calcite was significant at the p<0.05 level. But the maximum amount of quartz appeared in layer 2 of site 2, while its minimum amount has observed in layer 2 of site 1. The maximum and minimum amount of calcite was found in site 2 and 3 respectively, but predominance of quartz in the dust samples can be attributed to the wind blow within a short distance. This differences can be related to the nature of the parent materials of sites from which soils were derived. The presence of calcite as the main mineral in samples is due to study area temperature and precipitation increase and decrease respectively, which cause lake dryness, while gypsum and halite are produced in result of chemical equilibrium process and distribute in salty soils. Gypsum also can be produced during the reaction of calcite and sulfates of sea salts. The dryness of the lake also results in rising the gypsum minerals from dried floor of lake. Also, the presence of halite is affected by Urmia Lake salts that remain after water evaporation in dried land as a main mineral in soil and dust samples of affected lands.Key Words: XRD analyze, Wind erosion, Mineralogy, Wind tunnel, Urmia Lake.

Soil surface sealing is mostly influenced by the specific prevailing conditions during its formation, and the variables affecting soil surface sealing are the physical characteristics of the soil, the chemical conditions of the soil-water system, the characteristics of rain, and the initial and boundary conditions of the flow (Mualem et al, 1990). It is a common phenomenon in most soils of Iran due to arid and semi-arid climate, weak vegetation and loose soil aggregates. In Kowar plain, as an important Agricultural pole of Fars province, it is very important to determine the factors affecting the formation of surface sealing, to identify the most important characteristics of the soil in controlling the surface sealing formation, and to provide a suitable index to determine the sensitivity of the soil to this formation based on the characteristics of soil erosion, which are very important issues and have been addressed in this research study.

To carry out this research, 80 samples (0-20 cm) were selected from Kowar plain with a variety of physical and chemical characteristics, and after sampling, the samples were air dried and passed through a 2 mm sieve. Then, the parameters of particle size distribution, humidity, organic matter, electrical conductivity and pH of saturated soil extract were measured. In addition, the average weight and geometric mean diameter of soil aggregates, calcium carbonate equivalent, fractal dimensions of one-centimeter soil particles (Bartoli, et al, 1991), percentage of moisture saturation, sodium, calcium and magnesium were determined. The saturated hydraulic conductivity of the samples were measured and the evaluation of soil sensitivity to the surface sealing with seven different indices of SI, RSI, CI, WAS, PR (Permeability Resistance), CSI,   C5-C10 had been performed. Also multivariate statistical methods (cluster analysis, discriminant analysis and canonical correlation) were used for conducting the required analyses.

 After conducting the multivariate statistical method investigations, the results of cluster analysis led to the creation of a discriminant function with a chi-score of 12.73 reaching significance at the probability level of 0.001. This function completely showed the power (ability) to create separation between the two cluster analysis result groups. The organic matter was the most important primary variable that separated these two groups from each other and was significant at the probability level of 0.001. Based on the structure matrix, it was determined that CI, SI and CSI indexes with coefficients of 0.85, 0.58 and 0.30, respectively, are among the most important indices in the separation of these two groups. The performed canonical correlation provided a canonical function with a correlation of 0.99 and a chi score of 626.2. The highest canonical correlation belongs to primarily organic matter and then to clay. Two indices of Soil Stability Index (SI) and Crusting index (CI) were the most important indices having the highest correlation level among the indices. The most important variables influencing the evaluation indices of the sealing surface in the two group’s separation were organic matter and clay, which provided a function with high capability and the highest canonical correlation, respectively.

  The highest coefficient of variation is related to the mass of soil particles with a length of one centimeter (Bartoli model) and the highest canonical correlation in the first degree belongs to the organic matter and clay, it also shows the most important variables, with the highest correlation between these two variables with the mentioned indicators (CI,SI). In addition, two indices of SI and CI were the most important indices having the highest correlation among the indices. The results of cluster analysis, the discriminant function analysis and canonical correlation showed that the most important variables affecting the sealing surface evaluation indices in separating two groups and providing a function with high capability and the highest canonical correlation are organic matter and clay, respectively.  Also based on the structure matrix, the crusting index and aggregate stability are the most important indices that separate the two groups. In fact, the main samples differentiating factors in terms of the sealing surface are the above named indices. Organic matter and soil stability indexes have become significant with a very high correlation and showing a better justification of this indicator (SI) with the characteristics of the soil in determining the sensitivity of the soil to the seal structural formation layer.

