JWSS - Journal of Water and Soil Science

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In order to assess hydraulics of LNAPLs in soil, the soil retention curves of petroleum and water were both determined through hanging column method. And, the hydraulic conductivity of petroleum and water were determined by steady head method. The water and petroleum hydraulic conductivities were 7.27 and 57.84 cm.day-1, respectively. The soil retention parameters were obtained based on van Genuchten, Brooks-Corey and Campbell models. In addition, the soil hydraulic conductivity for both fluids was predicted based on Mualem- Brooks-Corey, Burdine- Brooks-Corey, Mualem-van Genuchten and Campbell models. The accuracy assessment of models was performed by ME, RMSE, CD, EF and CRM. The results indicated that the magnitudes of the pore-size distribution parameters and the bubbling pressure parameters were reduced in NAPL-air system compared to water-air system. Due to unusual hydraulic behavior of petroleum and soil-petroleum interactions leading to remaining substantial petroleum content in porous media, more matric potential is needed to drain out petroleum from soils compared to water. Thus, soil provides more retention for petroleum at a given quantity of fluid. Owing to high amount of petroleum kinematic viscosity, the saturated soil hydraulic conductivity of petroleum was lower than that of water. However, soil hydraulic conductivity for petroleum was larger than water at more than 100 cm matric head.

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As pressurized irrigation is not possible for all circumstances, the use of modern techniques in surface irrigation is essential. In this paper, BISEDOM, a new mathematical model for evaluation, design and optimization of border irrigation is introduced. The effects of weighting coefficients of indicators are investigated based on the potential to improve and the most appropriate weighting scheme in optimization process is presented. In this model, volume balance equations for hydrodynamic simulation and SA method for optimization steps are used. Due to the nature of the SA, its parameters are determined by the method of sensitivity analysis. In this model, evaluation of different combinations of decision variables (inlet flow, length, width and slope of the strip) and consequently the performance of irrigation efficiencies reagent strip in an objective function is possible. Finally, the results indicate that the proposed method for weighted indicators has significant effects on improving performance of border irrigation. Model validation results in three parts of design, evaluation and optimization in comparison with SIRMOD and asymptote method showed that the results are very close to each other. The results also indicate that the proposed model has a good efficiency in comparison with other existing models especially for optimization purposes.

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Check dams are considered as main measures for flood and sediment control in watersheds, and their uses have been rapidly increased from 1990 onward in Iran. This research is done in Darjazin watershed in north of semnan city. The check dams have been constructed from 15 years ago in two sub basins of the watershed for flood control in Mahdishar. More than 650 check dams were evaluated for effects on flood. The collected data in the field was fed to ArcGIS software. The effects of these structures on flood reduction were evaluated by HEC-GeoHMS extension and HEC-HMS model. Because of homogeneity of watershed management projects in the basin due to building more check-dams in different watercourses, any flood discharge is related to check dams. Evaluating the effects of check dams on flood by t-test showed significant differences between flood discharge before and after construction of check dams at 5 percent level. So, check dams have been able to reduce flood discharge by 16.7 percent on average.

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The main scope of this research is evaluation of Soil Conservation Service Procedure in derivation of initial abstraction of precipitation in watershed scale. For this purpose Dalaki watershed which is located in south east of Iran was selected then by using hec-hms and GIS models and a number of observed rainfall runoff events some parameters like CN of watershed ,K and X of Muskingam method and initial abstraction of precipitation were calibrated through two different search algorithm of univariate and Nelder & Mead methods. The early results of this research indicated the superiority of Univariate search algorithm over the Nelder&Mead method both in calibration and also validation processes. Then using calibrated CN and Initial abstraction parameters which were derived through Univariate search algorithm, the factor between initial abstraction and potential retention of surface runoff (S) in each of sub basins were estimated. 0.13, 0.43 and 0.19 were derived as the above mentioned factor respectively for Minimum, Maximum and mean of the above mentioned factor in this step of the research which showed an acceptable compatibility to the offered factor of 0.2 by SCS. Then in rainfall runoff modeling process of this watershed SCS offers a reliable method of initial abstraction estimation.

