Iranian Journal of Soil and Water Research
Year:2020 | Volume:50 | Issue:10|Papers Count:20

Due to limitations of laboratory tools and difficulty in interpreting the results obtained from complex porous media such as soil, artificial porous media such as glass beads, pure sand and quartz and riverbed sand are oftenly used to investigate the transfer of nanoparticles in porous media. In this study, the effect of different flow rates on transfer of titanium dioxide nanoparticles was investigated in the undisturbed soil columns. The flow rate equal to 100, 90, 70 and 50% of the saturated hydraulic conductivity were applied on the soil columns by the peristaltic pump (BT100-1F). By measuring the breakthrough curves for each column, the parameters explaining the transfer of nanoparticles based on a one-site sorption model, one-kinetic site sorption model, and a two-kinetic site sorption model were determined. The results indicate by increasing the flow rate, the reltive concentration of TiO2 nanoparticles (C/Co) in the soil column increases from 3% to 28%. Among the three studied models, the two-kinetic site sorption model which consider the physical straining mechanism based on the particle size and porosity of the porous medium, the function of saturation of the porous media particles with nanoparticles and the physical straining function considering changes of this mechanism with distance, shows the best fit (R2>%90) for estimation of the nanoparticles transfer in the soil column.

In order to investigate the effect of bio-fertilizers on contamination rate of plants to heavy metals, a factorial experiment based on completly randomized design with three replications was carried out in greenhouse of soil science department at agriculture faculty of Zanjan University in 2015. The proposed treatments were: contamination levels of soil to cadmium (0, 10, 25, 50 and 100 mg of cadmium per Kg of soil) and inoculation with bio-fertilizers including; phosphate solubilizing bacteria Pseudomonas putida, mycorhiza fungi Funneliformis mosseae and Rhizophagus intraradices. The measured factors were leaf chlorophyll index, plant height, shoot and root fresh and dry weight, phosphorus and potassium of shoot and root and cadmium concentration in plant. The results indicated that the use of bio-fertilizers increased the leaf chlorophyll index, plant height, shoot and root fresh and dry weight, phosphorus and potassium of shoot and root significantly as compare to the control. The treatment of Funneliformis mosseae and Pseudomonas putida (M+P) could improve leaf chlorophyll index and plant height by 11. 93 and 21. 89 % in comparing whit control respectively. The chlorophyll index was significantly decreased by increasing cadmium levels in the soil. Simultaneous application of Funneliformis mosseae and Pseudomonas putida (M+P) and cadmium increased the shoot and root dry weight by 6 and 7 % as compared to treatment of 100 mg cadmium per Kg of soil. Totally, the results indicated that the inoculation of soil whit bio-fertilizers could reduce the harmful effects of cadmium on plants growth and yield.

Soil moisture is a determinative parameter in many of the complex environmental processes and plays a decisive role in the occurrence of agricultural drought. So, in this study, based on estimated soil moisture data by SWAP model and Fifth Report Data of Climate Change, agricultural drought was determined by Soil Moisture Deficit Index for the upcoming period (2020-2039) for the wheat field of Faroub in Neyshabour. The climatic data were estimated using six models of GCM and two emission scenarios of 4. 5 and 8. 5 and were downscaled by LARS-WG model. Then the downscaled climatic data along with field, irrigation and soil data were entered into the SWAP model. Finally, using soil moisture data of 0-30 cm depth, agricultural drought was evaluated using SMDI index. The results showed that the minimum and maximum temperatures and precipitation in the upcoming period have increased compared to the base period and 8. 5 scenario have estimated a higher temperature and lower rainfall than the 4. 5 scenario. Also, the average SMDI in the upcoming period has increased relative to the base period for both scenarios. The certainty results of GCM models for estimation of SMDI index also showed that under the 4. 5 scenario, the IPSL and MIROC models have the highest certainty and the Canesm2 model has the lowest certainty. Under the 8. 5 scenario, MIROC model has the highest certainty and Ciromk-3. 6 and GFDL models have the lowest certainty.

