habib beigi; S. Ahmadzadeh; S. Heshmati
Abstract
Introduction: Soil pollution, i.e. elevated concentration of undesirable organic and inorganic matter such as trace elements higher than natural background concentration can be a consequence of indirect or intentional human activities. Evaluation of the effect of the agricultural operations and particularly ...
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Introduction: Soil pollution, i.e. elevated concentration of undesirable organic and inorganic matter such as trace elements higher than natural background concentration can be a consequence of indirect or intentional human activities. Evaluation of the effect of the agricultural operations and particularly using the wastewater on soil trace element concentrations is useful and required to manage the land and reduce the health risks of the food products. The aims of this study were: [1] The estimation of the mean concentration and max limit of the background concentration for Cd, Cr, Ni, Pb, Co and Hg in the surface soil samples of Boroujen-Faradonbeh plain; and [2] Evaluation of the effect of agricultural operation and farming by non-conventional water on background concentration and on accumulation, distribution and pollution load of the soil of this plain.
Materials and Methods: Boroujen-Faradonbeh is an agricultural plain loaced in the Chaharmahal and Bakhtiari mountainous province of Iran. Two hundered surface soil samples (0-20 cm) were taken from three types of land: never-uncultivated soil (20 samples), freshwater-irrigated (90 samples) and wastewater-irrigated (90 samples) soils. The total sampled area was about 2340 hectares. The exact position of the samples were recoded using a GPS device. The total concentrations of Pb, Co, Ni, Cd, Cr and Hg in the samples, and the background and upper limit concentrations were determined. In addition, pollution loading index (PLI) for the whole plain determined and delineated. To separate the affects of agricultural practices and wastewater application the analysis of variance of StatSoft Statistica 12 was used. Maping, and related operations were conducted inside ArcGIS 9.3.
Results and Discussion: Background concentrations of Ni, Cd, Cr, Hg, Co, and Pb, were determined as 1.13, 0.16, 1.56, 0.09, 0.80, and 1.52 mg/kg, respectively; while upper limit concentrations for the mentioned trace elements were respectively 1.3, 0.28, 1.6, 0.16, 0.9, 1.7 mg/kg. Conventional farming (application of fertilizer but not wastewater) increased the soil accumulation factor of Cd and Pb to 1.7 and 1.9 (p
habib beigi
Abstract
To investigate the long-term effect (13 and 23 years) of wastewater irrigation on soil physical quality indices in Taqanak, Shahrekord, four homogenous fields but with long and different history of treated municipal wastewater application were selected. The changes in conventional soil physical indicators ...
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To investigate the long-term effect (13 and 23 years) of wastewater irrigation on soil physical quality indices in Taqanak, Shahrekord, four homogenous fields but with long and different history of treated municipal wastewater application were selected. The changes in conventional soil physical indicators (organic carbon, bulk density, mean diameter of aggregates) as well as retention-curve derived indices: Dexter’s S index, Macro pore porosity (MacPOR), air capacity (AC), plant available water content (PAWC) and relative water capacity (RWC) were investigated in these farms.Irrigation with wastewater significantly increased (p
habib beigi
Abstract
Boroujen–Fradonbeh plain is one of the nine main agricultural hubs of Charmahal Provine. The aim of this study was to define and map a deficiency index of soil micronutrients and the effect of wastewater application on it. For this, 200 surface soil (0-30 cm) samples were randomly collected and plant ...
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Boroujen–Fradonbeh plain is one of the nine main agricultural hubs of Charmahal Provine. The aim of this study was to define and map a deficiency index of soil micronutrients and the effect of wastewater application on it. For this, 200 surface soil (0-30 cm) samples were randomly collected and plant available concentrations of copper, zinc, iron, and manganese were determined. After variography and determining the most suitable spatial estimation method, maps of each micronutrient was drawn, normalized, and ranked. An integrated deficiency map was then constructed using the weights from rank maps. According to the maps of copper, zinc and iron, the available concentrations increased from west to east of the plain. This increase was attributed to the wastewater irrigation. The mean value of the integrated map, namely 85.5, indicated the seroius soil deficiency of micronutrients in this plain where 34% of the area was showing severe deficiency. Wastewater application has increased the overall availability of micronutrients by 4%. Sensivity analysis indicated that the map was most sensitive to zinc. Therefore, zinc concentration must be monitored with more precision and frequency across the plain.
Abstract
Estimation of soil moisture content at different soil suctions is preferred to its determination due to required cost and time. The aim of the present work was to explore the relationship between soil texture fractal dimension and soil volumetric water content. A dataset of 195 soil samples from UNSODA ...