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Soil tillage changes chemical and physical properties which can change the soil available water capacity. For understanding the effect of soil disturbance in cultivated soil on available water, parameter pedotransfer functions of these soils created and their results were compared with measured available water by moisture release curves. For this purpose 54 soil samples were taken from cultivated and non cultivated soils of Abyek-Qazvin area northwesthern Iran. Selected properties of these soils such as particle size distribution, bulk density, organic carbon, calcium carbonate, cation exchange capacity and pH were determined. Soil moisture curve of samples were obtained by pressure plates. Parameter pedotransfer functions were created by Mualem-van Genucten model for non cultivated soil and their available water were predicted. The predicted available water was compared with measured available water. The results illustrated that the predicted results had higher correlation coefficient for moisture of permanent wilting point compared to of field capacity moisture, As the correlation coefficient was inccreased from 0.67 to 0.83 and also the root mean square error (RMSE) reduced from 2.59 to 1.06. So the predicted available water was overestimated.

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The geographical location of Isfahan province has led the province to be at risk of drought. One of the ways to mitigate drought is evaluation and monitoring of drought based on indices that can determine its intensity and permanence in each region. In this research, for drought and trend analysis standard precipitation index and Mann-Kendall test were used, respectively. Also, monthly precipitation time series of Isfahan province was applied to forecast drought from 1970 to 2009. For this purpose, Box and Jenkins modeling approach (1976) was used which has three main steps, namely model identification, parameter estimation, goodness of fit test or time independency and normal test of residual. The results showed that most of the stations in Isfahan province were faced with severe drought in the year 2000 and this situation was repeated one more time in 2008. Also, the results brought forth multiplicative models in all the stations. ARIMA (1,0,0) (0,1,1) showed the highest correlations between control and forecast data in Isfahan, Meime and Ardestan stations, and the model ARIMA (0,0,1) (0,1,1) displayed the highest correlation between control and forecasted data in Naein, Freydoonshahr, Khansar and Natanz. These models were selected as the best models through which the amount of precipitation was predicted till 2015. The trend of forecast data across Isfahan province showed that in most months the trend is not significant.

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Continuous decline of groundwater quality for agricultural purposes has become a major concern in extensive arid and semi-arid regions. Therefore, mapping the quality of groundwater on a broad scale is an essential step in land management. This study aimed to map spatial distribution of two important groundwater quality indices including EC and SAR in Isfahan province, Iran, using geostatistical techniques. Different techniques such as Kriging, IDW and RBF were applied to water quality data of 540 groundwater wells to map continuous variations of the EC and SAR indices in Arc GIS 9.3 environment. Among the interpolation methods, the Kriging by circular variogram model performed best and had the lowest RMSe error. Therefore, the produced maps from this technique were classified based on Wilcox method. Results showed that EC varies across the province from 392.2 in the west to about 17917.6 µmmhos/ cm in the northwest and eastern parts of the study area. The highest and lowest SAR values were estimated in the towns of Khour va Biabanak and Semirom, ranging from 38.9 to 0.13, respectively. According to the map of irrigation water quality based on Wilcox method, about 12.13 % of the region was classified as good, 16% as moderate, 17.5% as unsuitable and 54.35% as unusable category. In general, the quality of groundwater in Isfahan province decreases from west to east and also from south to north, especially in playas (non-agricultural lands) where the unusable class is dominant.

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Phytoremediation models are important to understand the processes governing phytoremediation and the management of contaminated soils. Little effort has been made for evaluating the potential of the phytoremediation of metals based on the mathematical models. Therefore, the purpose of this study was modeling the phytoremediation of the nickel-contaminated soils. For this purpose, a model was recommended for estimating the rate of the phytoremediation of nickel from the soil by means of relative transpiration reduction and concentration of nickel in the plant functions. To evaluate the model, soil was contaminated with different levels of nickel by nickel nitrate. Then, the pots were filled with contaminated soil and Basil (ocimum tenuiflirum L.) seeds were planted. To avoid the dry tension, the pots were weighed and irrigated to the point of field capacity (FC) at short time intervals (48 hours). The plants were harvested in four times. At each harvesting stage, the relative transpiration values and nickel concentration in the soil and plant samples were measured. The performance of the model was evaluated by statistical methods such as Maximum Error, Root Mean Square Error, Coefficient of Determination, Efficiency of Model and Coefficient of Residual Mass. Results demonstrated that in the case of nickel contamination in soil, changes in the relative transpiration of Basil can be measured by the two proposed models and the linear model (R2=0.94) has a better performance compared to the nonlinear one (R2=0.84). Also the model obtained from the combination of linear function and nickel's concentration in soil has a relatively good (R=0.7) fit with the measured values of the remediation rate of nickel in soil.

