Reza Sokouti; Hamidreza Peyrowan; Davood Nikkami; Mohammadhossein Mahdian
Abstract
Considering to high distribution of the marly lands in west Azarbaijan province and high sediment yield of such lands, in this research, the relation among the form and the rate of erosion on marls with their erodibility properties were studied. So marly regions of province with the special properties ...
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Considering to high distribution of the marly lands in west Azarbaijan province and high sediment yield of such lands, in this research, the relation among the form and the rate of erosion on marls with their erodibility properties were studied. So marly regions of province with the special properties were recognized and soils were sampled. Soil erodibility indices were determined and analyzed by statistical methods considering the form and the rate of erosion. Also portable rain simulator were used to study of the runoff and sediment yield potential of such soils. Finally the factors affected the soil erodibility were determined by variance analysis. Results showed erosion rate could be classified as moderate. Gully erosion had highest number in Gara-agaj and Gara-tape areas whereas rill erosion had high number in all area of marlly lands. Surface runoff volume ranged between 255 to 577 cm3 in Shabanlu and surface runoff coefficient 0.23 to 0.53 in Gara-tapeh. Maximum yielded turbidity was 180 gr/lit in Gara-Agaj area. Clay ratio was the effective factor to gully form and Surface runoff volume also was the factor to form surface and rill erosion.
Seyede Maryam Bagheri; Mohammadhossein Mahdian
Abstract
Due to the complexity and wide changes in wetlands' environmental factors, pollution monitoring, protection and control of soil quality is deemed to be necessary. Therefore, understanding the spatial distribution of characteristics including the concentration of heavy metals is of great importance. In ...
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Due to the complexity and wide changes in wetlands' environmental factors, pollution monitoring, protection and control of soil quality is deemed to be necessary. Therefore, understanding the spatial distribution of characteristics including the concentration of heavy metals is of great importance. In this context, this study aimed to investigate the spatial variations of copper element as for some chemical properties of Anzali wetland's soil. In this regard, sampling was conducted at 48 sites of the wetland topsoil and copper concentration, pH and cation exchange capacity of their soil was determined. Inverse distance estimators, polynomials, five spline functions including regularized spline, tension spline, multi quadratic function spline, inverse multi quadratic function, thin plates spline and universal kriging and combination of above mentioned and fuzzy methods using cross-evaluation method have been examined in this research. Also, assessment criteria of Mean Absolute Error (MAE), Mean Bias Error (MBE) and Model Efficiency (EF) were used to compare the differences between observed and estimated values and determine the appropriate method. Based on the results, fuzzy tension spline method using the auxiliary variable of cation exchange capacity (least MAE=5.64, percent error=90/11 and EF=0.3) was chosen as the preferred method in copper's distribution mapping. This method decreased the mean absolute error of 50, 56, 56, 53, 53 and 50 percent compared with techniques such as inverse distance estimators, local polynomials, universal polynomials, spline, universal kriging and fuzzy ordinary kriging, respectively. Furthermore, comparing maximum and average values of copper's allowable concentration in this study with the same values in Poland and Australia's soil standards showed that nowadays given to the data obtained from samples, the level of copper element in Anzali wetland's soil is less than the critical level.
Somaiye Moghimi; Yahya Parvizi; Mohammad Hossein Mahdian; Mohammad Hassan Masihabadi
Abstract
Soil organic carbon is one of the most important soil characteristics, and any changes in its content and composition, affects soil physical, chemical, and biological characteristics. Enhancing soil organic carbon improves soil structure, increases water and nutrients in soils, reduces soil erosion and ...
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Soil organic carbon is one of the most important soil characteristics, and any changes in its content and composition, affects soil physical, chemical, and biological characteristics. Enhancing soil organic carbon improves soil structure, increases water and nutrients in soils, reduces soil erosion and degradation and thus greater productivity of plants and water quality are expected in watersheds and ultimately soil and ecosystem reclamation happens. Climatic, topographic and managerial factors affect soil organic carbon content. In local scale, climatic factors have not high efficiency on soil organic carbon and topographic factors play more important role compared to climate on soil organic carbon variability. The objective of this study was to predict and evaluate the effects of topographic factors such as elevation, slope percent, aspect, hill shade, and curvature on the soil organic carbon content of a rangeland in Mereg watershed, Kermanshah, Iran. Stepwise Multi Linear Regression (MLR) and Artificial Neural Network (ANN) were employed to develop models to predict soil organic carbon. AMulti-Layer Perceptrons (MLP) ANN withback-propagationerror algorithm was applied to this research.Theresult showed that themulti linear regression and ANN models explained53and 77percent of the total variability of soil organiccarbon, respectively. The calculated RMSE and MBE were 0.40 and 0 for the MLR and 0.16 and 0.003 for MLP models. Results indicated that designated ANN model with 5-9-1 arrange was more feasible than multi linear regression for predicting soil organic carbon. Elevation with 0.79, hill shade with 0.64 and slope percent with 0.24, were identified as the important factors that explained the variability of soil organic carbon.
