Ali Akbar Moosavi; Mohammad Omidifard
Abstract
Introduction: Saturated hydraulic conductivity and the other hydraulic properties of soils are essential vital soil attributes that play role in the modeling of hydrological phenomena, designing irrigation-drainage systems, transportation of salts and chemical and biological pollutants within the soil. ...
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Introduction: Saturated hydraulic conductivity and the other hydraulic properties of soils are essential vital soil attributes that play role in the modeling of hydrological phenomena, designing irrigation-drainage systems, transportation of salts and chemical and biological pollutants within the soil. Measurement of these hydraulic properties needs some special instruments, expert technician, and are time consuming and expensive and due to their high temporal and spatial variability, a large number of measurements are needed. Nowadays, prediction of these attributes using the readily available soil data using pedotransfer functions or using the limited measurement with applying the geostatistical approaches has been receiving high attention. The study aimed to determine the spatial variability and prediction of saturated (Ks) and near saturated (Kfs) hydraulic conductivity, the power of Gardner equation (α), sorptivity (S), hydraulic diffusivity (D) and matric flux potential (Фm) of a calcareous soil.
Material and Methods: The study was carried out on the soil series of Daneshkadeh located in the Bajgah Agricultural Experimental Station of Agricultural College, Shiraz University, Shiraz, Iran (1852 m above the mean sea level). This soil series with about 745 ha is a deep yellowish brow calcareous soil with textural classes of loam to clay. In the studied soil series 50 sampling locations with the sampling distances of 16, 8 , and 4 m were selected on the relatively regular sampling design. The saturated hydraulic conductivity (Ks), near saturated hydraulic conductivity (Kfs), the power of Gardner equation (α), sorptivity (S), hydraulic diffusivity (D) and matric flux potential (Фm) of the aforementioned sampling locations was determined using the Single Ring and Droplet methods. After, initial statistical processing, including a normality test of data, trend and stationary analysis of data, the semivariograms of each studied hydraulic attributes were calculated in various directions and their surface semivariograms were also prepared to determine the isotropic or anisotropic behavior of each studied soil attributes. Since all of studied soil hydraulic attributes were isotropic variables, therefore, the omnidirectional semivariograms were calculated and different theoretical models were fitted to them. The best fitted semivariogram models were determined using the determination coefficient, R2, and the residual sum of the square, RSS. The parameters of the best fitted models to the experimental semivariograms were also determined. The prediction of study hydraulic attributes was carried out using the parameters of semivariogram models by applying the ordinary Kriging approach. Predictions were also carried out using the Inverse Distance Weighing approach. The results of predictions were compared to each other using the Jackknifing evaluation approach and the suitable prediction method was determined and zoning was performed using the results of introducing prediction method. All of the semivariogram calculations and modeling, prediction of zoning of study hydraulic attributes were performed using the GS+ 5.1 software packages.
Results and Discussion: Results indicated that all of the studied soil hydraulic attributes belonged to the weak to moderated spatial correlation classes and the spherical model was the best fitted model for their semivariograms (except for Kfs and D that their best semivariogram models were exponential). The sill of all semivariograms ranged between 0.0003 to 0.419 for the S and Kfs, respectively. The nugget effects and the Range parameter of all semivariograms were located between 0.00015 to 0.108 for the S and Фm, and 211 to 6.4 m for Ks and D, respectively. Results also indicated that 3.5 and 50% of total variation of D and Ks was spatially structured and the other was random, respectively. The spatial correlation classes of near saturated soil hydraulic conductivity and soil hydraulic diffusivity were week, whereas, the spatial correlation classes of the other studied soil hydraulic attributes were moderate. Results revealed that the Inverse Distance Weighting method was the most suitable approach for the prediction of all studied soil hydraulic attributes in the present study. Comparison of the calculated statistical evaluation measures (i.e. Determination coefficient, R2, Mean residual error, MRE, mean square error, MSE, Normalized mean square error, NRMSE and geometric mean error ratio, GMER) and the final determined order of precision showed that the most and the least accurate predictions were obtained for Ks and Фm, respectively.
Conclusion: It is suggested in the cases that we need to map the hydraulic attributes or need their quantities in a large number; geostatistical prediction be performed using the limited measurements to reduce the needed time and costs.
J. Behmanesh; E. Rezaie
Abstract
Study of soil hydraulic properties such as saturated and unsaturated hydraulic conductivity is required in the environmental investigations. Despite numerous research, measuring saturated hydraulic conductivity using by direct methods are still costly, time consuming and professional. Therefore estimating ...