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While the mass density current penetrates the stagnant fluid, a plunge point occurs. In this regard, the boundary of the dense fluid with ambient fluid is determined at the plunge point height. In this research, the hydraulic parameters of the dense flow and the bed slope of the stagnant fluid which have a significant effect on the plunge point have been investigated under the two turbulence models: the k- and the RNG at the Flow-3D model. To achieve the purpose of this research, a physical model was set up at the hydraulics laboratory of Shahid Chamran University (SCU), Ahwaz, Iran. Then, using the Flow-3D model with both the k- and the RNG turbulence model, the height of the plunge point was simulated according to the same experimental condition. Findings showed that the predicted depth under the RNG model is closer to the results of the physical model. For example, the k- and RNG model for the 12% slope can estimate the plunge point depth by 30% and 12.28% respectively more than the experimental data. However, for all the slopes, the k-e model can on average overestimate by 27% and RNG model 10.5% more than the results of experimental data. The statistical analysis showed that the RNG model predicts the plunge point depths with a satisfactory precision.

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Evaluation of hydrologic behaviour and soil erosion as an environmental crisis is important in order to maintain watershed ecological safety at optimum level. The aim of this study is to evaluate the performance of the distributed hydrological WetSpa model in simulating erosion and sediment transport and also sedigraph in Taleghan watershed, Iran. Base digital maps and daily meteorological time series data for 9 years are the major model inputs. The calibration of global parameters was done for the first 5 years and the model validation was carried out for 4 years considering three month warm-up period at the beginning of both calibration and validation periods. The Nash-Sutcliffe criterion for the calibration and validation periods pointed out the efficiency of model simulation (82.7% and 79%, respectively). The next phase, the erosion module was calibrated for erosion and sediment transport simulation. The results showed the Nash-Sutcliffe efficiency criterion (60% and 64% for suspended sediment concentration and transport, respectively). Overall, the evaluation results reveal the good ability of WetSpa model in simulation of the hydrological processes e.g., runoff, raindrop detachment, runoff detachment, net soil loss, etc., in a given time and space

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Water Uptake by the root under salinity and water Stress in unsaturated soils was investigated through mathematical equations in three Groups of additive, multiplicative and non-consumptive. This study was an effort to assess six water uptake functions of van Genuchten (additive and multiplicative), Dirksen et al., Van Dam et al, Skaggs et al, and Homaee, for Rasht Hashemi rice under salinity and water stress conditions. Based on field observations of Hashemi Rasht rice in 1386 and 1389, crop growth simulation model of SWAP was calibrated and validated with a correlation coefficient of 0.97 and 0.95, respectively. Water Uptake Reduction Models' parameters were determined by the simulated data using SAS statistical software. Results showed that for the anticipated reduction of Water Uptake in rice water and salinity stress conditions for Rasht Hashemi rice, Homaee model is best.

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Concerning the drying problem of the Lake Urmia in Iran, so far the relevant scientific research has not been conducted based on watershed management principles. The surface solar radiation (Rs) is one of the key input parameters in most of reference evapotranspiration (ET0) prediction models. In the present research, four solar radiation models were evaluated to predict the monthly-mean values of daily ET0 at seven synoptic stations located in the Lake Urmia basin during the 1985-2005 period. For the ET0 prediction, we applied the Penman-Monteith-FAO 56 model (PMF56). At first, we evaluated four radiation models consisting of Hybrid: H, Ångström-Prescott: AP, Modified Daneshyar: MD, and Modified Sabbagh: MS. Four statistical criteria used included the mean error (ME), the mean absolute error (MAE), the root mean square error (RMSE), and the mean percentage error (MPE). The mean RMSE value of hybrid model was 1.7 MJ/m2/day while the RMSEs for the AP, the MD and the MS models were 2.9, 2.3, and 2.9 MJ /m2/day, respectively. The results revealed a higher performance of hybrid model to predict the monthly radiation. In addition, the Rs models used in the original PMF56 model were compared with a case in which the measured daily Rs data was used. Finally, by integrating the hybrid model and the PMF56, we developed a coupled model as PMF56-Hybrid. The application of the Hybrid and the MD models resulted in a decrease in the RMSEs. The AP model used in the PMF56 showed about 19% overestimation.