Urmia Lake, which has been located in the northwest of Iran, is the largest saltwater in the Middle East. Unfortunately, nowadays various factors have exposed it to dryness and wind erosion, the result of which is the increase in soil salinity, the thinning of solute crystals, and the occurrence of dust storms. If this lake becomes dry, the climate of the area will change to hot climate and salt storms will start. Therefore, we must find new ways to control and prevent the occurrence of wind erosion. Identifying the nature of these dusts, especially their morphology, is important in providing solutions to deal with the crisis. Investigating the characteristics and morphology of dusts in the region is also useful in predicting ways and controlling factors to reduce their damages, and dust morphology is a practical method to determine their origin. Investigation of the properties and characteristics of rising dusts from this area can be useful in predicting and controlling ways to contrast/withstand their damages.

For this purpose, three flat sites without vegetation and prone to fine dust production were selected from the eastern shore of Urmia Lake. Each site was divided into 3 layers based on the height from sea level, but the first layer was omitted from the studying areas because of the high soil moisture due to low distance to lake, which results in decreasing dust production by this layer, and eventually 2 random samples (0-5 cm) were picked up from each layer. This research study was carried out based on 12 selected soil samples from 3 sites and their layers. The soil samples from 0 to 5 cm depth, as a surface soil of layers, were transferred to trays with dimensions of 3 x 40 x 30 cm in the wind tunnel of agriculture faculty of Tabriz University, with 370cm length, 50cm width and 70cm height. Subsequently, wind erosion was simulated by applying the maximum wind speed of 45 meters per second for 15 minutes at each height. Then, the dust particles released at 2 heights of the wind tunnel (10 and 30 cm from the floor of the device) and the control soil sample were sent to SEM to get their images. After processing these row images, the quantitative amounts of morphological properties were obtained. Finally, the statistical analyses were performed on these properties. Using a nested design to find the effect of factors such as the location, layer and height of the wind tunnel on the morphological characteristics of soils in the windblown dust.

The images which had been adopted from SEM were analyzed in Image J application and 5 parameters (perimeter, circularity, roundness, accept ratio and solidity) were calculated for each particle in samples and the average of these parameters for each soil sample was listed. The presented data were analyzed in Minitab application by using the fully nested method and for conducting these analyses, the test of normality of data was performed on data list. The results for each parameter were presented in a table which showed the effect of site, layer and location height of the sediments in wind tunnel.

The obtained results in this research (Table 3) revealed the significant effect of site (5%) on circularity and solidity properties. Also, the effect of height in wind tunnel from floor was significant in 5% just on roundness, and the effect of other factors on morphological properties were not significant. In other words, the size of particles, the area and their parameter in soil samples did not have significant differences and even the wind erosion with given speed in explained time duration didn’t act optional on the size of particles. There were no significant differences between size of diameter, area and parameters of particles before and after the wind erosion. The reason of these results can be dependent on the preparing method of samples for SEM study, in which the samples were rubbed on pin of device and the great grains were separated. Also, the effect of site and height of wind tunnel on roundness and circularity were significant, respectively. As for other morphological properties, the effects of site, layer and the wind tunnel height were not significant and there were no significant differences between the samples.

Soil erosion and sediment yield in the downstream areas, water transfer canals, and dams are the most serious problems in the world today. Soil erosion threatens soil resources, causes severe damage to infrastructures, and imposes high costs on agriculture, watershed management, and natural resources. Reducing these hazards and damages due to soil erosion and sediment yield requires the use of quantitative data to identify critical areas that require immediate protection. Due to the high cost and time consuming of conventional methods, the use of new remote sensing technologies and satellite imagery is essential. This study used the MPSIAC model, one of the most well-known models for estimating soil erosion and sediment yield in Iran, geographical information system (GIS), and satellite image processing with object-oriented and pixel-based methods. For this purpose, basic data were prepared using base maps, Sentinel-2 satellite imagery, meteorological and hydrometric data, and fieldwork. After establishing a database, the score for each of the nine factors of the MPSIAC model was determined using the three common, object-oriented, and pixel-based processing methods. The extent of soil erosion and sediment yield of the watershed was determined within each hydrologic unit. Based on the results, the soil erosion and sediment yield intensities of the Lighvan watershed were classified as medium class (III). However, the comparison of the specific soil erosion and sediment yield values obtained from the three methods showed that the use of object-oriented methods in determining the values for land cover, land use, and current soil erosion state increased the accuracy of the predictions (with the estimated error of 12.18% and 13.15% for sediment yield and erosion, respectively) compared to common (with the estimated error of 15.73% and 16.71%) and pixel-based (with the estimated error of 18.78% and 19.45%) methods.

