javad seyedmohammadi

The soil units in the irrigated plains across the country were identified based on previous soil studies, satellite images, land use maps, and agricultural-climatic zones. The purpose was to determine the land potential for irrigated cultivation of industrial crops such as sugar beet, cotton, safflower, and sugarcane. Then, the FAO framework and the square root parametric method were used to evaluate the land suitability for irrigated cultivation of these crops. The survey results revealed the land suitability classes for four crops under irrigated cultivation: sugar beet, cotton, safflower, and sugarcane. For sugar beet, out of 4 million hectares (Mha) of surveyed land, 1.23 Mha were in class S1 (highly suitable), 1.5 Mha in S2 (moderately suitable), 740 thousand hectares (Tha) in S3 (marginally suitable), 390 Tha in N1 (currently suitable), and 420 Tha in class N2 (permanently suitable). For cotton, out of 2.4 Mha of surveyed land, 75 Tha were in class S1, 671 Tha in S2, 895 Tha in S3, 420 Tha in N1, and 340 Tha in N2. For safflower, out of 2.2 Mha of surveyed land, 38 Tha were in class S1, 56 Tha in S2, 1.3 Mha in S3, 363 Tha in N1, and 398 Tha in N2. For sugarcane, out of 615 Tha of surveyed land, 6 Tha were in class S1, 18 Tha in class S2, 193 Tha in class S3, 98 Tha in class N1, and 300 Tha in class N2. The data was statisticaly analysed and the results indicated that the the land suitability classes were classified with resonable accuracy. The following factors were the main limiting characteristics that limited cultivation of the four crops under irrigation: For sugar beet: soil pH, salinity, alkalinity, and drainage; for cotton: climate, slope, salinity, alkalinity, lime and gypsum; for safflower: pH, drainage, salinity, alkalinity and climate; and for sugarcane: salinity, alkalinity, drainage and slope. Due attention to the prepared land suitability maps of the aforementioned crops would facilitate cultivation management for farmers and planners.

Climate has an important role in agricultural activities and can be examined from two perspectives. First, what locations are suitable for a specific plant, and second, what plants are suitable for a climate. The latter approach is less considered; thus in this study, it has been investigated by introducing a standard method (Sys method). The study area is located in Mako city. Climatic suitability evaluation was performed by numerical (parametric) method using the Maku Synoptic Station data for pistachio, almond, pears, plum, sour cherry and sweet cherry. The findings showed that except for pistachio, with marginally suitable class (S3), other plants were classified as moderately suitable class (S2) but the value of climatic index for each crop was different. The introduced method made it possible to identify the most important effective climatic factors for the cultivation of each plant and determine the most limiting factor in the phenological period. Such findings showed that there is a close relationship between crops, phenological period, climatic characteristic and location. Based on this, the most suitable plant or plant species can be selected for a region, using the phenological period of the plant and climatic characteristics. However, for sustainable development, other components of the land, such as soil and/or topography, should also be evaluated. In general, the introduced approach can be used as an efficient tool, both for choosing the most suitable plants in a climate and for choosing the most suitable place (in terms of climate) for specific plants.

In recent years, the increased of greenhouse gases due to agricultural activities has been significant. The purpose of this study is to investigate the extent of carbon dioxide and methane emissions in agricultural lands of Semnan province and Bastam region, including: apricots, grapes, wheat, barley, corn, forage and pastures.

For this purpose, soil samples were taken from a depth of 0-30 cm. Soil properties including salinity, pH, percentage of sand, silt and clay, organic matter, total nitrogen, phosphorus, potassium and calcium carbonate were measured. Closed static chambers were used for gas sampling and in each cultivated and used product, 3 to 5 points and total of 31 points were selected. Finally, the amount of greenhouse gas, global warming potential and environmental costs were calculated.

Based on the results, the highest carbon dioxide emissions were observed for fodder corn in autumn with an average of 3 g / m2 / day and the lowest emissions for pastures in autumn with an average of 0.25 g / m2 / day. For methane gas, the results showed that forage corn in the two autumn seasons had the highest gas emissions with an average of 3 g / m2 / day and the lowest emissions for pastures in autumn with an average of 1.03 g / m2 / day.