Solid particles transport in fluid flow is a common phenomenon in nature, and its typical example in hydraulic science is sediment transport in rivers. In a channel with a bed of sedimentary materials, there are no moving particles in the streams with a low discharge and remain steady in their place. As the particle velocity increases, the bed particles begin to move, which is called the threshold of motion of the sediment particles. In this study, using a numerical model based on OpenFOAM software, a two-dimensional simulation of the threshold of group motion of sediment particles in turbulent flow has been investigated. The approach used in the simulation is Eulerian-Lagrangian, in which the continuous phase is emulated in a continuous manner in the form of an Eulerian with finite volume method and sediment particles are simulated in a Lagrangian and particle tracing method. In the current model, the effect of fluid on the particle, the particle on the fluid, and the forces that the particles of the sediment enter to each other are considered. In order to consider the effect of sediment particles inner interacting, a soft contact approach and a friction damper spring impact model were used. The results of the numerical model have been compared with other researchers in the form of critical velocity method and a relation has been proposed for the particle motion threshold criterion. Also, Incipient motion of sediment particles with different criteria has been studied. The results show that the present model can simulate the phenomenon well with proper accuracy.

The remediation of heavy metal in contaminated soils using ornamental plants presents a suitable solution for decontamination, especially in urban areas. In order to investigate the ability of ornamental plants to refine contaminated soils, an experiment was conducted in the greenhouse using six levels of soil cadmium (0, 5, 10, 20, 40, and 80 mg/kg), three species of ornamental plants (Calendula officinalis L., Helianthus annuus L., and Celosia argentea L. ) and three replications. The results showed with increasing cadmium levels in the soil, cadmium concentration in the plant tissues increases, so that, the highest and the lowest concentrations of cadmium were measured in the shoot of Calendula officinalis L. and Helianthus annuus L. respectively with a difference of 50. 2%. However, the highest and the lowest cadmium concentration in the root were found in the Helianthus annuus L. and Calendula officinalis L., respectively with a difference level of 4. 2%. The cadmium uptake of the shoot in Calendula officinalis L. was at least 27. 63% more than those in the other species. The chlorophyll index of the leaf and the number of flowers in Calendula officinalis L. were respectively 17. 33% and 34% more than those in the other species. The translocation factor of Celosia argentea L. was equal to one (1. 0) and those of Calendula officinalis L. and Helianthus annuus L. were less than one (0. 5 and 0. 3), but the bioconcentration factors for all species were found to be more than one. With respect to high cadmium uptake, high cadmium concentration of shoot, high biomass and high beauty indices (chlorophyll index and the number of flowers) of the Calendula officinalis L., this species is recommended for remediation of cadmium contaminated soils.

The development of agricultural crop cultivation in greenhouse is one of the main strategies for managing water scarcity. Awareness of the crop water requirement and accurate estimation of crop coefficient is one of the most important component in irrigation scheduling and improving water use efficiency. The objective of this research was to determine water requirement and crop coefficient of basil in controlled greenhouse condition. For this purpose, a study was carried out in a research greenhouse of the College of Agriculture and Natural Resources, University of Tehran during a growth period using micro-lysimeter. Micro-lysimeters are useful tools for accurate determination of the crop evapotranspiration under standard conditions (ETc), or the actual crop evapotranspiration (ETa). In this study, the evapotranspiration of the reference crop and the Basil water requirement were estimated using the soil water balance equation. According to the results, average reference and basil crop evapotranspiration during the growth stage were equal to 8. 23 and 5. 13 mm per day, respectively. Then the crop coefficient was calculated based on the ratio of basil crop and reference evapotranspiration. The average basil crop coefficients for the initial, mid and end growth stages were obtained to be 0. 30, 0. 86 and 0. 76, respectively.

Accurate forecasting of river flow is one of the most important factors in surface water resources management, especially during flood and drought periods. In this research, the wavelet function and the ensemble empirical mode decomposition (EEMD), which are considered as soft computing tools, were used to derive the time series features, and the efficiency of the wavelet-Gaussian and the ensemble empirical mode decompositionGaussian models for predicting the discharge between the three consecutive stations located in the Housatonic river have been investigated. For this purpose, in the first step, the discharge of downstream stations is predicted by upstream stations using the Gaussian process regression model. Then, the discharge-stage time series was broken up by wavelet transform and ensemble empirical mode decomposition into cages, and these subclasses were introduced into the Gaussian process regression modeling to simulate the discharge-stage relationship. Also, the effect of each of the sub-series of ensemble empirical mode decomposition model (Residual and IMFs) was studied to improve predictive outcomes. It was observed that the most inefficient subseries in the ensemble empirical mode decomposition model is the residual subseries. The results indicate that wavelet compound techniques (DWT-GPR) and ensemble empirical mode decomposition (EEMD-GPR) have improved the results to a certain extent. As an example, for the test stage, the best prediction model of the second station, the combined model of ensemble empirical mode decomposition-Gaussian upgraded determination coefficient (DC) from 0. 74 to 0. 80 and the combined model of wavelet-Gaussian upgraded DC from 0. 74 to 0. 83.