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CEC of the soil is the exchange sites of organic and inorganic soil colloids. Modeling and Estimation of CEC is a useful indicator for fertility. The new alternative approaches for estimating CEC are indirect methods based on intelligent models. In this research in order to estimate CEC, 485 soil samples were prepared from two regions, chaparsar (Mazandaran in northern Iran) and Bostanabad (North of West Azarbaijan, Iran).In this paper introduces the application of genetic programming. Input parameters that are percent Clay, Organic Carbon and Silt, evaluate using genetic programming, neural network and Neural Inference Systems-Fuzzy models. The results indicate a good ability to intelligent models for CEC Estimation According to indices used in this study. Genetic programming model with a root mean square error of 1.78 and coefficient of determination 0.95 compared to other models have been more efficient and is able to provide satisfactory results, Also are the explicit solutions that reflect the relationship between input an output variable, was presented based on genetic programming. This preferred the genetic programming model adds the other models. Stepwise regression analysis to determine the contribution of each of the parameters indicated in the CEC that organic materials having Most coefficient of variation of 84% is justified CEC and clay and silt, respectively, with a correlation coefficient of 10% and 6% respectively.

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In the present research, the performances of six empirical models, i.e., simple threshold exceedance, fixed proportion exceedance, quadratic function of storage, power function of storage, cubic function of storage, and exponential function of storage were investigated for estimation of groundwater potential recharge in a semi-arid region. First, the FAO Dual Crop procedure was used to calibrate evaporation from bare soil during the occurrence of potential recharge period. Then, the empirical models were calibrated utilizing soil moisture and potential recharge data. For validation of empirical models, soil moisture and potential recharge were simultaneously estimated for an independent event. Results indicated that 5 of the six models (except for the simple threshold exceedance model) were able to estimate potential recharge with a reasonable accuracy, showing the maximum computed value of NRMSE (Normalized Root Mean Square Errors) of 24.4 percent. According to validation results, exponential, cubic, and power function models provided better estimation of potential recharge in comparison with the linear models. Also, all of the applied empirical models were able to simulate soil moisture during the recharge period with an acceptable accuracy. Finally, the exponential model with minimum NRMSE value for soil water simulation and also acceptable performance of potential recharge estimation was recommended for estimation of potential recharge in the study area.

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With the advent of advanced geographical informational systems (GIS) and remote sensing technologies in recent years, topographic (elevation, slope, and aspect) and vegetation attributes are routinely available from digital elevation models (DEMs) and normalized difference vegetation index (NDVI) at different spatial (watershed, regional) scales. This study explores the use of topographic and vegetation attributes in addition to soil attributes to develop pedotransfer functions (PTFs) for estimating soil saturated hydraulic conductivity in the rangeland of central Zagros. We investigated the use of artificial neural networks (ANNs) in estimating soil saturated hydraulic conductivity from measured particle size distribution, bulk density, topographic attributes, normalized difference vegetation index (NDVI), soil organic carbon (SOC), and CaCo3 in topsoil and subsoil horizon. Three neural networks structures were used and compared with conventional multiple linear regression analysis. The performances of the models were evaluated using spearman’s correlation coefficient (r) based on the observed and the estimated values and normalized mean square error (NMSE). Topographic and vegetation attributes were found to be the most sensitive variables to estimate soil saturated hydraulic conductivity in the rangeland of central Zagros. Improvements were achieved with neural network (r=0.87) models compared with the conventional multiple linear regression (MLR) model (r=0.69).

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The objectives of this study were to investigate the effect of dripper discharge and irrigation time on the wetted width in the sandy loam soil with high percentage of gravel and to evaluate previously developed models of estimation of the wetted width in the previous researches. The treatments included three irrigation times (T) of 4, 8 and 12 h and three dripper discharge rates (q) of 2, 4 and 8 l/h, with three replications. The wetted width of each dripper was measured 24 hours after irrigation application. The maximum and minimum wetted widths were 159.8 and 63.5 cm for T12q8 and T4q2, respectively. A linear model was developed as a function of two variables of irrigation time and dripper discharge rate was developed to predict the wetted width in sandy loam soil with high percentage of gravel. The evaluation of recommended models of wetted width for the studied soil showed that only one of six models was accurate enough to estimate wetted width. It can be concluded that the presence of gravels in the soil has a complex effect on width and depth of wetted zone. Thus, it is necessary to measure the wetted width and wetted depth in the field.