Soil characteristics and development are influenced by environmental factors such as land use. Investigating the agricultural use effect on soil development and evolution can be useful in maintaining and improving the quality of land resources and preventing soil erosion and degradation. Soil development and evolution are the result of changes in its physical, chemical, biological, morphological, micromorphological and mineralogical characteristics, so the study of soil evolution indices indicates the impact of soil on environmental factors. Various morphological, physicochemical, and micromorphological indices of soil evolution due to their special nature show different aspects of soil impact from environmental factors. Therefore, the study of soil evolution as a result of environmental conditions of its formation and development can provide a suitable perspective for the continuation or the need to change the current management to maintain or improve land quality. This research study intends to examine the various indices of soil evolution that consider each aspect of soil development and evolution in relation to land management to be a fundamental step for the sustainable management of agricultural land.

The study area is the cultivated lands of alfalfa, corn, onion and wheat, and the adjacent barren lands in the Shurgol section of Bonab city of East Azerbaijan province, which is the site of selected control soil profiles under constant and uniform management over an average period of 15 years. After selection, the soil profiles were dug and described, and disturbed and undisturbed samples were taken from genetic horizons for physicochemical and micromorphological analyses and were transferred to the laboratory. Soils were identified and classified according to field studies and the results of laboratory analysis based on 12th edition of the Keys to Soil Taxonomy. Micromorphological studies of thin sections prepared from undisturbed soil samples were performed using a polarizing microscope based on a standard terminology system. In this study, a set of soil evolution indices, including harden, clay accumulation, appearance cation exchange capacity, MISODI, MISECA, and revised MISECA were used. Harden index is obtained by comparing the characteristics of texture class, plasticity, adhesion, type and degree of structure development, dry and wet stability of aggregates, clay coatings, darkening, lightening color and acidity of soil solum with C horizon. Clay aggregation and the apparent cation exchange capacity indices have been calculated based on the differences between the amount of soil clay in horizons B and C and the ratio of soil CEC to the percentage of clay, respectively.
To calculate the MISODI, MISECA and revised MISECA indices, the studied pedofeatures during micromorphological analyses, including microstructure, b- fabric, coating, nodule and degree of weathering and evolution of mineral particles were used. For this purpose, each of the mentioned characteristics, in terms of quality and quantity, was assigned a weight based on the relevant scoring tables, and the final evolution index was calculated from all of them.

The results showed that the soils of the region are non-saline and pH neutral; their texture is clay loam to clay and different amounts of organic carbon with irregular depth distribution are observed in soils under each type of productivity. Based on a complete study of the characteristics, different families of Inceptisols were identified with cambic and calcic horizons characteristic as well as Vertic properties in the soils of the region. Micromorphological studies revealed that the voids are simple and compound packing and include channels with granular and blocky microstructure in the surface horizons as well as chamber and sometimes vugh with massive microstructure in the lower horizons, while in the middle horizons angular blocky and subangular blocky microstructure were observed. According to the boundary between fine and coarse particles with 20 microns dimensions, the c/f particles in all soils have increased from surface to depth and the coarse part includes a variety of minerals. The b-fabric and related distribution pattern between the predominant coarse particles are of the crystalline and porphyric types, which in some cases are observed in speckled and monic forms, respectively. Pedofeatures observed in the soils of the region include intact, semi-decomposed and fully-decomposed organic residues, partial clay coatings and continuous and incomplete lime coatings and infillings in the channel. Soils under alfalfa productivity type with values ​​of 26.98, 1345.83, 13, 15 and 16 were identified as the most complete soils for harden, clay accumulation, MISODI, MISECA and revised MISECA soil evolution indices, respectively, while barren soils with 15.52, 419.75, 7,8 and 8 were identified as the least developed soils for the mentioned indices and the evolutionary order between these two groups is based on the mentioned indices for the productivity types of corn, onion and wheat. The values for the appearance cation exchange capacity index were 0.7 for wheat and barren soils, 0.68 for corn and onion and 0.67 for alfalfa.