Soil quality indicates soil ability to provide biological, ecological and production services. Determination of soil quality indices requires a large number of soil characteristics measurements. Soil enzyme activities have been recognized as suitable indicators in assessing the effect of management and environmental factors on soil quality. This study has been implemented to develop a regression model between soil enzyme activities and soil characteristics along the north-south transection in Miamicounting. For this purpose, 120 soil sampleswereselected from the top layer (30 cm) at three different sites using the standardized classification method. Soil properties and activity of enzymes were determined according to standard methods and also, applying linear regression method of ordinary least square, the relationship between soil properties and three soil enzymes included in b-glucosidase, urease and alkaline phosphatase was modeled. The results showed, overall all soil enzyme activity decreased from north to south and b-glucosidaseenzyme had the highest coefficient of variation (%68). The models provided with accuracy (R 2 adj) about %50. 4 to %70. 4 are able to predict the soil enzymes activity. The most important soil properties effective on enzyme activity in the northern region included respectively, total organic carbon, soil texture, cation exchange capacity, Phosphorus and potassium available but in the southern region, total organic carbon, salinity, PH. The results of validation (RMSE, R 2 adj) ascertained that the predictors were sufficiently accurate. The results of this study used in the improvement of regional planning for sustainable management of soil.

In the present study, 105 tests were carried out to investigate the effect of horizontal screen slope on hydraulic characteristics of vertical drop with the subcritical flow in upstream. The experiments were arranged in two models, plain vertical drop and vertical drop equipped with horizontal and sloping (three slopes) screens in two porosity ratios. The range of relative critical depth was from 0. 07 to 0. 24 the screen slopes were 7 ◦ ◦ , 14 ◦ , 21, and the screen porosities were considered to be 40% and 50%. The relative wetted length of the screen, the relative turbulance length, the relative depth of pool, the relative downstream depth, and the relative residual energy were analyzed. In all cases, by increasing the relative critical depth, the turbulance length, pool depth, downstream depth, and relative residual energy were increased. The results showed by increasing the slope of screen, the characteristics of the relative wetted length of the horizontal screen, relative turbulance length, and relative pool depth increases. However, the slope of screen has no effect on the relative downstream depth and the relative residual energy. It was also observed that with increasing porosity ratio of the screen, the characteristics of the relative wetted length of the horizontal screen, relative turbulance length, and relative pool depth decreases, and the relative downstream depth increases. But the porosity of screens has an insignificant effect on the relative residual energy.

The aim of this study is to determine the growth pattern and to investigate the vegetation indices power for sugarcane yield modelling at field scale in Imam Khomeini Agro-industry. For this purpose, the vegetation indices extracted from Landsat7 satellite images were investigated using time series analysis. Overall, 306 Landsat7 satellite images from March 2004 to February 2017 were used. All of the images were converted to surface reflectance via FLAASH algorithm. The average values of 13 vegetation indices related to the study region extracted from satellite images and converted to seven days' time-series via interpolation. In order to eliminate the noise, all series were reconstructed using the Savitzky-Golay algorithm. Thus, 13 different time series of vegetation indices were made for 523 sugarcane fields. Then the growth pattern was drawn via averaging NDVI time series and it was divided into three growth periods. Then the accumulative values of vegetation indices related to the first and second periods of growth stage were extracted since 2004 to 2017. Therefore, 3286 samples were prepared overall, of which 2628 samples were used for modelling and 658 samples for evaluation. The samples extracted from time series were evaluated by simple linear regression model against the average observed yields. The result showed that the accumulative vegetation index of GNDVI for the first growth period with R 2 =0. 47, RMSE=11. 70 ton/ha and the accumulative vegetation index of NDI for the second growth period with R 2 =0. 56, RMSE=10. 62 ton/ha are a better indeces for sugarcane yield estimation as compared to the other vegetation indices. Also, the sum of GNDVI and NDI indeces for summation of first and second growth periods had a better result (R 2 =0. 65, RMSE=9. 47 ton/ha) than that's where one index at one period was used. Finally, the sugarcane yield of 658 samples was estimated for evaluation and the R 2 and RMSE of the best model was obtained to be 0. 58 and 10. 99 ton/ha, respectively. The results of this study confirm the suitability of the GNDVI and NDI indeces for monitoring sugarcane growth during the first and second growth stages.