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Study of soil hydraulic properties such as saturated and unsaturated hydraulic conductivity is required in the environmental investigations. Despite numerous research, measuring saturated hydraulic conductivity using by direct methods are still costly, time consuming and professional. Therefore estimating saturated hydraulic conductivity using rapid and low cost methods such as pedo-transfer functions with acceptable accuracy was developed. The purpose of this research was to compare and evaluate 11 pedo-transfer functions and Adaptive Neuro-Fuzzy Inference System (ANFIS) to estimate saturated hydraulic conductivity of soil. In this direct, saturated hydraulic conductivity and physical properties in 40 points of Urmia were calculated. The soil excavated was used in the lab to determine its easily accessible parameters. The results showed that among existing models, Aimrun et al model had the best estimation for soil saturated hydraulic conductivity. For mentioned model, the Root Mean Square Error and Mean Absolute Error parameters were 0.174 and 0.028 m/day respectively. The results of the present research, emphasises the importance of effective porosity application as an important accessible parameter in accuracy of pedo-transfer functions.
sand and silt percent, bulk density and soil particle density were selected to apply in 561 ANFIS models. In training phase of best ANFIS model, the R2 and RMSE were calculated 1 and 1.2×10-7 respectively. These amounts in the test phase were 0.98 and 0.0006 respectively. Comparison of regression and ANFIS models showed that the ANFIS model had better results than regression functions. Also Nuro-Fuzzy Inference System had capability to estimatae with high accuracy in various soil textures.
Sh. Asghari; S. Dizajghoorbani Aghdam; Abazar Esmali
Abstract
Knowledge of the spatial distribution of soil properties is the major issues in identifying, program planning, management and utilization of soil and water resources. This study was carried out to investigate the spatial variability of some important soil physical quality indices including sand, silt, ...
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Knowledge of the spatial distribution of soil properties is the major issues in identifying, program planning, management and utilization of soil and water resources. This study was carried out to investigate the spatial variability of some important soil physical quality indices including sand, silt, clay, mean weight diameter of aggregates (MWD), organic carbon (OC), saturated hydraulic conductivity (Ks), saturated water content (θs) and bulk density (Db) in the three adjacent land uses i.e. forest, agriculture and range land located at Fandoghlou region of Ardabil. Totally, 100 soil samples were systematically (100 × 100 m grade) taken from 0-15 cm depth in spring 2013. At first, the accuracy of Kriging and inverse distance weighting (IDW) geostatisticaly methods in mapping of studied parameters was evaluated then the final map was presented. The values of nugget effect to sill ratio for clay, sand and silt were 0.5, 0.47 and 0.49, respectively so these parameters have an average spatial structure. The values of above mentioned ratio for OC, Db, θs, Ks, and MWD were obtained 0.002, 0.014, 0.0007, 0.05 and 0.008, respectively, indicating strong spatial structure. According to the R2 criteria, Kriging method in estimating clay, sand and silt and IDW method in estimating MWD, OC, Ks ،θs and Db had the highest accuracy. The final map indicated that forest land had higher OC, MWD and Ks and lower Db compared with agriculture and range land. The results of this research showed that soil physical quality of the studied region in agriculture and range land uses was lower than forest lands.
T. Asadollahzadeh; M. Mashal; S. Karimzadgan
Abstract
Saturated hydraulic conductivity (Kfs) and sorptive number are the most important hydraulic characteristics effective on soil process. Cased boreholes falling-head permeameter (Philip method) is the one of hydraulic conductivity measurement borehole method. The analysis borehole cased falling-head in ...
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Saturated hydraulic conductivity (Kfs) and sorptive number are the most important hydraulic characteristics effective on soil process. Cased boreholes falling-head permeameter (Philip method) is the one of hydraulic conductivity measurement borehole method. The analysis borehole cased falling-head in unsaturated area promoted and investigated .This method has been investigated by HYDRUS- 2D simulator but in this study is not use experimental data. The purpose of this study precision investigation and determine Reynolds method accuracy by experimental data. Thirty boreholes has been prepared, 12 boreholes with 4 different length and 4 centimeters diameter, 9 boreholes with 3 different length and diameters of 6 and 8 centimeters (3 replications done for each length). A program was written by FORTRAN language for solving the equations presented by Reynolds. Shaghaghi et al determine soil hydraulic conductivity by Guelph method in mentioned area. The results gained by FORTRAN program compared by Shaghaghi et al results. Results showed that the best data drawdown zone for determining Kfs and α* is lower range of data. Considering studies is shown that diameter and length of cased boreholes are not effective on investigation and every length and diameter can be used for solving Reynolds equation. Also the results show that the best gravity factor for precision of estimation is obtained in zero value.
M. Karimzadeh; A. Alizadeh; M. Mohammady Arya
Abstract
One of the important factors that limits the maintenance and expansion of agriculture in irrigated lands of arid areas is the water shortage. Reuse of the municipal waste water effluent as one of the uncommon water resources especially around the big cities has received a lot of attention. One of the ...
