hamidreza momtaz

According to the environmental crisis of the last two decades and the drying of some parts of the Urmia Lake and its impact on the surrounding agricultural lands, this study aimed to identify minerals in soils in different parent materials in order to understand the interaction of soils with parent materials and to predict their change trends. Twenty six soil profiles were described on different parent material and thirteen were selected as index profiles and studied precisely. Clay mineralogy results indicated the presence of clay minerals of illite, smectite, chlorite, kaolinite, vermiculite and palygorskite in this area.The presence of palygorskite in the profiles had two origins, pedogenic and inherited from parent material. Also, kaolinite and chlorite minerals are inherited from parent materials due to the lack of conditions for pedogenic formation. Illite was inherited in most soils and in profiles with agricultural use, potassium adsorption was carried out by expanded minerals and formed the illite on the soil surface. The origin of smectite was also pedogenic in some soils of this region, probably due to illite weathering, and in others it was hereditarym, Because they have also been observed in their parent rocks.Vermiculites in this area were also often of pedogenic origin and are derived from mica and chlorite. The results showed that different parent materials have a high effect on soil physicochemical and the amount of minerals in this area.

Sustainable agriculture will be achieved only when land is used, essentially based on soil and water capacity. Otherwise, agricultural lands will influenced by increasing degradation and erosion. Therefore, this study aimed to evaluate the land suitability of orchard (200 hectares) located on the southern Urmia plain (Darbrud soil series) and also provide a suitable irrigation model using CROPWAT considering irrigation water shortage and lack of adequate drainage for apples as a main crop in this area (%55). Ten years of climate data was collected, and the land index was evaluated by parametric method (square root method). Limitation in drainage status resulted in (S3w) for land subclass, while for climate and temperature suitability, the minimum average temperature during the month before harvest, reduced the subclass to S2. Moreover, CROPWAT model was used to estimate the efficiency of model for important horticultural crops under a proper-irrigation management in the study area through comparing the results of the model with those from the FAO model. The result of this study indicates that an excessive or over irrigation regime has occurred in the studied fields which have no positive effect on the crop yield or economic benefits. Providing irrigation projects based on a suitable water model will increase the water use efficiency.

Soil erodibility is a dynamic aspect that varies over time and with plough, animal’s activities and biochemical factors resulting in a major environmental threat to the sustainability and productive capacity of agricultural areas. In Universal Soil Loss Equation (USLE), soil erodibility factor (K-factor), as an effective parameter in water erosion is a function of particle size distribution, organic matter, structure and permeability. In the present study, the spatial distribution of the amount of K-factor was investigated in the Nazlou Chai Watershed in Urmia, West Azerbaijan using geostatistics. Then soil samples were taken from 1 km by 1 km square grid over 64 location, and the amount of K-factor was calculated in the USLE model. The results showed that K-factor was ranged from 0.029 to 0.079 (T h MJ-1 mm -1). The spatial variation of K-factor was best fit to the exponential model and showed a moderate spatial structure. The studied soils were categorized in low and very low erodibility classes. The quantitative amounts of erodibility were categorized based on slope classes and the highest value observed for 5-8% slope that belongs to dry farming land use. Also K-factor showed various values in different hydrological groups, where group A showed the least and group D showed the highest amount. It seems that inappropriate soil management in both hilly areas and dry farming lands is one of the main causes of soil damage and an increase of soil erodibility.