As for soil classification, although differences exist at different categories or levels, but in this study, even at the family category or level, it is not possible to express the differences between soils under the productivity types of corn, onion, wheat and barren lands. In such cases, it can be useful to consider the soil evolution indices that quantitatively examine soil properties and determine their differences. Soil properties and, consequently, their evolution are affected by the productivity type in agricultural uses, and among these properties, the ones related to soil fabric are affected more than the others. Observing the evolutionary order of the majority of soils based on the studied indices for the productivity types of alfalfa, corn, onion, wheat and barren lands indicates that optimal agricultural operations and sustainable land use lead to accelerated evolution. Based on the quantitative values obtained for different indices in different types of productivity, it can be stated that the effectiveness of soils from the cultivated crop depends on the morphological and physiological characteristics of the plant and their planting, holding, and harvesting operations. Therefore, in arid and semi-arid areas, such as the studied area, where the soils are young and at the beginning of their evolution, the existence of more complete soils will be in line with increasing their quality and will prevent land degradation.

Soil evolution is the result of a combination of geomorphological and pedological processes. In this study to investigate the spatial variation of soil characteristics and determine the relationship between soil evolution and different geomorphic surfaces of epandage pediment, erosion pediment, slope surfaces, smooth surfaces, horst, lake deposits, alluvial fan, mountain ridge and circgue in an elevation-climatic profile in the Southeast of Ardabil 12 soil profiles were dug. After digging and field studies, physicochemical and clay mineralogical experiments were performed on the samples. The results showed that variations in weathering intensity and the types of soil forming processes at different geomorphic surfaces, had significant effects on soil properties and evolution and vertisols, mollisols, inceptisols, and entisols orders were identified. Smectite, vermiculite, kaolinite, and illite have formed the composition of evolved soil minerals, respectively and the relative amount of smectite varies from 78.5% at the epandage pediment to 12.3% at the mountain ridge. Also statistical comparison of the mean confidence interval of crystalline iron (Fed-Feo) by Bootstrap method showed that there were significant differences between geomorphic surfaces in terms of soil evolution and the highest amount of crystalline iron with mean of 6.372 g kg-1 was observed in epandage pediment with vertiolsols and the lowest value with average of 0.913 g kg-1 in alluvial fan with entiolsols. According to Spearman correlation test, crystalline iron had a direct relationship with clay percentage, calcium carbonate equivalent, pH and cation exchange capacity, but inversely with sand and organic carbon.

Land suitability evaluation is one of basic efforts to sustainable managements of any region. Shortcomings in traditional land suitability evaluation assessments have drawn the attention of this field users to use of artificial intelligence and multi-criteria decision making methods. Subsystems of mentioned methods alone or in the combination with each other were used to increase accuracy of evaluation, simplify of calculations and achievement of useful side results. Fuzzy-Delphi approach is one of discussed methods that in this study, its efficiency has been measured behind investigating of Horand region potential for irrigated wheat production.

In this study, 662 ha of lands in Horand region were selected in the form of 12 land units and after completing the climate, landscape and soil database, the Fuzzy-Delphi method was applied to qualitative and quantitative land suitability evaluation of irrigated wheat. The qualitative evaluation was done by land index determination and the quantitative one was completed based on predicted yield which calculated by combination of archived potential yield from Agro-ecologic method with soil index. In this regard, the Delphi method was used to select and determine weights of the factors which are involved in the evaluation based on the experts’ opinion and were validated by Kendall coefficient. The properties matrix which obtained from fuzzyization of land properties with kandel membership function were combined with weight matrix and leads to suitability matrix. The suitability zoning of the study area were identified according to suitability classes which were determined based on resulted soil and land index from defuzzification of suitability matrix with triangle Tnorm way. Validation of Fuzzy-Delphi method was done by conventional statistical tests.

According to experts’ opinion, the 8 properties (Climate, slope, texture, calcium carbonate equivalent, gypsum, EC, drainage and flooding) of studied lands with Entisols and Inceptisols, were selected for land suitability evaluation that climate and gypsum have had maximum and minimum weight respectively, that its accuracy was confirmed by an incompatibility rate of 0.07. The conformed suitability evaluation showed S1 to S3 classes by qualitative and quantitative methods for irrigated wheat utilization type with limitation of slope, salinity, texture and gypsum. Difference of land units classes in qualitative and quantitative methods was seen only in one land unit which quantitative one take lower class. According to mean management index of 0.73, the middle management level was estimated for region. Chi-square value of 1.32, r2 0.91, RMSE 2.1% and GMER 1.34 obtained in the validation of Fuzzy-Delphi method.