Appropriate selection of ancillary covariates have a specific important on digital soil mapping. Currently, use of machine learning algorithms for digital mapping and updating of conventional soil map has been developed in Iran. The current study has been done to compare the BRT and RF models for spatial prediction of subgroup and family classes with selection of axillary variables using VIF approach in some part of Qazvin Plain. 61 pedons were sampled based on stratified random, digged, described and classified with consideration of laboratory analysis up to family level. The most appropriate variables were selected among 15 Geomorphometry and Remote Sensing Indices using Variance Inflation Factor (VIF). Soil landscape modeling was conducted with RF and BRT learning algorithm in RStudio software based on Randomforest and C5. 0 packages at subgroup and family levels. The results showed that six indices including CHA, DEM, STH, SI DVI and NDVI were selected as input variables. Assessment indices such as the Overall Accuracy (OA) and Kappa were obtained for BRT (35, 26%) and RF (70, 60%) at family level, respectively. Sensitivity analysis based on the mean decrease accuracy (MDA) revealed that the modified catchment area variable is the most relative important variable among the selected variables. Generally, by using feature selection innovative approach and effective learning algorithms, the spatial distribution of soil maps could be made even in low relief lands with acceptable accuracy.

Surveying of soils along a toposequence is a primary key for identification of the spatial variability and development of soils that have been performed continuously at a certain direction. The main objective of this study is to assess both clay mineralogy and Sorensen similarity index to describe the genesis and development of soils in Fasarood region. In this context, three major physiographical units were recognized in this area (i. e., Colluvial fan, Piedmont plain and Flood plain). Moreover, nine presentative pedons were digged according to physiographical map units in the direction of NW to SE. Typic Endoaquepts and Oxyaquic Haplustepts are identified as dominant soils in the flood plain in which the redoximorphic and gleyzation processes have been occurred. Fluventic Haplustepts and Typic Calciustepts were recognized in the piedmont plain along with an irregular decrease in organic-carbon content as well as calcic horizon, caused by erosion and sedimentation, respectively. Typic Ustorthents is the major soil of Colluvial fan that have more than 60% coarse fragment in subsurface horizon. The results revealed that smectite, illite, cholorite, palygorskite and kaolinite were dominating minerals in colluvial fan, piedmont plain and flood plain. According to the similarity index, 0. 5, 0. 54, 0. 55, 0. 74 and 0. 74 were achieved for order, suborder, great group, sub group, and family levels, respectively. Generally, similarity index could better describe soil variation in different slope position than clay mineralogy due to its quantity approach.

The erosion of riverbeds is one of the factors that causes changes in the morphology of rivers. Scour depth represents the amount of potential degradation of the flow around hydraulic structures located in the flow path. Therefore, it is necessary to determine the scour depth and flow rate. In this study, the experimental results of bed topography changes and flow patterns around impermeable and impermeable groines are compared. For permeable groines, two types of gabion groines and one and two-row groines with a 90 degree angle to the flow were used. In the use of two-row groine, the two positions are considered parallel and zigzag. Experiments were performed in a rectangular channel with a moving bed of 60 cm width and a flow rate of 28 lit/s and Froude number of 0. 26. The results showed that the trend of maximum scour depth change with increasing permeability decreased. The scour depth in gabion groines is much higher than rod groines with the same permeability. Also, the effect of increasing the row spacing of two-row groines on the prediction of the maximum scour depth for the zigzag type is additive and for the parallel type it is decreasing.