For the proper use of water resources and prevention of soil degradation, it is necessary to select the best irrigation system. The aim of this study was to map the land suitability evaluation for different irrigation methods (surface and drip) in 46000 ha of Sistan plain including Hirmand, Hamon, Nimroz, Zahak, and Zabol counties. For this purpose, 600 pedons with an approximate distance of 700 to 800 m were excavated, described, and sampled. In this study, land suitability evaluation for different irrigation methods based on soil properties and topography was done using the parametric method. Then, land suitability maps for surface and drip irrigation methods were prepared using the Inverse Distance Weighting (IDW) method. The results showed that in the studied area, the conditions for drip irrigation are better than the surface irrigation method. However, in many studied areas, there are restrictions for drip irrigation, and for proper and efficient use of this irrigation system, the restrictions must be removed. Moreover, the results confirmed that in all studied areas the most important limitations are salinity/alkalinity and limitations due to physical soil properties. The silty clay and silty loam textural were the most limitation classes. Due to the fact that changing the physical properties is not easily possible, it seems that soil remediation based on salinity and alkalinity can help to remove or reduce the limitations.

Land suitability classification is a useful management method to ensure using the planned and sustainable agricultural land according to their potential. Therefore, the suitability of irrigated plains in Iran was evaluated for wheat, barley, grain maize, rice and triticale in the years 2017 to 2022. The results showed that 1.4 million ha of the studied lands for wheat are in highly suitable class (S1), 2.8 million ha in moderately suitable class (S2), 1.39 million ha in marginally suitable class (S3), lands with an area of 524,531 ha in currently unsuitable class (N1) and 199,503 ha in permanently unsuitable class (N2). For barley, about 1.3 million ha are in S1 class, 2.2 million ha in S2 class, S3 class lands with an area of 1.3 million ha, about 501 thousand ha in N1 class and 489 thousand ha in N2 class. About 39 thousand ha for grain maize are in S1 class, 1.1 million ha in S2 class, S3 class lands with an area of 1.6 million ha, 853 thousand ha in N1 class and 999 thousand ha in N2 class. For rice cultivation, there are 310 thousand ha of land in S2 class, S3 class lands with 1.5 million ha, 877 thousand ha in N1 class and 949 thousand ha in unsuitable N2 class. There are 127,000 ha of land for Triticale in S1 class, about 549,000 ha in S2 class, 323,000 ha of land in S3 class, about 97,000 ha in N1 class and 83,000 ha in N2 class. Statistical analysis of the data showed that the separation of land suitability classes for all crops has acceptable accuracy. The main limiting characteristics were; texture, salinity/alkalinity, slope, drainage and in some areas climatic characteristics. With regard to the distinction of suitable and unsuitable lands, the application of the obtained results can be effective into correct programming for sustainable exploitation, production and cultivation pattern development.

Land suitability studies of Iran have been scattered and few of them have investigated specifically land suitability for agriculture. Indeed, most of the studies have been conducted locally and, so far, comprehensive studies have not been done at the country level. Determining the suitability of Iran’s agricultural lands for production of crops is one of the most important tools for the optimal use of soil resources. For this purpose, by consolidating, preparing and digitizing soil survey and classification studies in the country and according to satellite images and land use maps and considering agro-climatic zones, soil units were identified to determine the potential of land for irrigated wheat in the irrigated plains of the country. Then, by entering the climate, soil and topographic data in the prepared software based on the FAO approach and parametric square root method, the suitability of all soil units was assessed for irrigated wheat. The results show that, in the irrigated plains, 1.4 Mha of land is in S1 class, 2.08 M ha are in S2 class, 1.4 Mha in S3 class, and 524 thousand ha have currently unsuitable class (N1), with 503 thousand ha being permanently unsuitable (N2). Statistical analysis of the data showed that the separation of land suitability classes has acceptable accuracy. The main limiting characteristics of lands are the soil physical properties including texture, salinity and alkalinity, slope, drainage, and in some areas, climatic characteristics. Due to the comprehensive map of land suitability and differentiation of suitable lands from the unsuitable ones, application of the results obtained with ideal management and usage of irrigated lands in the country will lead to the conservation of land resources, especially soil and sustainable production. Notably, the above results are the basic information layer that along with other aspects including economic issues are needed for developing  a suitable cropping pattern.