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Estimation of soil moisture content at different soil suctions is preferred to its determination due to required cost and time. The aim of the present work was to explore the relationship between soil texture fractal dimension and soil volumetric water content. A dataset of 195 soil samples from UNSODA database was selected. A pedotransfer developed by Sepaskhah & Tafteh (2013) was used to estimate soil fractal dimension. Exponential functions better describe the fractal-water content relationship than linear functions. A set of exponential pedotransfer functions using texture fractal dimension or additionally soil bulk density is proposed for predicting water content at several suctions across soil water retention curve. These pedotransfer functions, generally, function well or better than the most recent pedotransfer functions proposed by Ghanbarian-Millan (2010).
H. Beigi Harchegani; Y. Ostovari
Abstract
Particle size distribution (PSD) is one of the most important soil physical properties. The Grey Model GM(1,1) is a new method and different from empirical and parametrical models for description and estimation of soil particle size distribution. In this study, the models of Grey GM(1,1) and Skaggs ...
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Particle size distribution (PSD) is one of the most important soil physical properties. The Grey Model GM(1,1) is a new method and different from empirical and parametrical models for description and estimation of soil particle size distribution. In this study, the models of Grey GM(1,1) and Skaggs have been used to estimate PSD in five soil textural classes including 138 soil samples taken from Shahrekord Plain. For evaluating and comparison of two models, four statistical indices (MSE, MAPE, AAE, R2) and 1:1 lines were used. The results showed that the performance of both models was relatively good in all five textures. However, Skaggs and Grey GM(1,1) had the best performance in loam and clay textures, respectively. It seems that the performance of Skaggs and Grey GM(1,1) models improved when soil textures changed to coarser and finer textures, respectively. Absolute cumulative error (AAE) of the Skaggs model in some textures tended to decrease while that of the Grey GM(1,1) tended to slightly increase with increasing uniformity and curvature indices of soil.
E. Nabizadeh; H. Beigi Harchegani
Abstract
Abstract
Water retention curve (WRC) is a fundamental property of soil. It is used to evaluate available water, permeability, drainage and movement of solutes. Despite numerous studies on WRC of soils abroad, no local study has been carried out on Charmahal-va-Bakhtiari soils. The objective of this ...
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Abstract
Water retention curve (WRC) is a fundamental property of soil. It is used to evaluate available water, permeability, drainage and movement of solutes. Despite numerous studies on WRC of soils abroad, no local study has been carried out on Charmahal-va-Bakhtiari soils. The objective of this study was to compare the quality of fitting of several WRC models to Lordegan soils and to select the appropriate models. The studied models were: Brooks-Corey, van Genuchten, Farrel-Larson, Libardi et al., Simmons et al., Bruce-Luxmoore and Campbell. Fifty soil samples were collected from across Lordegan plain and Their texture were determined characterized for texture. Water retention data were obtained using hanging water column and pressure plate apparatus. Models were fitted using SWRC 3.0 software. R-square ( ) and were used for evaluating fitting quality. All models did well with ranging from 0.90 to 1.00 and from 0.001 to 0.036. However, in all samples and all textural classes, van Genuchten model fitted best. Brooks-Corey model was the weakest although its was always greater than 0.90 and its maximum was 0.036 . Therefor, van Genuchten model is recommended for soils of Lordegan plain.
Keywords: Soil water retention curve, Van-Genuchten, Brooks-Corey, Fitting quality
M. Memarian fard; H. Beigi
Abstract
Abstract
Cation Exchange Capacity (CEC) is an important characteristic of soil in terms of nutrient and water holding capacities and contamination management. Measurement of CEC is laborious and time-consuming. Therefore, CEC estimation through other easily - measured properties is desirable. In this ...
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Abstract
Cation Exchange Capacity (CEC) is an important characteristic of soil in terms of nutrient and water holding capacities and contamination management. Measurement of CEC is laborious and time-consuming. Therefore, CEC estimation through other easily - measured properties is desirable. In this study, PTFs for estimation of cation exchange capacity from basic soil properties such as particle-size distribution, organic carbon, percentage saturation and pH were developed and validated using artificial neural network (ANN) and multiple-linear regression methods and the predictive capabilities of the two methods was compared using some evaluation criteria. Total of 200 soil samples was divided into two groups as 165 for the development and 35 for the validation of PTFs. Accuracy of the predictions was evaluated by the criteria of coefficient of determination (R2) and the root mean square error (RMSE) between the measured and predicted CEC values. Clay (%), OC (%), SP and sand (%) predicted CEC better than other models with an R2=0.81 and RMSE=3.05 cmol.kg-1 when a neural networks model with one hidden layer and seven nodes was used. The R2 and RMSE varied from 0.66 to 0.69 and from 4.26 to 4.69 for regression, and varied from 0.78 to 0.81 and from 3.05 to 3.29 for ANN, respectively. Results showed that neural networks predictions is better than regression-based functions.
Key words: Artificial neural networks, Cation Exchange Capacity, Chaharmahal - Bakhtiari