Near-saturated soil hydraulic conductivity (Ks) is a key property for several purposes including simulation of hydrological processes, determination of unsaturated soil hydraulic conductivity function and modelling water flow and solute transport. Since it is soil structure-dependent, field measurement techniques should be used to minimize disturbance of the sampled soil volume. Because of high spatiotemporal variability of Ks, replicated measurements need to be carried out, so that, the method to be applied should be simple and rapid enough as the simplified falling head (SFH) technique is. Alternatively, pedotransfer functions (PTFs) could also be utilized for indirect prediction of Ks through the surrounding soil attributes. The objective of this study was to test some new inputs to predict the Ks of salt-affected soils adjacent to Lake Urmia. A 32 cm diameter ring was used to determine Ks by the SFH technique in soils with different salinity (electrical conductivity of saturated extract, ECe = 0.1 – 95.3 dS/m) and sodicity (exchangeable sodium percentage, ESP = 4 – 70.9 %) levels. A total of 190 SFH runs were carried out, adjacent to each of which, some undisturbed soil cores (5 cm in height by 5 cm in diameter) and disturbed soil samples were randomly collected from the surface soil and were analyzed for their physicochemical properties. The studied soils mainly had moderate (≈ 40%) to moderately rapid (≈ 48%) conductivities. Correlation and stepwise regression analysis showed that Ks was correlated negatively with bulk density (ρb) (r = -0.205), index of crusting (Ic) (r = -0.180), and degree of compaction (SDC) (r = -0.206) (P ≤ 0.01) and positively with structural stability index (SSI) (r = 0.184) and geometric mean diameter of soil aggregates (GMD) (r = 0.157) (P ≤ 0.05). Furthermore, the Ks had negative correlation with both soil ECe and ESP.

Phosphorus (P) is an essential nutrient that its bioavailability controlled by sorption and desorption process. To study the behavior of phosphorus (P) sorption in agricultural soils of Khoy region, bath experiments were carried out with 60 cultivated soil samples and 9 initial P concentrations from 0 to 30 mg L-1 in 0.01M CaCl2 as a background solution. After equilibrium, remaining amount of P in solution was measured and the experimental sorption data were fitted to Langmuir, Freundlich and Temkin models. Based on coefficient of determination (R2) and standard error of estimate (SE), Langmuir isotherm models, is relatively better fitted to experimental data compared with Freundlich and Temkin models. The maximum mono layer sorption of Langmuir (qmax) varied from 135 to 486 mg kg-1 and energy parameter of Langmuir (KL) varied from 0.09 to 0.52 L mg-1. Also, Freundlich sorption capacity (KF) and intensity (n) parameters was varied from 16.0 to 123.4 mg kg-1 and 1.1 to 2.4 respectively, and Temkin equation constants, A and KT varied from 10.3 to 196.3 mg kg-1 and 17.3 to 88.7 L mg-1, respectively. The soils with high clay and CaCO3 showed maximum qmax, KF and A, and mentioned sorption parameters significantly correlated with clay and CaCO3. The result showed that the amount of equilibrium P concentration (EPC) values varied from 0.01 to 0.89 mg l-1, 0.35 mg l-1 on average for the cultivated soils. Also, there was a highest significant correlated between EPC and extractable phosphorus with sodium bicarbonate (r = 0.90**). The Potential buffering capacity (PBC) values was from 3.2 to 122.4 and 33.5 mg kg-1 on average. PBC significantly correlated with soil clay content (r= 0.80**) and amount of calcium carbonate (r=0.43**).