The objective of this study was to investigate the effect of soil and land characteristics on saffron yield, their rating for preparation of a soil requirements table of this plant for land suitability studies by FAO method. First, 124 saffron farms in Khorasan Razavi, South Khorasan, Fars, Golestan, Markazi and Kerman provinces were selected. In each field, suitable soil samples were taken and a land use questionnaire was completed during three years from 2017 to 2019. Soil samples were tested to determine their physicochemical properties. After preparing the data, they were statistically analyzed. Multivariate regression between yield as a dependent variable and salinity, percentage of exchangeable sodium, soil reaction, gypsum, lime, clay, sand, silt, gravel and available potassium and phosphorus of soil were studied as independent variables by stepwise method. By examining the relationships of simple regression between important and effective land characteristics and yield, land characteristics rating was performed. Then, the saffron soil requirements table prepared. The proposed table was verified with the data of 21 new farms. The results showed that available potassium, sand, soil salinity, percentage of exchangeable sodium and lime had the highest and the reaction of soil and organic carbon had the lowest range of changes. Regression results showed that the independent variables of soil salinity, ESP, lime, gypsum, gravel and available potassium and phosphorus, respectively, affect yield. Coefficient of determination of multivariate regression showed that the variables entered in the model were able to determine 95% of the variance related to the dependent variable. The largest contribution to the reduction of saffron yield is related to soil salinity, gravel, exchangeable sodium percentage and the amount of lime. Validation results showed that the yield correlation coefficient with the soil index of the proposed table for saffron is about 0.92, which indicates the acceptable accuracy of the proposed table.

Identifying land potential and suitability based on soil characteristics is one of the appropriate management tools to increase sustainable land use. The objective of this study was to investigate the effect of soil characteristics on fig yield, their rating and the preparation of vegetative requirements table of this plant for land suitability studies by FAO method. Therefore, 94 fig orchards were selected in Fars, Lorestan, Kermanshah and Kerman provinces. In each orchard, a soil profile was studied, a land use questionnaire completed and physical and chemical tests performed on soil samples. The values of soil characteristics were calculated by applying weighting factors with depth in the profiles and multivariate regression between yield and soil characteristics was investigated by stepwise method. The high coefficient of determination of the multivariate model (R2= 0.89, P<0.01) showed that the variables entered in the model were able to determine 89% of the variance related. The results showed that among the measured soil characteristics, the effect of salinity, alkalinity, amount of lime, gypsum, gravel, available phosphorus and potassium was significant on fig yield. Finally, according to the results, soil salinity, alkalinity, amount of gypsum, lime and gravel had a decreasing effect and organic carbon, available phosphorus and potassium had an increasing effect on fig yield.

Accurate assessment of land suitability for agricultural production plays an important role in reducing the effects of land degradation. The aim of this study was to apply fuzzy, AHP and GIS techniques to determine the degree of land suitability for wheat production in lands of about 61,000 ha located in Qazvin plain. By Investigating the land use maps, geology, topography, slope and satellite image of the region, the delineation of primary soil units was separated, then in the separated units, profiles were excavated and described, and soil horizons were sampled. Based on the characteristics of representative profiles in each map unit, land suitability assessment for wheat cultivation was performed using fuzzy method with AHP and square root method and land suitability map was prepared in GIS environment. According to the results of AHP-fuzzy method 48169.1 ha (78.2%) of the land are moderately suitable (S2), 9086 ha (14.7%) marginally suitable (S3) and 4346.3 ha (7.1%) currently unsuitable (N1). The most important limiting characteristics were slope, pH, ESP, drainage and soil salinity. The results showed that the fuzzy method integrated with AHP was able to evaluate accurately with high value of determination coefficient between land index and yieldcompared to the parametric method of the square root and the modified square root due to determining the appropriate limits of critical points, suitable weights for characteristics, use of fuzzy logic relations and principles and suitable membership functions. Therefore, the mentioned integrative method can be an accurate and effective method for better planning and management of land use for agricultural production.   Identification of Land Potential and Characterizing Limitations for Irrigated Wheat Cultivation in a Part of Qazvin Plain Land Using Fuzzy and AHP Techniques