Applying main agricultural lands users opinions in selecting and valuating land suitability evaluation parameters, combination of characterize weight with their rating and also considering intermediate classes, identified as the main advantages of the studied model over traditional methods that introduced the fuzzy-Delphi approach as an efficient method based on estimation of the land potential. The reliability of mentioned approach was confirmed by checked statistical accuracy and validity although with little over estimation. Beside main finding of this research work, coordination of qualitative and quantitative suitability evaluation with discussed approach, possibility of ranking the land limitation remove by sub data and also, pay attention to the land suitability class along with the management index for future land management planning are the cases that can be useful for researchers and executive experts. However, in order to find other capabilities of the model and recommending its use at the wide level, it is suggested to run this new model in different areas for various utilization types.

The wind erosion occurs when wind speed exceeds the soil erosion threshold and plants or their residues,surface roughness, or other obstacles do not protect the soil surface. Also wind erodibility is oneof the most important determining parameters of wind erosion under certain climatic conditions. The main objective of this research was mapping of soil erodibility through empirical relationship between satellite imagery and physicochemical properties and estimation of soil erosion using a comprehensive assessment model, on the east shore of the Urmia Lake. For this research work soil sampling carried out in 153 points of three elevation classes(1271-1273, 1273-1275 and 1275-1278meters)and4supervised classification methods such as, support vector machine(SVM), Maximum likehood classification (MLC), Minimum distance and Artificial neural network(ANN)were used in classifying and mapping of soil erodibility. Soil samples physicochemical properties measured and 26 samples of them randomly were selected for wind erodibility measurement in wind tunnel laboratory. Wind tunnel experiments at a distance of 20 cm from the tunnel floor, revealed wind erodibility of 2.92 grm-2.min-1/ms-1. Also stepwise regression (SPSSv.25) results showed that among the physicochemical properties of soils, erodible fraction were the most important soil properties, which used in estimating erodibility and have a positive correlation with soil erodibility. The mean weight of aggregate diameter had negative correlation with soil erodibility and no relationship was found between soil chemical properties and erodibility. Of the4supervised classification methods, the artificial neural network has a higher capability in classifying and mapping erodibility and finally the results showed that the overall classification accuracy is57.1%.

In this study, digital mapping of the most important forms of soil Iron were done using two data mining techniques namely Decision Tree (DT) and Cubist (Cu) models. The study area includes 500 km2 of lands from two different sites located in the eastern shore of dried bed of Urmia Lake, northwest of Iran. 131 surface soil samples were taken from depth of 0-10 cm and three different forms of Iron including i): total iron (Fet); ii) pedogenic iron (Fed); and iii) amorphous iron (Feo) were measured. A total of 19 environmental covariates (auxiliary variables) derived from the Landsat-8 OLI imagery related to July 2017 were used in this study. It was found that Cu model has a higher precision than that of the DT model for predicting all three forms of  soil iron with the values R2=0.89 and RMSE= 2.25 g/kg , R2=0.85 and RMSE=0.57 g/kg and R2=0.88 and RMSE=0.09 g/kg for predicting Fet, Fed and Feo, respectively. In addition, the results of the importance and percentage of contribution of environmental covariates in both models indicated the high importance of some spectral indices such as Normalized Difference Moisture Index (NDMI) and Modified Soil Adjusted Vegetation Index (MSAVI) in the prediction of Fet, Fed and Feo. Generally, the Cu model has a higher ability and performance in modeling and predicting the spatial distribution of different forms of soil iron in the study area compared to the DT model.

Water erosion is one of the most important causes of soil destruction, and it is considered a serious environmental hazard all over the world. Recently, remote sensing is customarily used in conservation and erosion projects that most of them use air photography which, despite the many benefits, bot have limitations. The present study was aimed to detect and zoning soil erosion levels using high resolution of Sentinel-2 satellite image, its integration with aerial photographs, base maps, and implementation of various classification methods, including pixel-based and object-oriented techniques. After the staff operations, atmospheric and geometric corrections, pre-processing, and processing done on images of Sentinel-2 for detecting the area of erosion in the Lighvan watershed. In order to evaluate the correctness and accuracy of each method in this study, the criterions of user and producer accuracy, accuracy and kappa coefficient were compared. Based on the results, the supervised tuning method with user accuracy equal 77.78 and 33.33, has the highest and lowest accuracy for classification using spectral angle map algorithm and Mahalanubis distance, respectively. The maximum of overall accuracy and kappa coefficients, 72 and 62 percent, respectively, indicate the medium accuracy of the produced maps with pixel based algorithms. The results of object-oriented processing show that based on user and producer accuracy, object-oriented methods have increased accuracy (12 %) compared to pixel-based methods. Classification results with object-oriented algorithms and based on overall accuracy, 88 and 84 percent, respectively, for the brightness and the combination of brightness and slope, and the kappa coefficient for these two algorithms was 0.86 and 0.79, respectively. This result represents an acceptable increase in classification accuracy in the use of object-oriented algorithms compared to pixel base algorithms.