Cation Exchange Capacity (CEC) refers to the amount of negative charges available on the soil colloids surface. Clay and organic colloids carry a negative charge on their surfaces. Cations are attracted to the colloids by electrostatic bonds. Therefore, the charge of the soil is zero. For fertility map planning and commonly indicator of soil condition, CEC is an essential property. CEC is commonly measured on the fine earth fraction (soil particles less than 2 mm in size). CEC could be obtained directly but its measurement is difficult and expensive in the arid and semi-arid regions with high amounts of gypsum and lime. Pedotransfer functions (PTFs) are appropriate tools to estimate CEC from more readily measured properties such as texture, organic carbon, gravel, pH and etc. Regression PTFs, artificial neural networks (ANN), and hybrids technique (HA) could be used to developing pedotransfer functions. The prior research revealed that could provide superior predictive performance when developed ANN model. Furthermore, ANN technique has no comprehensive method to select network learning algorithm and stopping algorithm in the minimum local. Therefore, application of optimization algorithms such as Genetic (GA) and firefly (FA) is necessary. The Purpose of the present study was to evaluate the performance of FA and GA to predict the soil cation exchange capacity by ANN technique based on easily-measured soil properties.
220 soil samples were collected from 39 soil profiles located in Golfaraj (Jolfa) area of East Azarbaijan province. The study site lies from 45° 30ʹ to 45° 53ʹ east longitudes and from 38° 42ʹ to 38° 46ʹ north latitudes. Then, soil samples were air-dried and passed through a 10 mesh sieve for removing gravels and root residues. Soil textural class, organic matter content and CEC were, respectively, determined by hydrometer, Walkley and Black, and bower methods. The artificial neural network (ANN), artificial neural network-Genetic algorithm (ANN-GA) and artificial neural network-Firefly algorithms (ANN-FA) models were applied to predict the soil cation exchange capacity on the basis of the easily-measured soil properties. In ANN-GA and ANN-FA models, soil CEC was estimated via an artificial neural network and were then optimized using a genetic algorithm and firefly algorithm. The Genetic algorithms are commonly used to generate high-quality solutions to be optimized by relying on crossover, mutation and selection operators. The firefly algorithm is modeled by the light attenuation over fireflies’ mutual gravitation, instead of the phenomenon of the fireflies light. The schema of flashes is frequently unique for specific types. The techniques’ results were then compared by four parameter, i.e., correlation coefficient (R2), root mean square errors (RMSE), Nash–Sutcliffe (NES) and Geometric mean error ratio (GMRE).
The correlation coefficients of soil characteristic factors with CEC were analyzed through correlation matrix analysis. According to this analysis, the factors which had insignificant influence on the CEC were excluded. The clay, silt, sand and organic matter content were selected as input data. The parameter of the best deployment for MLP network could be used to predict CEC in the studied site. This model comprised 4 neurons (sand, silt, clay percentage and OM) in input layer. The optimum number of neurons in hidden layer was estimated to be 5. Additionally, the most efficient activity function in hidden layer was Axon sigmoid. Results showed that three CEC models performed reasonably well. ANN-FA model had the highest R2 (0.94), lowest RMSE (1.31 Cmol Kg-1) and highest Nash–Sutcliffe coefficient (0.53) in training stage and high R2 (0.97), lowest RMSE (1.06 Cmol Kg-1) and highest Nash–Sutcliffe coefficient (0.59) in test stage. ANN-GA model had also higher R2 (0.91), lower RMSE (1.77 Cmol Kg-1) and higher Nash–Sutcliffe coefficient (0.45) in training stage and higher R2 (0.93), lower RMSE (1.50 Cmol Kg-1) and higher Nash–Sutcliffe coefficient (0.48) in test stage indicating good performance of the model as compared with ANN models. The results showed that both ANN and Hybrid algorithm methods performed poorly in extrapolating the minimum and maximum amount of CEC soil properties data. In addition, the comparison of ANN-FA, ANN-GA results with ANN models revealed that ANN-FA was more efficient than the others.
The results of present study illustrated that ANN model can predict CEC with acceptable limits. Therefore, FA and GA algorithms provide superior predictive performance when is combined with ANN model. Firefly algorithm as a new method is utilized to optimize the amount of the weights by minimizing the network error. Final results revealed that this suggested technique improves the modeling performance.

