مجله تحقیقات آب و خاک ایران
سال پنجاه و یکم شماره 10 (پیاپی 58، دی 1399)

Piano Key Weirs (PKWs) are amongst the newly developed long-crested weirs that offer a higher discharge capacity relying on their more extended crest compared to labyrinth weirs of the same width. However, the use of barriers at the outlet of PKWs to increase energy dissipation has received little attention so far. In the present work, stepped and baffled models (with a bench height of 30 mm and baffle dimensions of 30 * 30 mm) were adopted to conduct experiments, and the Flow3D software was used for 3D simulation. Experiments were performed using discharge rate of 10 to 50 lit/s. The results revealed by increasing the discharge rate, the energy dissipation reduces. The energy dissipation rate using the baffles was 8.75% higher than that of the stepped model, and 15.21% higher than that of the case with no barriers.

Fodder plants are the most important crops in the world, because these plants provide fodder for millions of livestock in the world, which in turn feeds millions of people. In order to evaluate the effect of drought stress on some agronomic traits and forage palatability of cuctus, an experiment was carried out on the basis of a randomized complete block design consisted of four treatments; the supply of water based on 56, 24, 15 and zero percent of the plant dry matter (rain-fed farming condition) with three replications in Research farm of Dasht-e-Zahab (2017-2018). The results showed that there is not a significant difference between the drought stress (23.34 and 18.28, respectively) and normal irrigation (23.17 and 20.18, respectively) in terms of length and width of pad in moderate drought. The maximum fresh yield was obtained in years of 2017 (65.46 t.ha-1) and 2018 (64.88 t.ha-1) in the no-stress treatment. The fresh yield was 60.04 t.ha-1 in the moderate-stress treatment. Also, the maximum dry yield was obtained in the first year of no-stress treatment which did not have a significant difference with the moderate-stress treatment. The ratio of elements concentration in the young pads to the 1- and 2-year pads were respectively 33.43 and 23.4 percent for P, 0.14 and 21.48 percent for K, 2.47 and 21.55 percent for Ca and 66.01 for Na. The results showed that the deficit irrigation increased nutrition accumulation and forage palatability of the crop. Also, dry and wet forage showed a positive significant correlation with the length and width of pad and forage palatability. Therefore, it is possible to achieve similar forage with normal irrigation treatment by applying moderate drought stress. Cactus pear with its high efficiency in converting water to dry matter, produces significant forage and helps to revive vegetation in drought conditions.

The aim of this study was to investigate the effect of different levels of sewage sludge and its biochars on availability and release kinetics of Cu in a contaminated calcareous soil. For this purpose, the sewage sludge and its biochars produced at two temperatures including 400 and 600 0C were added to a contaminated calcareous soil at 0, 0.5 and 1% levels (w/w), and samples were incubated for 5 months. The kinetics of Curelease was determined by successive extraction with DTPA-TEA in periods of 1 to 504 h in the amended and control soils. Results showed that the desorbed Cu from the soils treated with 0.5 and 1% sewage sludge significantly increased (p < 0.05) as compared to the control soil, whereas, the amount of Cu desorbed from soils treated with 0.5 and 1% biochar produced at 400 and 600 0C significantly decreased (p < 0.05), as compared with the control soil. Desorbed Copper from treated soil with 1% biochar produced at 600 0C was reduced 54.2% as compared to the control soil. The comparsion of release rate constants indicated that the highest and lowest desorption rate of Cu were observwd in 1% sewage sludge and 1% biochar produced at 600 0C treatments respectively. Overall, the results demonstrated that the conversion of sewage sludge to biochar is a suitable method for its management and it can be used for stabilization and remediation of Cu contaminated soils.