Soil enzymes are considered as a measure of soil biological status. Phosphatase enzymes (alkaline and acid) are very important because of their role in converting organic to inorganic phosphorus and improving plant nutrition. Various factors such as organic compounds and phosphate fertilizers affect the activity of these enzymes. In this study, the effect of humic acid and phosphorous (P) fertilizers on soil rhizosphere phosphatase enzymes, active carbon and P uptake by sugarcane was investigated, conducting a greenhouse pot experiment in south west of Iran. The experiment was performed as a factorial based on complete randomized design, in three levels of P application as triple super phosphate (0, 50% and 100 % of recommended phosphorus application, 250 kg. ha-1, in the region), four humic acid treatments (three immersion levels of setts in 0, 0. 3 and 0. 5% solution of humic acid as well as application of 30 mg humic acid per kg soil treatment) and two harvesting time (45 and 90 days after planting). The results showed that in non-fertilized treatment, the use of humic acid (especially in the form of cuttings immersion) increased P uptake by about twice at the first harvest and by 30% at the second harvest compared to the control treatment. Improvement of P uptake in the soil with deficit P was due to changes in activated carbon in the rhizosphere and also the impact on density and activity of microorganisms and the activity of enzymes such as phosphatase, which increases the availability of P in the vicinity of the plant root. By increasing the phosphorus application, the activity of the alkaline phodphatase enzyme decreased and reached to the minimum measured value dry soil (17% Less than the control).

According to numerous reports about the global warming process and the fluctuations of rainfall, the study of climate change, especially in semi-arid regions of the country's dryland, is necessary in order to adapt to this phenomenon. The purpose of this study was to investigate the current process of climate change and the projection of CMIP5 (Coupled Model Intercomparison Project Phase 5) climate models under the CORDEX (Coordinated Regional Climate Downscaling Experiment) project in dryland areas of Kurdistan province. In this study, Sanandaj, Qorveh, and Zarineh stations were selected as the nearest synoptic meteorological stations to the agricultural research institutes of dryland in Kurdistan province. At first, bias correlation was done on downscaled data of the CORDEX project. Given that the future course of the project began in 2006 and continues until 2100, the data were divided into four time periods. The forecasted climatological data were compared with the observed data from 2006 to 2017, then the projection of climate models in the future periods was considered. The trend of climate change in the past, using the Mann-Kendall test and the Sen’ s slope estimator, indicates a decrease in precipitation and an increase in temperature and potential evapotranspiration. The comparison between predicted and observed data during 2006-2017 showing the high accuracy for temperature and evapotranspiration estimation, and low accuracy for rainfall estimation. Also, according to the projection of climate models at the end of 21st century, temperature and evapotranspiration increase in all climatic models of all stations and fluctuations in rainfall are projected. While precipitation reduction in Sanandaj is expected, more precipitation will occur in Qorveh and Zarineh stations.

Due to climate change and growth of urban communities, the need for groundwater and exploration of these resources are increasing. Therefore, the purpose of this study was to provide a groundwater potential mapping using the geographic information system (GIS) in a region located in Booshehr plain using an ensemble of certainty factor (CF) method with Bagging data mining method. For this purpose, in the first step, 339 well locations were identified in the study area, of which 238 wells (70%) were randomly selected as training points and 101 wells (30%) were selected as validation points. In the next step, 15 factors affecting groundwater such as altitude, slope angle, slope direction, slope length, plan curvature, profile curvature, topographic wetness index, distance from fault, fault density, distance from river, drainage density, rainfall, lithology, Soil and land cover were prepared in ArcGIS 10. 3 and Saga GIS software. The spatial relationship between the effective parameters and the location of the wells was determined using a CF model. These weights were used to implement the Bagging model. In order to validate the accuracy of the ensemble model, the RMSE and MAE indices were used. Also, in order to validate the accuracy of the maps, ROC and AUC were used. The results of this study showed that the values of RMSE and MAE indices for training and validation are equal to 0. 247, 0. 162, 0. 256 and 0. 169 respectively. The evaluation results of the ROC curve indicated that the AUC was 86. 2 and 94. 8%, respectively, for CF models and the ensemble of CF model with the Bagging model.

The semi-portable sprinkler irrigation system is a base irrigation system in the irrigation network of tropical region in Ilam province. The climatic condition of tropical regions of Ilam, especially Mehran plain, is such that the average wind speed in May to September is more than 16 km/h and the use of sprinkler irrigation due to high temperature, low relative humidity and high wind speed faces to a severe limitations. For this purpose, it is necessary to develop a system that is able to cover land in summer planting which is not suitable for sprinkler irrigation. The objective of this research was to study the hydraulic and economic feasibility of switching sprinkler irrigation systems into drip tape irrigation (integrated) in summer planting. For this purpose, different scenarios for developing of infrastructures required for converting sprinkler irrigation to drip tape irrigation system were designed and then these scenarios were analyzed in terms of hydraulic (WaterGEMS software) and economic factors. The results showed that the cost of provision and implementation of infrastructure for converting sprinkler irrigation to drip tape irrigation system is ranged between 15. 1 to 15. 8 million Rials (5. 7 % total costs of the Sub-network) and the annual operating cost is 19 million Rials. Development of integrated irrigation systems at 12350 hectares of arable lands, will save water consumption by 8. 85 MCM and increase net revenues from 145709 to 165731 million Rials.