Spatial variability of the soil properties is related to the environmental factors such as climate, topography, parent material and vegetation. Topography causes significant differences in soil properties through the three factors of elevation, natural drainage and slope. This research was carried out to investigate the effect of elevation on some physical and chemical characteristics, type and content of the clay minerals, and finally on the evolution of soils of an elevation profile in Talesh Mountain in Ardabil province. Following excavation and description of five profiles on non-eroded surfaces, physical, chemical and clay mineralogy experiments were performed on the samples. The results showed that weathering intensity and type of pedological processes were different and hada significant effect on some soil characteristics such as clay content, different forms of iron, minerals and soil classification at the different surfaces of elevation. With decreasing the altitude, the amount of illite minerals was reduced but the amount of smectite minerals has increased, which is a reason for the improved weathering and evolution of the soils. The results show that toeslope lands have evolved soils of Vertisols and Mollisols, but highlands have Inceptisols with low degree of evolution. Addition, in the studied elevation profile, as the altitude decreases, the climate becomes warmer and consequently the intensity of pedogenic processes increases.The increase in the amount of crystalline iron (Fed-Feo), as an indicator of soil evolution, from 2303.9 mg kg-1 at the topslope to 7558 mg kg-1 at the toeslope of the mountain illustrates this evolutionary trend.

In this research work, land suitability as one of the first step in sustainable agriculture was done to find urgency of utilization type change in Horand region. Also, different aspects of qualitative and quantitative land suitability methods were discussed to determine and improve the involved criteria in sustainable agriculture evaluation.  

Qualitative and quantitative land suitability of common utilization types in study area such as rainfed and irrigated wheat and onion carried out by providing climate, landscape and soil information. Chi-square test, Pearson correlation and Regression relationship were performed to test accuracy and validity of evaluation methods. The suitability zoning of study area was completed for different land utilization types and behind interpretation output maps, the management level was analyzed.  

Dominant climate and slope limitation with other studied factors which had role in decrease of suitability in some case, caused to suitability classes of N for rainfed wheat, S1to N for irrigated wheat and N for onion. Statistical studies confirm the accuracy of the evaluation methods. Determined middle and low levels of managements are keeping with field conditions.  

Unsuitability and in some cases low suitability of the region, indicates the urgency of change in common utilization type. There isn’t so important difference between qualitative and quantitative suitability evaluation methods in high limitation with unsuitable class. Environmental and management factors which have indirect effects on limitations should be considered behind yield value in land management index determining.

Soils are considered as one of the most important parameters to be achieved the sustainable agriculture at any place in the world. Additionally, the digital environment needs to have a soil continuous maps at local and regional scales. However, such information are always not available at the required scale and mapping with high accuracy. Digital soil mapping (DSM) is a key for quantifying and assessing the variation of soil properties such as organic carbon (OC) especially in un-sampled and scarcely sampled areas. Using remotely sensed indices as an important auxiliary information relevant to the study area and data mining techniques were the pathway to create digital maps. Previous studies showed that digital elevation model (DEM) and remotely sensed data are the most commonly useful ancillary data for soil organic carbon prediction. the importance of DEM and derivative data in soil spatial modelling, it was not carried out in our research because there were no sharp differences in relief, and climate for that matter, across the study area. This research aims to investigate the spatial distribution of soil organic carbon (SOC) in a study area in north-western Iran using 21 remotely sensed indices as well as two data mining techniques namely Random Forests (RF) and Cubist.