Heavy metals have received much attention in recent years due to their stability in the environment and pollution potential in the soil. In sediments, a significant proportion of toxic metals are absorbed by clays and remain for a long time, so they can increase the severity of air pollution due to dust which is rising by wind. The aim of this study was to investigate the contamination level of heavy metals in Hooralazim wetland sediments which known as dust zone. For this purpose, 65 samples were collected from 0-15 cm depth of Hooralazim Wetland sediments and the concentration of heavy metals were measured using atomic absorption spectrometry. In order to evalute the contamination level, Molar geochemical index, enrichment factor, contamination coefficient and contamination load index were calculated. Based on the molar geochemical index, the results showed Cd, Ni and Cr were in the non-contaminated range to moderate contamination and Pb, Cu, Zn, Fe and Mn were in the non-contaminated range. Also, based on the enrichment factor, Cd had the highest enrichement, Ni and Cr had moderately enrichement and Pb, Cu, Zn, Fe and Mn had low enrichment. Contamination coefficients were also found to be low for Pb, Cu, Zn, Fe and Mn, moderate for Ni and Cr and high for Cd. The contamination load index showed no pollution for the sediments. Therefore, based on the calculated indices, the amount of Cd, and then Ni and Cr were above the standard level. Since, the effluents of industerial, oil fasilitiess and chemical fertilizers are entering into Hoorolazim wetland.

Today, the effects of climate change and global warming have been demonstrated by rising greenhouse gases. Occurrence of these conditions affects hydrological processes such as precipitation and river flow, which is one of the main sources of water for the basin. In this study, the monthly values of precipitation, temperature and inflow of Jamishan Dam during the period of 1988-2017 are considered as the basic period. The output of climate models does not have the desired accuracy and spatial and temporal resolution, so it is necessary to downscale the output of CMIP5 models for the study area. In this study, using Change Factor Method (CFM), the data of two FLO_ESM and CNRM_CM5 models were downscaled under the RCP8.5 scenario and the monthly temperature and precipitation parameters of Jamshan dam were produced for the period 2021-2050. To evaluate the effect of climate change on runoff in the region, SVM, GEP and IHACRES models were studied and compared. The results of climate model indicate an increase in temperature between 0.1 to 1.4 degrees of Celsius for both FLO_ESM and CNRM_CM5 models. Also, the results of simulated precipitation in FLO_ESM and CNRM_CM5 models show that the monthly long-term average under the RCP8.5 scenario in the next period decreased 1.1 and 5.8%, respectively, as compared to the baseline period. In general, the results show a reduction in runoff in all three models (SVM, GEP and IHACRES), which the highest reduction (28.9%) is corresponded to SVM in FLO_ESM model and the lowest reduction (14.1%) is corresponded to GEP in CNRM_CM5 model. In this study, GEP and IHACRES models are more accurate than the SVM model.

Wetlands as the most important aquatic ecosystems, in addition to include many ecological values, have provided many goods and services to local communities. Determining the amount of water required to simultaneously preserve the environmental and socio-economic values ​​of wetland stakeholders, is essential given the key role of water in functions dependent on aquatic ecosystems. Normally, socio-economic issues are less considered in calculating the water needs of wetland ecosystems, but in comprehensive approaches within the IWRM framework, in addition to hydrological and ecological issues, socio-economic issues related to the livelihood of human communities are also considered. In the present study, Anzali International Wetland was selected as a case study, and the required depth and volume of the wetland for tourism purposes was determined using a combined method that uses hydrological, ecological, and socio-economic methods. In this method, at first, all the services that the wetland provides to local stakeholders were identified through face-to-face interviews, observation, and review of resources, and it was shown that in socio-economic issues, boating tourism is one of the most important factors in determining the required water of the wetland. In the next step, the locations of cooperatives and boating docks were identified, and by selecting ecological-tourism indicators, the optimal routes for moving motorboats to these places were identified.  By estimating the depth of water required for the movement of boats, the volume of water required for the tourism water needs in Anzali Wetland was estimated to be 130 million cubic meters, which is 50 million cubic meters more than the current volume of the wetland and also less than the minimum ecological needs of the wetland.

