مجله مدیریت خاک
سال دوم شماره 2 (پیاپی 3، پاییز و زمستان 1392)

Prediction of the rate of water infiltration into the soil and its influencing factors is the most important issues in the management of soil resources. In this study, the infiltration rate of the soil was estimated using 3 methods of artificial neural networks (ANN), Adaptive neuro fuzzy inference system (ANFIS) and genetic algorithm neural networks (GA-NN). The input data to all three methods in 8 information structurs including physical and chemical characteristic of soils from 60 sampling points in Ghezel Ozan river of Zanjan province. Evaluation results based on the statistics model of, root mean square error (RMSE), correlation coefficient (r) and mean absolute error (MAE) and the coefficient of performance. Statistics RMSE, MAE, and r in the best GA-NN architecture, respectively, 0.27, 0.15 and 0.99. This algorithm improved results 82.2% and 85.2 % compared to ANFIS formation and 48.1 % and 21.1% compared to ANN with 1-4-9 structure. Similarly, the coefficient of performance of the GA-NN structure, 0.996, ANFIS 0.863 and ANN 0.984, respectively, which reflects the performance of GA-NN. The Comparison of results of T- Student test from each of the three methods is in the 0.05 and 0.01, indicating no significant difference between the 8 structures. So, in 8 structure with three neurons including the percentage of soil particles.

Adopting different systems in soil cultivation after ignorant and non-scientific approaches regarding land use change leads to physical and chemical changes in soil properties especially in agricultural lands on steep slops. This research has been done by the aim of study of landscape position and landuse on physicochemical soil properties and microbial respiration of soils on in Lordegan hill-land under two landuses: dryland and forest. In this way sample from a hill with five part of slope (including: summit, shoulder, back slope, foot slope, toe slope) in two kinds of land use, forest and dryland were collected. The results showed that available K and P, clay, total nitrogen, organic carbon content, in both of land use had been increase through the lower part of slope and CEC at forest land use had been increase of the summit to back slope. soil pH in two kinds of land use decreasd from up to the down of the slope. Comparison of mean of microbial respiration index in both kinds of land use showed that more soil microbial respiration in forest land use than other, which in both, the two kinds of land use were increased through the lower part of slope because of accumulation of organic matter. Overall, relief, plant community, slope position and land-use are influence on soil erosion and leaching.

Information about distribution and availability of copper (Cu) in calcareous soils treated with sewage sludge and after wheat planting is essential in management of sewage sludge application. This study was performed to evaluate Cu availability (using 3 extractants) and its fractionation in 10 calcareous soils of Chaharmahal-Va-Bakhtiari province before and after treated with sewage sludge (1% w/w) and also after wheat plantation in greenhouse conditions. The results of this study showed that among 3 extractants, mean of Cu extracted by Mehlich 3 increased (27%) significantly (P<0.05) after sewage sludge application and decreased (34%) significantly (P<0.05) after planting. After sewage sludge application and planting, Cu-fractions were changed significantly (P<0.05). After sewage sludge application, mean of Cu exchangeable, Cu associated with carbonates, Cu associated with iron-manganese oxides, Cu associated with organic matter and residual increased 89, 22, 17, 26 and 6%, respectively. After wheat planting in treated soils, mean of exchangeable Cu, Cu associated with carbonates and Cu associated with iron-manganese oxides decreased 65, 73, 17, and 11%, respectively and Cu associated with organic matter (47%) and residual Cu (8%) increased. The results of the present research showed that difference in supplier Cu fractions could be used to describe difference for Cu extracted with one-step methods after treatment.

Pedotransfer functions are used increasingly to predict the cation exchange capacity (CEC), because, its measurement is difficult, costly and time-consuming. The 129 soil samples were collected from Hamedan and Guilan provinces. The soil particle size distribution, organic matter, CEC, pH and mean weight diameter (MWD) have been measured. In addition to conventional predictors of soil CEC, MWD have been used to predict CEC and their capability in the improvement of CEC predictions by regression and artificial neural networks (ANNs) have been evaluated. The results showed that entering MWD improved the accuracy of the models from 6 to 46 %. The indirect relationships between MWD and CEC were the reason for this improvement. According to root mean square error, ANN models performed better than regression models in the prediction of CEC in training step but, the different results were found in the testing step for most of the models. Therefore, MWD is the suitable predictor for the estimation of soil CEC by regression and ANNs methods.

The effect of land use change on some chemical and physical properties of disturbed and undisturbed lands were studied in Golestan province. Two hundreds and twenty soil samples were collected from surface layer of soils. Some soil properties such as Na, K, Ca, Mg, available P, S, soil electrical conductivity, pH, CCE, organic carbon percentage, cation exchange capacity and particle size distribution were measured in all soil samples. Statistical analysis were also performed on the data and the results showed that change in land use from pastures to agriculture lands did not show any significant changes on Ca, Mg, P, CCE, pH, EC and soil organic carbons; whereas Na, K, S, soil cation exchange capacity, clay, silt and sand contents showed significant changes due to the land use change. Correlation coefficients of the most effective factors were also calculated. The results showed that sodium and sulfur were the most correlated factors with soil electrical conductivity and calcium were found to be the most correlated factor with CCE percentage. Also, clay percentage, organic carbon and CCE were shown the stronger correlations with soil cation exchange capacity, than other factors.

This study was conducted to investigate the status of soil potassium including different K forms, in soils and their relation to chemical and mineralogical properties of soils in soil orders and different physiographies unites of Kaftar region, Fars province. The study showed that the region soils were in four soil orders: Alfisols, Vertisols, Inceptisols and Entisols. Smectite, chlorite, illite, quartz, and interstratified minerals were detected in the clay fraction of the studied soils. The average of soluble, exchangeable, non -exchangeable, structural, and total K in the studied soils were 3.22, 510, 1013, 5568 and 7095mg kg-1, respectively. The average amount of soluble K in surface and subsurface horizons in low land physiography and exchangeable and non-exchangeable K in piedmont plain were higher than the other physiographies units, and the content of total and structural K in Alfisols were higher than the other soils. Also, there were significant differences between K pools in different soil orders. Comparison of K forms distribution between different soil orders revealed that Vertisols and Alfisols had higher amounts of different forms of K than those of other soil orders. Also, the amounts of K pools were lower in Entisols than other soil orders.