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One of the most essential and appropriate groundwater model components is accurate information of the recharge values among input data often introduced to the model as the percentage of rainfall of aquifers. The recharge values are influenced by many temporal and spatial factors. Firoozabad plain is one of the suitable plains for agriculture in the Fars province in which utilization of groundwater resources has been banned since 23 September 2002, due to the declining water level and negative balance. The main purpose of this study was to estimate the recharge values of groundwater aquifer by using SWAT in the MODFLOW model. Firstly, surface water was simulated via SWAT model, and sensitivity analysis, calibration, validation and uncertainty analysis of results were performed by SWAT-CUP software. After extraction of aquifer recharge values from the calibrated model, the groundwater of basin was simulated via MODFLOW model in both steady and unsteady conditions. Following the model calibration, the hydrodynamic coefficients of plain were determined and sensitivity of model was checked in terms of hydraulic conductivity and discharge rate of pumping wells. As for the confidence, the model was revalidated, which proved in simulating the behavior of the aquifer very well.

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The SIMDualKc model is an irrigation scheduling simulation model that uses dual crop coefficient method for estimating ETc by computing two separate soil water balances in daily time-step, one for the soil evaporation layer from which Ke is computed, and the other one for the entire root zone to compute the actual Kcb adjusted to the soil moisture conditions. In this study, lysimetric measurements of evapotranspiration rates relative to (Coriandrum sativum L.) during 2 years were used for model calibration and validation. Kcb values for coriandrum were found as 0.21 for the initial, 1.12 for the mid-season and 0.79 at harvesting period. Model results have shown a good agreement between the actual daily evapotranspiration predicted by the model and the ones resulting in water balance calculation on drainable lysimeters, and root mean square errors of estimates (RMSE) of about 1.64 mm and 1.53 mm for the calibration and validation, respectively.The modeling efficiency EF and the index of agreement dIA were equal to 0.8 and 0.93, respectively, thus indicating good performance of modeling with SIMDualKc. Model estimates of evaporation (E) for validation and calibration years displayed an average of 181 mm, representing 25% of ETc. In conclusion, results show that the model is appropriate to simulate the daily evapotranspiration adopting the dual Kc approach for coriandrum in west regions of Iran.

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Transport of fluoride and consumption of groundwater with excess fluoride concentrations poses a health threat to millions of people around the world. The objective of this study was to simulate transport of fluoride (F) using HYDRUS-1D model. The study was conducted in lysimeters at Lavark research station site in Isfahan. The treatments consisted of two concentrations of F (157 and 315 mg kg-1). The duration of the study was 125 days. Some of soil physical and chemical properties, soluble F and total F concentration were determined during the study. The results showed the transport of F in calcareous soil profiles. This may be due to the high pH and desorption of F ion as a result of repulsion by the more negatively charged soil surfaces. The highest concentration of total F and water soluble F were observed in the 10 cm surface soil layer. The concentration of F decreased with increased soil depth. The correlation coefficient was significant between the water soluble fluoride and the total fluoride (1% level). Also, the difference between the observed t- value and a critical value on the t distribution is statistically insignificant. It showed that the model simulated successfully water soluble F concentration in the soil profile.

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Erosion and sedimentation as a river natural behavior lead to the loss of soil and cause irreparable damages to water development projects. Since the phenomenon of erosion and deposition is one of the most complex natural processes, the complete understanding of the effective factors involved in this phenomenon is really a big problem. This study was done to optimize the parameters affecting sediment yield and determine their sensitivity in the Doiraj river basin in the West of Iran, using SWAT, a semi-distributed model, and SUFI2 algorithm, and the monthly sediment yield from 1994 to 2004. In the first run of the model, coefficients R2, NS, and Br2 were respectively obtained as 0.43, 0.39 and 0.28. The results showed that performance of the model with the default data was not satisfactory and we needed to determine the used optimal values. Then, the optimal values of parameters were determined using SUFI2 algorithm and reverse modeling and the model was run with the new values. Based on the new results, coefficients R2, NS, and Br2 were respectively obtained as 0.75, 0.73 and 0.65 and performance of the model improved and its accuracy increased acceptably. In the next step, from among the studied 30 parameters, (CH_N2), (USLE_K), (USLE_P) and (OV_N) were identified as the important parameters effective in the output of the sediment yield from basin. Also, USLE_K as was diagnosed as the most sensitive parameter. Results of this survey can be used in the management of the effective parameters in sediment load. Determining exact values of the effective parameters in other studies can be helpful to improve the simulation results in similar basins, too.