Iran is one of the major date-producing countries and not only has a long history in this field, but also it currently has the second grade of Date production in the world. Therefore, the cultivation and production of Dates in Iran is of particular importance both nationally and for the inhabitants of the producing provinces. In this regard, planning for optimal utilization of production resources such as soil and lands for development of the yield in the country has a special place. Consequently, evaluation of land suitability and utilization of lands in proportion to their potential and capacity for specific land use seems an important solution. However, one of the necessities of land suitability assessment is to determine the crop requirements of the plants such as the status of the soil as a production bed. The objective of this study was to investigate the effect of soil characteristics on Date yield and their rating for use in land suitability evaluation studies.

First, 91 palm Date orchards were selected with diversity of soil and yield in Kerman, Fars, Khuzestan, Hormozgan and Bushehr provinces, in each garden, a soil profile was studied and a land use questionnaire completed. Physicochemical and fertility analyses were carried out on the collected soil samples. Multivariate regression was investigated between yield as dependent variable and independent variables including salinity, percentage of exchangeable sodium, pH, gypsum, calcium carbonate equivalent, clay, sand, silt, gravel, available potassium and phosphorus by stepwise method. Then, by checking the relations of simple regression between the important and effective characteristics with yield, related equations and diagrams were drawn and the rating of land characteristics set. The proposed crop requirement table was evaluated and validated using soil and yield data of 20 orchards.

Results showed that potassium, sand percentage, soil salinity, ESP and CaCO3 had the highest and soil organic carbon content and pH had the least variation. Maximum amount of lime and gypsum was 74 and 17% and soil texture varied from sandy to clay, respectively. Regression results showed that independent variables including soil salinity, ESP, CaCO3, gypsum, gravel, available potassium and phosphorus were effective on yield, respectively. The determination coefficient of multivariate regression indicated that the variables entered into the model can determine 79% of the variance related to the dependent variable. In simple regression equations, soil salinity, ESP, gypsum, CaCO3 and gravel had a decreasing effect and organic carbon, available phosphorus and potassium had increasing effect on yield. The highest contribution to the decline in Date yields was related to soil salinity, gravel, ESP and calcium carbonate.

The coefficient of determination between yield and soil index obtained from the proposed soil and landscape requirements table for the Date was about 0.79 which showed acceptable accuracy of the prepared table. Soil salinity, ESP, gypsum and calcium carbonate limit for Date palm were determined 8 dS/m, 12, 8 and 38 percent, respectively.

Pistachio is one of the most important and valuable orchard products in Iran, and its compatibility with unfavorable growth conditions, especially drought and salinity, causes its high production in the country. The study aim was to investigate the effect of soil characteristics on pistachio yield and their rating for applying in land suitability assessment studies. So, 124 pistachio orchards were selected in Kerman, Fars, Khorasan-Razavi, Isfahan and East-Azarbaijan provinces. In each orchard, a soil profile was studied and a land use questionnaire completed. After the necessary physical and chemical analyzes, multivariate regression was performed by the stepwise method between yield (dependent variable) and different soil characteristics (independent variables). By creating simple regression relations between effective soil characteristics on yield, the characteristics rating was determined for different land suitability classes. The results showed available potassium, salinity, ESP, sand and CaCO3 had the highest variation, and pH, organic carbon and available phosphorus had the lowest one. The results of stepwise regression showed the input of salinity, ESP, gypsum, CaCO3, gravel, available phosphorus and potassium to the equation were significant (P<0.01). The variables entered into the regression model with NRMSE=0.280 determined 75% of the variance related to the dependent variable (yield). In simple regression relations, salinity, ESP, gypsum, CaCO3 and gravel had negative influence and organic carbon, available phosphorus and potassium had positive influence on yield. The validation of soil variables ratings with R2=0.82 and NRMSE=0.224 distinguished acceptable accuracy of the proposed table which can be confidently applied for use in land suitability assessment.

Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Analytical Hierarchy Process (AHP) methods are important research fields for soil sustainable management and suitable usage that have been developed in the recent decade. In the present research work, these methods along with Square Root method have been used for determination of cultivation priority of wheat, barley and maize in 12000 ha of Dasht-e-Moghan with 167 soil profiles. After soil sampling and analysis, the data of soil texture, percentage of particles larger than sand, soil depth, lime, gypsum, available water capacity, pH, OC, available P and K, CEC, ESP, slope, flooding, drainage and region climate in different land units were produced by weighted coefficients. Besides soil classification, finally eight properties of soil depth, lime, gypsum, pH, EC, ESP, slope and climate were selected for calculation of cultivation priority determination. Principal component analysis and Euclidean distance methods applied for selection of the effective properties on crops yield for application in priority determination methods and the criteria weights determined via pair-wise comparison matrix method. In all three methods cultivation priorities in land units were allocated to barley, wheat and maize respectively except in units 13 and 16, because of pH limitation. Multivariate variance analysis was used for comparison of the methods difference and the results revealed significant difference of all the three methods at 0.05 probability level. Allocated score mean values were calculated as 0.390, 0.381, 0.229 in TOPSIS, 0.380, 0.353, 0.267 in Square Root and 0.341, 0.337, 0.322 in AHP for barely, wheat and maize respectively and mean comparing of crops scores with LSD test showed the TOPSIS better accuracy than the others, which was related to twin comparing nature of alternative (crop) from positive and negative ideal, data standardization with Euclidean norm method, using mathematical equations and matrixes as well as suitable weights.

Direct measurement of some soil properties may be difficult, costly and time consuming. So, these properties can be predicted usefully using easily available data. Soil cation exchange capacity (CEC) is a vital indicator of soil fertility and pollutant sequestration capacity. Soil hydrodynamic properties drive the flow of water in the soil-plant-atmosphere system, and hence control processes such as aquifer recharge or nutrient fluxes between soil and vegetation. Knowledge of soil hydrodynamics is important for modeling physical processes related to soil water content. Despite great advances in measurement methods, it is still difficult to determine soil hydraulic properties accurately, especially for undisturbed soils and in the dry range. However, the measurement of the soil hydraulic properties and CEC is time-consuming, labor-intensive and expensive. That is why, the present study aimed to develop pedotransfer functions (PTFs) for the estimation of field capacity (FC), permanent wilting point (PWP), and CEC of the soils of Guilan province.
Study area is located in south of Guilan Province, Gilevan region, northern Iran. The climate is aridic. The annual precipitation is 245 mm, and the average temperature is 18 °C. A total of 240 soil samples from 0-30 cm layer of this region were collected. Then, both difficulty and easily available properties such as clay, sand and silt percent, CaCO3, organic matter, bulk density and gypsum were measured. The first step for using statistical methods is to study the normality of data. In order to know whether the data were normal, Kolmogorov-Smirnov test was used. Data were divided into two groups of test (%25) and train (%75). This division carried out in such a way that statistical characteristics of two groups such as minimum, maximum, standard deviation, etc. were similar. Then regression and artifitial neural network (ANN) models set on training data. For prevention of error in ANN process, data converted in standard scale from 0.1 to 0.9. Multi-layer percepteron, feed forward backpropagation, and Levenberg-Marquardt functions were used for extension of ANN. Relative root mean square error (RMSE), determination coefficient (R2) and model efficiency factor (MEF) criteria were used for evaluation of models.
In regression analysis, for CEC, clay and organic matter percent, in FC moisture content, clay, silt as well as bulk density, and for PWP, clay percent showed significant effects in created models. Coefficients of determination in created linear models for CEC, FC and PWP were 0.72, 0.84 and 0.73, respectively.While these coefficients for non-linear models were 0.78, 0.87 and 0.74 for CEC, FC and PWP, respectively. The best PTFs for prediction of difficulty available properties in ANN obtained by multi-layer perceptron model with 2 hidden layers, 8 neurons for FC and PWP, 6 neurons for CEC and considering all inputs. Coefficients of determination for CEC, FC and PWP were 0.98, 0.99 and 0.98, respectively. ANNs designed for prediction of difficulty available properties with inputs include soil easily available properties that have the most sensitivity coefficient with difficulty available property. Test results of these models were similarity non-linear regression models. The results of models compared with test data showed that the models obtained from ANNs were more accurate than the regression model.
In regression method, non-linear models for prediction of soil difficulty available properties were more accurate than linear models. In ANNs, models with inputs including all of the soil easily available properties were more accurate than models with inputs include soil easily available properties that have the most sensitivity coefficient with difficulty available property.