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One of the important factors that limits the maintenance and expansion of agriculture in irrigated lands of arid areas is the water shortage. Reuse of the municipal waste water effluent as one of the uncommon water resources especially around the big cities has received a lot of attention. One of the most important physical properties of the soil affected by using wastewater is the saturated soil hydraulic conductivity (Ks). In order to investigate the effect of wastewater on Ks, the farms with sand, silty loam and clay were selected from the area around Parkand Abad (2) refinery in Mashhad that has been irrigated during the past 5 years with wastewater. Undistirbed sample was selected and saturated with water , wastewater and mixture of them was used to determine the amount of ks (with constant head method) and the of soil in laboratory. The results showed that the farms with wastewater with total suspended solids of 60 mg per litere floating in water limits the ks in different textures. The reduction in soil with clay texture as about 9 Percent and in silty loam and sand was about 4.5 and 2 Percent respectively. Using water as the liquid of experiment didn’t have any effect on increasing the amount Ks so that leaching the soil under the irrigation with wastewater increased the soil saturation up to 3 percent That shows no effect of leaching in improving the water direction. The most change of pb was observed in clay soil about 11 percent and the least in sand texture soil about 0.6 percent that with respect to the amount of floating materials in wastewater (60 mg) per liter the use of wastewater has been effective in blocking the soil openings. It seems that the floating material in waste water soil aggregation and the duration of continuous use of wastewater are effective factors in changing the physical properties of soil such as Conductivity of water saturated soil.
H.R. Samaei; A. Golchin; Mohammad Reza Mosaddeghi; Sh. Ahmadi
Abstract
Organic matter improves soil structure and any factor that decreases soil organic matter content causes soils structural instability. In soils with low organic matter content, soluble polymers can be used to increase the soil structural stability. In order to study the effects of polymer type and concentration ...
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Organic matter improves soil structure and any factor that decreases soil organic matter content causes soils structural instability. In soils with low organic matter content, soluble polymers can be used to increase the soil structural stability. In order to study the effects of polymer type and concentration on physical properties of soils with different texture, factorial experiment ..was ..conducted.. within ..completely ..randomized design ..with ..three replication. Three types of polymer (R790, TC108 and NC218) and three polymer concentration (1:1, 1:3 and 1:10 V/V polymer: water) were used in factorial combinations. Samples from soils with different texture were sprayed with different concentrations of the polymers and physical properties of polymer- treated soil samples were measured and compared with the control. Polymers application significantly enhanced the physical conditions of the soils. It increased the soil saturated hydraulic conductivity and dry and wet structural stabilities of the polymer-treated samples when compared with the control. The application of polymers decreased the dispersible clay and soil density of the polymer-treated soil samples. Increase of the soil saturated hydraulic conductivity and structural stability of the polymer-treated samples was greater for high polymer concentrations. The TC108 and R790 polymers were more effective than the NC218 polymer in improving the physical properties of the soils.
V. Yazdani; B. Ghahreman; K. Davari; M.E. Fazeli
Abstract
One of the important aspects of soil is, knowing the relationships between spatial features of soil and quantity in statistical model. The goal of this research is to estimate saturated hydraulic conductivity by regression and Co-Active Neuro-Fuzzy Inference System (ANFIS) with using the parameters of ...
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One of the important aspects of soil is, knowing the relationships between spatial features of soil and quantity in statistical model. The goal of this research is to estimate saturated hydraulic conductivity by regression and Co-Active Neuro-Fuzzy Inference System (ANFIS) with using the parameters of Bulk density, real density, porosity, Fractal dimension of particle size, and clay percent, silt percent, sand percent. So experiment related to saturated hydraulic conductivity calculation and soil physical properties calculation of soil in 54 points which were specified 5 by 5 meters. Also, amount of bulk density based on paraffin Hunk, Fractal dimension of particle size by wet sieve method, the percentage of sand, clay and silt by Hydrometry and saturated hydraulic conductivity above water table by double rings method was measured. The best regression model for Pedo transfer function (PTF) was chosen according to minimized the goal function based on statistical parameters R2, RMSE and MAE. Parameters sand and silt percent, bulk density, real density, Fractal dimension of particle size, and porosity were chosen as input. In PTF amount of R2, RMSE, NRMSE and MAE, are 0.65, 0.017, 0.96 and 0.012 respectively. ANFIS with four layers input includes bulk density, real density, porosity and Fractal dimension of particle size and an output layer with the best performance. In this research, the amount of R2 in the presented ANFIS model in training and test is 0.88 and 0.86 respectively, and RMSE values will be 0.012 and 0.02 respectively. Noticing to sensitivity analysis result, PTF has the least sensitivity than changes in porosity and Fractal dimension of particle size, on the other hand, it has the most sensitivity than changes in the values of bulk density, silt and sand percent. ANFIS model is like PTF is more sensitivity than changes in values of bulk density. In addition, the outcome shows more effect on ANFIS than PTF. Evaluation of models show that estimation in clay soil is not acceptable, in contract contrast its model for estimate saturated hydraulic conductivity in soil texture (lom sandy, lom and silt lom) is suitable.