Prediction of bacteria transport to groundwater is very important to prevent water resources from coliform bacteria pollusion. The objective of this study was to investigate the effectiveness of microbially induced calcium carbonate precipitation (MICCP) in preventing the transport of Escherichia coli as an indicator coliform. For the MICCP process, the sand sample was poured into PVC tubes (with inside diameter of 4. 8 and height of 14. 92 cm) and incubated for 3 days in the presence of Sporosarcina pasteurii. After the stablishment of steady-state flow, 0. 1 pore volume of Escherichia coli suspension (10 8 CFU/mL) was added to the sand column and the leaching was followed with distilled water. The column effluent was sampled in 0. 1 to 5 pore volume. After leaching, the sand column was sliced into five sections (~3 cm), and the number of E. coli trapped in each slice was measured using the plate count method in EMB agar culture medium. Leaching was also carried out in control sand column. The effect of MICCP treatment and its interaction with pore volume was significant (p<0. 05) on Escherichia coli count in effluent. The effect of depth and its interaction with MICCP treatment were significant (p<0. 05) on E. coli residuals and bioprecipitated calcium carbonate in the column. Overall, the role of biopreciptated calcium carbonate was significant in bacteria filtration, as it decreased the sand column hydraulic conductivity and reduced the number of E. coli in column effluents.

Arsenic metalloid is a toxic contaminant and has a high carcinogenic effect. One of the new and effective methods to reduce the concentration of arsenic in contaminated water is to use mineral amendments. The purpose of this research is to investigate the reduction rate of arsenic in water using magnetite nanoparticles, titanium nanoparticles, ferrosilicon and magnesium ferrosilicon. In this study, the effect of time, initial concentration of arsenic, the amount of adsorbent and pH on variation of arsenic concentrations of solutions were studied by performing batch experiments. The equilibrium time, the optimum amount of adsorbents and the most suitable adsorbent were determined and the adsorption isotherms were plotted. The equilibrium time was two hours for magnetite nanoparticles and titanium nanoparticles, 16 hours for magnesium ferrosilicon, and 24 hours for ferrosilicon. Freundlich isotherm showed greater correlation with test data (R2≥ 089). With increasing pH, the percentage of arsenic removal decreased and maximum removal (90%) was observed by iron nanoparticles and titanium at pH = 3. Magnetite nanoparticles and titanium oxide nanoparticles were more efficient adsorbent. Ferrosilicon and magnesium ferrosilicon were cheaper adsorbents for removal of arsenic from water.

To investigation the efficiency of phytoremediation, bioremediation and bioaugmented phytoremediation to remove crude from the soil, a factorial experiment was conducted in a completely randomized design with three replications. The treatments consisted of 3 levels of oil concentrations in the soil (0, 4 and 8% by weight), four treatments of plant (no plant, bermudagrass (Cynodon dactylon), sorghum (bicolor Sorghum) and barley (Hordeum vulgare)) and 3 treatments of fungi (no fungi, native fungi and Non-native fungi (Phanerochate chrysosporium)). In this study, the isolated fungi from polluted soil was Aspergillus niger. Samples of five kilograms of soil were polluted with different amounts of crude oil and poured into plastic pots. After six weeks, some pots were inoculated with fungi, then all pots were planted with the proposed gramineae species. The results showed that the application of plants significantly increased the removal percentage of crude oil compared to the control. The removal percentage of crude oil was corresponded to cultivated soils of sorghum, bermudagrass, and barley, in desending order. Inoculated soils with fungi increased the removal percentage of crude oil significantly as compared to the control. The native fungus had more efficiency than the non-native fungus in terms of degradation of crude oil. Also, their combined application of bioaugmentation and phytoremediation (bioaugmented phytoremediation) was significantly more than the application of each method alone (phytoremediation and bioremediation); which indicate the better efficiency of the bioaugmented phytoremediation method than the phytoremediation and bioremediation method individually.