With regard to increasing population of country, need to high agricultural production is essential. The most suitable method for this issue is high production per area unit. Preparation much food and other environmental resources with conservation of biotic resources for futures will be possible only with optimum exploitation of soil. Among effective factors for the most production balanced addition of fertilizers increases production of crops higher than the others. With attention to this topic, determination of soil fertility degree is essential tobetter use of fertilizers and right exploitation of soils. Using fuzzy logic and Analytic Hierarchy Process (AHP) could be useful in accurate determination of soil fertility degree.
The study area (at the east of Rasht city) is located between 49° 31' to 49° 45' E longitude and 37° 7' to 37° 27' N latitude in north of Guilan Province, northern Iran, in the southern coast of the Caspian sea. 117 soil samples were derived from0-30 cm depth in the study area. Air-dried soil samples were crushed and passed through a 2mm sieve. Available phosphorus, potassium and organic carbon were determined by sodium bicarbonate, normal ammonium acetate and corrected walkly-black method, respectively. In the first stage, the interpolation of data was done by kriging method in GIS context. Then S-shape membership function was defined for each parameter and prepared fuzzy map. After determination of membership function weight parameters maps were determined using AHP technique and finally soil fertility map was prepared with overlaying of weighted fuzzy maps. Relative variance and correlation coefficient criteria used tocontrol groups separation accuracy in fuzzy fertility map.
With regard to minimum amounts of parameters looks some lands of study area had fertility difficulty. Therefore, soil fertility map of study area distinct these lands and present soil fertility groups for better management of soil and plant nutrition. Weight of soil parameters was0.54, 0.29 and 0.17 for organic carbon, available phosphor and potassium, respectively. Fuzzy map of study area includes five soil fertility groups as: 22.9% very high fertility, 27.7% high fertility, 35.53% medium fertility, 10.48% low fertility and 3.39% very low fertility. Consequently, a separated map for soil fertility prepared to evaluate soil fertility of study area for rice cultivation. Toinvestigatethe efficiency of fuzzy model and AHP in increasing the accuracy of soil fertility map, soil fertility map with Boolean method prepared as well. Boolean map showed 58.88% fertile and 41.12% unfertile.15 soil samples from different soil fertility groups of study area were derived fromcontrol of maps accuracy. 13 renewed samples of 15 and 9 soil samples have matched with fuzzy and Boolean map, respectively. Comparison of parameters mean in fuzzy map fertility groups showed that parameters mean amounts of very high and high fertility groups are higher than optimum level except potassium that is a few lower than optimum level in high fertility group, therefore, addition of fertilizers in these groups could not be useful to increase rice crop production. Phosphorus parameter amount is lower than the critical level in very low, low and medium fertility groups, then in these groups phosphorus fertilizer should be added to the soil toincreaserice production. The amount of potassium parameter is higher than the critical level and lower than optimum limit in very low, low, medium and high fertility groups, then in these groups addition of potassium fertilizer will results in theincrease of production. Organic carbon amount is lower than optimum level in very low and low fertility groups. With regard to the relation between organic carbon andnitrogen and phosphorus, therefore, the addition of organic carbon fertilizer could compensate deficit of nitrogen and phosphorus in these groups as well. Attention to the presented explanations and comparison of fuzzy and Boolean maps using parameters amounts in renewed sampling points for control of maps accuracy, it is distinct that fuzzy logic could influencetheoptimum using of fertilizers with increasing map efficiency and accuracy. In addition, relative variance and correlation coefficient amounts showed that fuzzy map has separatedquite wellparameters changes.
Effective parameters in soil fertility, includingorganic carbon, phosphorus and potassium were used topreparesoil fertility map for rice cultivation. With regard to the minimum amounts of parameters looks some lands of study area had fertility difficulty. Therefore, soil fertility map of study area distinct these lands and presents soil fertility groups tobetter management of soil and plant nutrition. Fuzzy and Boolean methods were used topreparesoil fertility map. Comparison of these two approaches showed that fuzzy method with AHP caused to increase theefficiency and accuracy of fertility map for rice. Separated and distinguish soil fertility groups in fuzzy map help suitable distribution and optimum use of fertilizers for rice production.