Davood Nikkami; Mohammad Hossein Mahdian
Abstract
Rainfall erosivity as one of the major factors of soil erosion is expressed as indexes. The objective of this study is determining the appropriate rainfall erosivity index in Iran and generalizes it by its estimation from more readily available indexes to stations without rainfall intensity data and ...
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Rainfall erosivity as one of the major factors of soil erosion is expressed as indexes. The objective of this study is determining the appropriate rainfall erosivity index in Iran and generalizes it by its estimation from more readily available indexes to stations without rainfall intensity data and to determine the most accurate interpolation method for preparation of its map. For this reason, necessary data were collected from seven soil erosion research plots in Western Azerbyjan, Khorasan Razavi, Zanjan, Semnan, Mazandaran, Markazi, and Yazd provinces, respectively. The rainfall intensities were recorded, as was the sediment yield associated with storm events, and 64 different erosivity indices based on rainfall intensity were computed for these soil erosion research stations. Our founding shows that were the best correlated with sediment than other erosivity index. Further, rainfall erosivity indices, based on the amount of rainfall, were also computed for all soil erosion research plots and synoptic and climatic stations. The results showed that the modified Fournier index had a significant correlation with After normalizing the primary data, semi-variograms were determined and the best model was obtained. Then, different interpolation methods were compared and spline was chosen for drawing the rainfall erosivity map. The output map showed a decreasing trend from west and north to east and south of the country and this trend was correlated with climatic change from humid to semiarid regions.
Davood Nikkami; Hadi Chamheydar; Mohammad Hossein Mahdian; Ebrahim Pazira
Abstract
Environmental and economic impacts of soil erosion are due to improper land management in a watershed. Although it is impossible to stop soil erosion completely under natural conditions, there is a great need to control erosion for proper land use planning. According to the scarcity of literature in ...
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Environmental and economic impacts of soil erosion are due to improper land management in a watershed. Although it is impossible to stop soil erosion completely under natural conditions, there is a great need to control erosion for proper land use planning. According to the scarcity of literature in the area of soil nutrient evaluation with optimization models, the main objective of this research is determining the optimum level of land uses to minimize soil erosion and nutrients losses and maximize people incomes that live in a watershed. For this purpose, Abolabbas Watershed in the north-eastern part of Khouzestan Province was chosen for this research. A linear programming model was used in three different scenarios including current land use condition without land management, current land use condition with land management and standardized land use condition. Results demonstrated that the current land uses are not optimized for the least soil erosion and nutrient losses and high income. At optimized conditions, the area of forests and orchards increased by 1.81 and 55.7% respectively, rangelands with no changes, and irrigated and drylands decreased by 67.5 and 31.4% respectively. Also, results showed that land use optimization, in current land uses with no land management, decreases total soil erosion by 3.2% and total nutrient soil losses by 2.5 and increases total income by 29.7%, in current land uses with land management, decreases total soil erosion by 35.3% and total nutrient soil losses by 70.2 and increases total income by 37.2%, and in standardized land uses, total soil erosion by 47.2% and total nutrient soil losses by 70.4 and increases total income by 41.8%. Sensitivity analysis, also, showed that the change in the area of orchards and Irrigated lands has the most effects on increasing income and decreasing soil erosion and nutrients losses in Abolabbas watershed.
Reza Sokouti Oskooei; Mohammad Hossein Mahdian; Shahla Mahmoodi; Mohammad Hasan Masihabadi
Volume 2, Issue 3 , October 2010, , Pages 161-169
Abstract
Planning and suitable management is necessary for optimal use of soil and for this; spatial variability of soil characteristics is important which may be edcarried out through geostatistical methods of parametric and non-parametric predictors such as TPSS, WMA, Kriging and Co-kriging. This research work ...
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Planning and suitable management is necessary for optimal use of soil and for this; spatial variability of soil characteristics is important which may be edcarried out through geostatistical methods of parametric and non-parametric predictors such as TPSS, WMA, Kriging and Co-kriging. This research work was done in Southern part of Uromieh plain with 36690 ha surface area in order to study the spatial variability of soil lime, sand and saturation moisture percentage. Distance between soil profiles ranged 1300 to 4700 meters. For estimation and prediction of them in non-sampled points, the Kriging, Co- kriging and Weighted Moving Average were used in Geographic Information System environment. For selecting suitable interpolation method, Cross validation and MAE and MBE parameters were used. Selected method was also used for estimating and mapping of the selected soil characteristics. The Sturges rule was used for defining map classification. Results showed that the Kriging method has the highest accuracy with correlation coefficient of 0.83 and error of 3.98 percent for prediction of soil characteristics in non-sampled points.