This study was performed on the east shore of Urmia Lake located in the east Azerbaijan province, Iran. The area extension is about 500 km2. Based on the synoptic meteorological station report, the average annual precipitation and temperature of the study area is 345.37 mm and 10.83°C, respectively. Soil moisture and temperature regimes are Xeric and Mesic, respectively. Using stratified random soil sampling method, 131 soil samples (for the depth of 0-10 cm) were collected. Soil organic carbon (SOC) were then measured. The next step was to gather a suite of auxiliary data or environmental covariates thought to be useful (and available) for predicting SOC within a DSM framework for the region studied. Then, a number of remotely sensed imagery scenes from the Landsat 8-OLI acquired were collected in July 2017. The RF and Cubist models were applied to establish a relationship between soil organic carbon and auxiliary data. Both reflectance of the individual bands and indices derived from combinations of the individual bands were used. Fourteen spectral indices relevant to four types of data including: i) vegetation and soil; ii) water; iii) landscape; and iv) geology were gathered. Three different statistics was used for evaluating the performance of model in predicting SOC, namely the coefficient of determination (R2), mean error or bias (ME) and root mean square error (RMSE).

The results of the descriptive statistics of determined and calculated SOC for 131 soil samples showed that the mean and median values for SOC were 2.52% and 2.11%, respectively. Also, the CVs was recorded 57.94%. Minimum and maximum recorded values for SOC were 0.83% and 5.22%, respectively. The contents of SOC was left-skewed in the data set. The RF model prediction was quite good with calibration (R2= 0.89, MSE = 0.16 and ME = 0.01). While, in the Cubist calibration data set, the Valve of RMSE and ME were increased (R2= 0.85, MSE = 0.21 and ME = 0.03). In terms of R2, The RF model showed the higher value (0.89) compared with the Cubist model (0.85) for the validation dataset. Generally, the remote sensing (RS) spectral indices can successfully predict various SOC across the study area. The covariate importance rankings showed that VARI , NDVI , CRI2 and CRI1 were the four important covariates to predict SOC in the study area. Accordingly, the changes in SOC over space were not uniform across the study area and also it means that the study area is very dynamic and evolved over time.

The results of this study showed that although variables and auxiliary data had different importance in predicting the distribution of SOC, in general it can be found by modelling the relationship between them and SOC through the model. The results revealed that the RF model was suitable for the target variable. Accordingly, the auxiliary variables had different importance in predicting the spatial distribution of SOC. Remote sensing imagery, particularly those encompassing the combined indices played an important role in the prediction of SOC. The obtained results also indicated that the Visible Atmospherically Resistant Index (VARI) and Normalized Difference Vegetation Index (NDVI) were important to predict SOC. The current study revealed that DSM using important environmental covariates can be successfully used in Iran which there is no sufficient soil databases. This research also provided a pathway to start further works in the future such as DSM relevant to the soil erosion, soil ripening, trace elements and so on.

According to important ecological roles of soil organic matter in stabilizing ecosystems, it is essential to consider soil organic carbon condition for managements of worldwide problems such as soil quality, carbon cycle and climate change. Also, organic matter is one of the main component of soil which have vital impress on its evolution. Therefore, assessing soil organic matter fate in various environmental conditions and its relation with environmental factors will be useful for management decisions. Determining soil organic carbon content, stocks and forms by the physico-chemical and micromorphological studies may respond to the question about soil organic matter evolution from the different point of views. Based on mentioned reasons, our research work focused on soil organic matter content, stocks and forms under various environmental condition of the forest ecosystem to find new aspects of its relation with environmental factors.

This research work was carried out in Arasbaran forest, northwest of Iran, which recognized as a part of the international network of biosphere reserves and has unique species of plants with special ecological properties. Sampling was carried out in a Kaleybar Chai Sofla sub-basin as a part of Arasbaran forest with eastern longitude of 46º 39´ to 46º 52´ and northern latitude of 38º 52´ to 39º 04´. Based on the Amberje climate classification, the climate of the region is semi-humid and moderate. The soil moisture and temperature regimes are Xeric and Mesic, respectively. Hornbeam (Carpinus betulus) and Oak (Quercus petraea and Quercus macranthera) were identified as the main woody species in this area and volcano-sedimentary rocks were the geological structure. Primary site surveying showed 5 forest stand types such as Oak (Quercus macranthera), Hornbeam-Oak (Carpinus betulus-Quercus macranthera), Hornbeam (Carpinus betulus), Hornbeam-Oak (Carpinus betulus-Quercus petraea), Oak (Quercus petraea) along altitudinal transects, that used as environmental parts with different conditions. In each environmental part, a soil profile was described and sampling was done for physical, chemical and micromorphological analysis. After preparing soil samples in the laboratory, soil physico-chemical routine analyses were carried out by standard methods and then the studied soils were classified on the basis of 12th edition of soil taxonomy. To achieve the main aim of the study, various aspects of soil organic matter evolution were assessed. Soil organic matter content was determined according to the Walkley–Black wet oxidation method and using alteration factor f = 1.724 recommended by USDA. Variance analysis and means compare of soil organic matter content in surface horizons of different environmental parts were performed by using the SPSS software package and Dunkan's multiple range test, respectively. Soil organic carbon stocks were calculated for each soil horizon and weighted average based on profile depth was used to calculate this index for each soil profile. The prepared thin section for micromorphological study was examined under both plane-polarized light (PPL) and cross-polarized light (XPL) using a polarized microscope and explained based on standard terminology to identify various forms of soil organic matter all over the study area.