Minerals are one of the main components of soils which play different roles in the soils. Minerals make up about 50% of the volume of most soils. They provide physical support for plants, and create the water- and air-filled pores that make plant growth possible. Mineral weathering releases plant nutrients which are retained by other minerals through adsorption, cation exchange, and precipitation. Minerals are indicators of the amount of weathering that has taken place, and the presence or absence of particular minerals gives clues to how soils have been formed. The physical and chemical characteristics of soil minerals are important consideration in planning, constructing, and maintaining of buildings, roads, and airports. Clay minerals can be used for understanding of soil formation, optimum management of dry and wet lands and interpretation of paleo environments. Moreover, clay minerals can provide some valuable information such as the origin of sediments, transportation and precipitation of sediments and also some information about intercontinental weathering regimes. Quaternary sediments have occupied most of the agricultural and natural resources of Urima plain and recognition of mineralogical of these soils is essential to optimum and stabile use of these soils. Additionally, caly mineralogical investigation can provide some information about the intensity of weathering processes and climate change in this area. Thus, in this study clay minerals of quaternary sediments in northeast of Urmia and the mechanisms of their formation and also tracing probable climate change in this area were investigated.
This study was performed in theUrmia plain in west Azerbaijan Province. The study area is located on quaternary sediments and physiographically, this area is a part of a river alluvial plain with the gentle slope toward Urmia Lake. The mean annual precipitation and temperature of this area are 345.37 mm and 10.83 °C respectively and the soil moisture and temperature regimes are dry xeric and mesic respectively. In this study, eight soil profiles in quaternary sediments were dug and sampled and the morphological, physical, chemical and mineralogical properties were determined using standard methods.
According to the results, Illite, smectite, Kaolinite, chlorite, vermiculite and hydroxy interlayer vermiculite (HIV) were the dominant clay minerals in these soils. The origin of illite, chlorite and kaolinite were related to inheritance from parent material. Regarding to the present of some smectite in the parent material of these soils, some of smectites have been inherited from parent material. Nevertheless it seems that, the most of smectites in these soils have pedogenic origin. Based on mineralogical results and trends variation of smectite and illite along studied profiles, we concluded that some of smectites in these soils have been formed from illite transformation. In profiles 4 and 6, regarding to low depth water table and consequently poor drainage, high pH and high values of calcium and magnesium cations, provide suitable conditions for the neoformation of smectit and so, some of smectites have been formed via neoformation from soil solution. In these soils, vermiculites were pedogenic and have been formed during transformation of illite to smectite. Small amounts of hydroxy interlayer vermiculites were present in buried horizons and regarding that they were not present in parent material, it might be because these minerals are pedogenic and have been formed in a past wetter climate. The transformation of illite to smectite in lower horizons needs high moisture and regarding to recent semiarid climate of study area, the suitable amount of moisture for this transformation, especially in lower depths and also in buried horizons, is not present. Thus, it seems the transformation of illite to smectite in lower depths and buried horizons has been taken place in a wetter past climate. So we concluded that smectite and hydroxy interlayer vermiculite are evidences of a wetter past climate in this area.
In this study the origin of smectite in buried horizons was related to transformation of illite. According to high moisture condition which is necessary for the weathering of illite, the occurrence of this process related to more humid climate of the past. Additionally, the presence of hydroxy interlayer vermiculites was related to previously wetter climate as well. So results of this study can be used for recognition of climatic change in the study area.

The present study was conducted to study of potassium sorption behavior of soil in Khoy region. Sorption isotherm was constructed in the laboratory by equilibrating and shaking 2.5 g soil with 25 ml of 0.01 mM CaCl2 containing 0-150 mg K L-1 as KCl for 24 h. After equilibrium, remaining concentration of potassium measured and potassium Quantity-Intensity (Q/I) curves and their parameters such as potassium buffering capacity (PBCK¡( potassium activity ratio at equilibrium (AReK), readily exchangeable K (∆K0), standard potassium requirement (SKR), equilibrium potassium concentration (EKC) and energy of exchange (EK) were calculated. Mean comparison of paired soil samples indicated that the AReK, EKC and ∆K0 values of cultivated soils were significantly (p≤0.001) lower than those of virgin soils, indicating decreasing of potassium in the cultivated soils. As with cultivation, AReK mean decreased from 0.0188 to 0.0048 (mol.L-1)0.5 and ∆K0 mean decreased from 0.117 to 0.057 cmolc kg-1. Mean of equilibrium potassium concentration (EKC) in virgin and cultivated soils was 91 and 34 mg.l-1 respectively and PBC mean for cultivated and virgin soils measured 11.8 and 7.7 cmolc.kg-1/(mol.L-1)0.5 respectively. It was concluded that soils of studied region have relatively sufficient potassium for plants but cultivation and fertilizer management lead to a reduction in the amount of potassium in soils and increasing the adsorption parameters.

Quaternary sediments have occupied most of the agricultural and natural resources of urmia region. Recognition of physicochemical and mineralogical properties of these soils is essential to optimum and stable use of these lands. In this study, eight soils profiles excavated on Quaternary sediments of Urmia region were investigated. The results showed that little thickness and evolution of studied soil was possibly due to the sequential soil erosion and sedimentation processes.Consecutive erosion-deposition processes at different periods led to the formation of calcic horizons and sedimentary layers in lower depths indicating climatic fluctuation, along with dissolution and translocation of carbonate in wetter periods as well as its deposition and accumulation in drier periodsClay mineralogical results revealed smectite, kaolinite, illite, chlorite and vermiculite as dominant clay minerals in the study area. Illite, cholorite and kaolinite mainly considered as inheritance fromthe parent materials while pedogenic formation explain the presence of vermiculite. Moreover, smectites was found to have three origins of inheritance, neoformation and transformation and its abundance was increased with depth. The origin of smectite in the buried horizons was attributed to the illite transformation. According to the heavy moisture demand on illite weathering, the occurrence of this process can be associated with more humid condition during the past climate. So the achieved results of present study can be a clue to recognize the climatic changes in the study area.