Paddy soils are important and the base of agriculture in Guilan province. It is necessary to recognize these soils for understanding of their limitations and optimum use. Unsaturated soil submerging is the cause of collection of chemical and electrochemical process that has significant effects on soil fertility. Eh, rH and pH are important indexes that are used to investigate oxidation and reduction condition in submerged soils and have abundant effects on activity and sorption rate of nutrients. Decrease of Eh and rH in poorly drainage of paddy soils affects availability and solubility of nutrient. Different Fe forms are used for analysis of soils evolution trend and submerging influences on changes of Fe forms. The aim of the present study was conducted to investigate the effect of redox potential changes on soil characteristics and analysis of soils evolutional trend in different physiographic units.
The study area with 40000ha (at the east of Rasht city) is located between 49° 31' to 49° 45' E longitude and 37° 7' to 37° 27' N latitude in North of Guilan Province, Northern Iran, in the southern coast of the Caspian sea with different water table depth. The climate of the region is very humid with the mean annual precipitation of 1293.6 mm. The mean annual temperature is 15.8°C. The soil moisture and temperature regimes are Aquic, Udicand Thermic, respectively. The parent materials are derived from river sediments. The soils formed on the plateaues and upper terraces, river alluvial plain and lowland physiographic units were classified as Inceptisols and the soils formed on coastal plain physiographic unit as Entisols. Air-dried soil samples were crushed and passed through a 2mm sieve. Particle-size distribution, organic carbon and cation exchange capacity were determined by hydrometric, wet oxidation and ammonium acetate methods, respectively. Eh by Eh electrode, total iron, free iron and amorphous iron were determined using nitric acid, dithionite-citrate-bicarbonate and ammonium oxalate methods, respectively. The means of different Fe forms values compared through LSD test.
It can be seen especial morphological and physicochemical characteristics in studied paddy soils with high groundwater table due to artificial submerging in rice growing seasonDifferent Fe mottles such as orange mottles include lepidocrocite mineral was observed in studied soils. Low redox potential with average 145/7mV and rH with average 19.6 in lowland and coastal soils implicate intense reduction condition. In lowland soils Eh was lower than other units and it was lower in top horizons than to sub horizons in all of units. Eh index had inverse relationship with organic matter, because of high organic matter amount caused high activity of anaerobic micro-organisms, increase of iron reduction and reduction soils degree decrease. rH index amounts showed that studied soils had reduction condition and presence of brown iron and black manganese minerals proved this condition. CEC was high in top soil of physiographic units due to high amount of organic matter and clay content. Clay particles in plateaues were lower than other units because of alteration and suitable aeration and showed high evolution in these soils. Clay coatings were not observed due to high ground water table and its alternative fluctuation. Results showed amorphous iron in surface horizons with average amount of 24.3g kg-1 was higher than subsurface in all soils and had positive correlation with organic matter, because of high activity of anaerobic micro-organisms that prevent from transformation of amorphous iron to crystallized iron, therefore amorphous iron amount increased in presence of organic matter. Pedogenic iron was high in A and B horizons with regard to BC and C horizons due to aeration and weathering. In lowland and coastal land Fed was lower than plateaues and upper terraces and river alluviums units because of ground water presence and its alternative fluctuation. Fed-Feo index showed crystallized iron oxides, high amount of Fed-Feo index proved soils evolution and high weathering. Feo/Fed ratio was related to amorphous pedogenic iron and high amount of this index showed few evolution of soil. Fed/Feo and Fed-Feo indexes indicated the lower rate of crystallized iron with average 6.8g kg-1 in lowland and coastal soils and implicated the lower evolution of these unit's soils, due to higher surface groundwater and its more fluctuation than soils of plateaues, upper terraces and river alluviums unites with average amount of crystallized iron 15/8g kg-1.The comparison of different Fe forms using LSD method showed significant difference at the 0.01 level for different Fe forms values in different physiographic units.
Submerging, high groundwater table and severe fluctuation caused noticeable changes in morphological, physical, chemical and electrochemical properties of studied paddy soils. Noticeable organic matter amount added to soil and their burial by puddling operation and slow decomposition were effective factors in redox potential changes of studied wet soils. In equal anaerobic condition, more organic matter caused to decrease redox potential in surface horizons of soils with aquic condition and reverse, lower organic matter caused increasing in redox potential. lower amount of Eh and rH proved severe reduction condition in lowland. Investigation of Fed-Feo and Feo/Fed showed that their amount in lowland and coastal land were lower than plateaus and river alluviums, therefore lowland and coastal soils had lower evolution. Mean comparison of different Fe forms values using LSD method showed significant difference at the 0.01 level for different Fe forms in different physiographic units.