Results revealed increasing of soil evolution with decreasing of elevation. Entisols, Inceptisols, Alfisols and Mollisols with different families were the soil observed along altitudinal transects by decreasing elevation. According to the obtained results, environmental effects caused different soil organic matter content and evolution with various soil organic carbon stocks in each part. Improvement of environmental condition by decreasing elevation resulted in more evolution of soil organic matter, dominant of decomposed forms of organic matter and rise of soil organic carbon stocks from the highest part to the lowest one. Soil organic matter content in soil surface increased by elevation, although the main source of soil organic matter have better condition in lower parts due to ecological reasons. This inverse statue can be explained by special environmental conditions causing limited organic remnants decomposition in the highest parts. In the same trend with soil evolution, soil organic carbon stocks increased by decreasing of elevation. This trend refers to the relation of mentioned index ability with various soil-forming processes. Micromorphological study showed that organic intact remnants were the dominant forms in upper parts which changed to well-decomposed forms in the lowest parts. This observation revealed the occurrence of mechanical decomposition processes of organic remnants in high elevation while biochemical ones happen in the lower parts. Also, this distribution of soil organic matter decomposition processes can explain soil organic carbon content and stocks all over the study area.

Elevation was identified as an important environmental factor controlling soil organic matter in the studied scale. Generally, results confirm the same trend for soil organic matter evolution and soil organic carbon stocks with soil development, especially in pedogenesis processes in relation to organic matter. Thus, it can be recommended to use soil map for management of soil organic matter under various environmental conditions in large-scale studies.

Due to the location of Iran in a dry and semi-arid region, it is always affected by sloping instability and erosion as the most severe type of erosion, gully erosion. This erosion pattern occurred in different parts of Iran and continuously over many years, and during erosion and the transfer of high sediment volume, it destroyed roads, facilities, pastures, slopes, etc. This will require the identification of high risk areas and the development of sensitivity maps. In recent years, the processing of satellite imagery as an advanced method has been widely used by researchers to increase the accuracy and save time and money. The object-oriented analysis of images is one of the most important methods for extracting information from satellite imagery, which is based on spectral, form and spatial characteristics and using expert knowledge to identify complications.

In this research, the Lighwan watershed basin was studied as one of the most important sub-basins of Aji Chay in East Azarbaijan Province and the satellite images of Sentinel-2 (2016) with spatial resolution of 10, 20 and 60 meters for the processing and identification of gully Was used. The images were processed using the eCognition software and applied with different types of algorithms to design a semi-automatic model based on object-oriented analysis. Finally, in order to evaluate the accuracy of the model, the identified Gully were mapped out and calculated using ArcGIS software to match the ground reality map and the formation of the error matrix, manufacturer accuracy, user accuracy and kappa coefficient for each of the algorithms.

The results showed that the Density and Compactness algorithms had the highest and lowest accuracy of the manufacturer (manufacturer accuracy was 88 and 78 respectively). While based on Kappa coefficient, the asymmetry algorithm has the highest accuracy compared to other methods (kappa = 0.91). Then, the shape index and density algorithms with kappa coefficient equal to 0.89 and 0.85 provided acceptable accuracy for the classification and identification of the gully.

The use of object-oriented methods due to the increased accuracy of classifying and identifying surface effects and phenomena can be used as a suitable solution for future soil studies and natural phenomena. In the present study, semi-automatic semi-automatic model for ditch identification was presented using spectral and geometric properties of Sentinel-2 satellite images and object-oriented processing in eCognition software environment. Key words: Object Oriented Algorithms, Object-Oriented Processing, Segmentation, Classification