Maize is one the major utilization type in Gobadloo region where placed in East Azarbaijan porivince, North-West of Iran, so performance of land suitability evaluation and land production potential prediction are very important for knowing environmental limitations and planning proper cultivation. FAO guidelines on the land evaluation system were widely used for the land suitability, so soil morphological and analytical data were carried out for 16 land units. Then, based on AEZ model, radiation thermal production potential for Maize was estimated and then soil indices which indicate the extent of soil limitations effectiveness on production reduction, was calculated by the square root formulas. Finally land production potential was calculated by multiplication of the soil indices and radiation thermal production potential. The results reaveald that parametric methods (square root and storie formulas) uncorrected land indices had lower values than which what it was expected in real conditions. For solving this problem land indices were corrected and the results improved land suitability classes. Coefficient of correlation values between land production potential and observed yield were 0.79, 0.84, 0.86 and 0.9 for uncorrected storie, uncorrected root mean square, corrected storie and root mean square models respectively. Based on the results, can conclude that Mean Absolute Error is able to predict yield better than that other methods because of higher regression coefficient and lower error.

Sugar beets are used primarily for production of sucrose, a high energy pure food. The identification of suitable locations for the production of this valuable plant is of crucial importance. In this regard, land evaluation suitability determination spatial Mediterranean land evaluation method is one of the main management procedures in sustainable agriculture for planning. The purpose of this research is using Mediterranean land evaluation to land suitability evaluation for sugar beet in an area with 7990 ha extension, which is located in North of East Azerbaijan province (Golfaraj-Jolfa). The goal of this study is land planning of Golfaraj (Jolfa), thus soil morphological and analytical data were carried out for 17 land units. Based on each model effective parameters, bioclimatic deficiency, land capability and qualitative land suitability were determined using above mentioned models. The result of Terraza model showed that rainfed cultivation is possible with 20-40 percentages in yield for sugar beet. Also, considering some of the management recommendation such as identifying the sensitive time of crops for irrigation, reduce the water consumption without any negative impacts on annual yield. According to Cervatana model results, total area was distinguished as good. Therefore, qualitative land suitability evaluation of susceptible lands using Almagra model revealed that 24.3, 39.9, 8.1 and 27.7 of total area can take place in excellent (S1), suitable (S2), moderately suitable (S3) and unsuitable (S4,S5) respectively by soil texture and carbonate. In summary, MicroLEIS DSS tool appears to be useful in semi-arid regions, such as Golfaraj area located in East Azerbaijan (Iran), to formulate sustaining agro-ecological systems.

For design and implementation of soil conservation programs, accurate and optimized mapping of soil properties is required. The type of interpolation method is one of the most important issue involved in mapping soil properties. Six ordinary methods of spatial interpolation were compared to determine their suitability for estimating some quality properties of topsoil including clay content, electrical conductivity, equivalent calcium carbonate and organic carbon in the Naqade region farmlands located in west Azerbaijan. The area of study region was about 8300 ha. For this purpose, 282 topsoil samples were collected randomly and tested for laboratory analysis. Deterministic methods (radial basis function and global polynomial interpolation) as well as geostatistical estimators (ordinary Kriging) were utilized to map related soil properties. The highest and lowest CV was obtained for EC and clay content variables, respectively. For clay and electrical conductivity, the exponential model, for equivalent calcium carbonate the Gaussian model, and for organic carbon the spherical were the best fitting models to calculate the experimental variogram. According to the results, the ordinary Kriging approach characterized with the minimum error indicator of bias-variance trade-off (BVTO) for evaluating clay, electrical conductivity, equivalent calcium carbonate and organic carbon. The thin plat spline model of radial basis function showed the maximum error in assessment of studied attributes. Eventually, the interpolation maps were generated regard to the most appropriate interpolators.