Marls are the most talented geological formation of erosion and produce large amount of sediments that annihilate fertile soil and deduct the capacity of dams. Erosion in marls depends on external factors such as distribution of rainfall and internal factors which include soil physical and mineralogical properties. Therefore, the objective of this research was to determine erosion variations because of the changes of physical and mineralogical properties of marls in arid regions of Guilan Province (Gilevan region) located in Northern Iran. The concerned soil physical properties of marly lands were percentage of saturation, surface gravels, sands, silts, clays, fine sands, fine clays, and the level of bulk density, mean weight diameter (MWD) of soil aggregates (dry sieve), liquid limit, plastic limit, activity and ratio of fine clay to total clay. In addition, four samples from Marly soils were prepared for X-ray diffraction analysis. Comparing the average of physical factors with different type of erosion by means of Duncan multiple range test showed that the percentage of clays, fine clays, saturation, and the level of MWD, liquid limit and activity showed significant changes (p<0.05) in some types of erosion, whereas other measured parameters had no significant effect on the form and type of erosion. Furthermore, results of X-ray diffraction showed the presence of smectitic group clay minerals that are dispersive (2:1 clays), in badland and gully areas, while these types of clay minerals were not found in areas with rill and sheet erosion. Hence, with respect to the results of this research, it can be concluded that mineralogical properties such as smectitic clays, as well as some soil physical characteristics such as clay percentage, fine clay and mean weight diameter are the main factors controlling the shape and form of erosion in marly lands of Northern Iran.

Cation exchange capacity and specific surface area are among some of the important soil characteristics the direct measurement of which is laborious، costly and time consuming. Therefore، fractal dimension of particle size distribution has been widely studied in relation with many such dynamic and static processes as transmission of water and solutes، water holding capacity، heat storage and conductivity، etc.، and as a useful parameter، it has been proposed for property estimation as related to soil texture. Throughout the present research، the relationship between fractal dimensions of particle size distributions (Dm) vs. specific surface and cation exchange capacity for 40 soil samples (32 samples for finding the empirical functions and 8 for testing of the derived functions)، from Gilevan region، with textures ranging from sandy to clay and different parent materials were evaluated. The obtained results showed that the value of Dm of the soil samples ranged from 2. 45 to 2. 99; the finer the soil texture، the larger the fractal dimension Dm. The Dm-specific surface area and Dm-cation exchange capacity relationships were described by power functions (R2=0. 87 and 0. 80، (significant at probability level of 0. 01))، respectively. Testing of Dm-clay content، Dm-specific surface area and Dm-cation exchange capacity relationships showed significant correlation (probability level of 0. 01) for the measured vs. predicted data. The results indicated that Dm can be used as an integrating index for estimating the specific surface area as well as cation exchange capacity of soils from particle-size distribution، useful in modelings and simulations.