Due to limited water resources and the problem of water distribution in irrigation and drainage networks and non-compliance of plant irrigation needs with existing irrigation periods, a water stress is introduced to the plants systematically. Therefore, in this study, two production functions of Raes (2004) and Tafteh et al. (2013) were evaluated for corn using the yield response factor suggested by Tafteh et al. (2014a). For this purpose, two varieties of corn 500 and 302 were harvested in two years of cultivation with irrigation treatments of 100, 75 and 50% of water requirement and their yield values were evaluated using the proposed functions. The results showed that both production functions in determining corn yield of 500 and 320 together with the amount of root mean square error is about 591 kg / ha, the normal root mean square error is about 8% and the mean bias error is about 25 kg / ha. The agreement index was about 0.94 and the efficiency factor index of the model was about 0.81. These statistical results showed that the proposed functions are highly effective in determining the yield of both varieties. A separate study of these two varieties also showed that the 302 cultivar has lower yield and in water shortage conditions, its sensitivity to the plant, especially in the middle period of growth, is higher than the 500 cultivar. Therefore, cultivar 500 has a higher yield than cultivar 302 and in water shortage conditions, its sensitivity coefficients are less and it shows more resistance to water stress. Yield response factor of cultivar 302 in the initial, middle and final stages of growth were determined to be 0.5, 1.4 and 0.8, respectively Which is different from the suggested values.. Therefore, it is necessary to evaluate the proposed cultivars in water stress conditions using production functions.

Controlling relative residual energy values, relative depth, and downstream Froude numbers are important issues faced by designers of inclined drop structures. In this study, 60 different experiments including three angles and two drop heights with subcritical flow at upstream were performed to investigate the effect of using gabion structure in inclined structure in comparison with using the stilling basin downstream of this structure. The results showed that for all experiments, increasing the relative critical depth increases the relative residual energy values and downstream relative depth. Relative energy values and relative downstream depth were significantly reduced when the gabion structure was used in inclined drop and the inclined gabion drop was constructed. The inclined gabion drop reduced the relative energy remained at downstream by 30, 33, 30, and 36 percent as compared to the standard type one, two, three and four stilling ponds, respectively. The average relative depth of downstream was also reduced 37, 40, 37 and 43% as compared to the standard type one, two, three and four stilling ponds, respectively. The range of Froude numbers reduced from 4.49-8.35 to 1.28-2.64. Also, some relationships were presented for estimating relative residual energy and relative depth at downstream of the gabion inclined drop structure.

Precipitable Water Vapor (PWV) is one of the most important quantities in meteorology, atmospheric physics, hydrology and climate change studies, which its estimation is useful in predicting precipitation, flood occurrence and other hydrological parameters. Today, satellite imagery is widely used to estimate PWV and analyze its correlation with other meteorological Variables. The objective of this study was to estimate the amount of PWV and to investigate its relationship with six climatic variables such as; temperature, pressure, relative humidity, cloudiness ratio, precipitation and wind speed in the geographical area of Iran using satellite-based data.The proposed data with monthly time steps and 1°*1° spatial resolution were selected in the climatic range of Iran's atmosphere for the period of 2003-2019. Pearson correlation coefficient was used to investigate the relationship between PWV and the above mentioned climatic variables. Digital data extracted after qualitative control and pre-processing were used by specialized software such as ENVI, ArcGIS and Grads to build raster layers based on the geographical boundary of Iran.  According to the results, the average PWV in the atmosphere of Iran is 12.7 mm, which shows a lower amount as compared to the global average (21.6 mm). On the other hand, the amount of PWV in the Atmosphere of Iran does not have a temporal and spatial homogeneous distribution. So that the highest amount of PWV is concentrated in the coastal area of south and north and the lowest amount is concentrated over the Zagros mountain range, parts of northeast and east of Iran and in the next priority in the desert areas of central Iran. The Pearson correlation coefficients between PWV and the meteorlogical variables were 86% for air temperaure, - 89% for pressure, - 88% for relative humidity, - 32% for cloudiness ratio, - 64% for precipitation and  67% for wind speed.

The present study was carried out to investigate the effects of biological and chemical fertilizers on morpho-physiological characteristics and nutrients uptake in tomato plant (Lycopersicon esculentum Mill). A factorial trial arranged in a completely randomized design was carried out under greenhouse conditions. Treatments consisted of five levels of  chemical fertilizers applied as: control (F0), fertilizer traditionally used (F1), soil-test-based optimum nutrients levels (F2), commercial root stimulant (F3), optimum nutrients levels + application of N, P, Zn and Si by the rate of twofold of the optimum levels (F4) and five levels of  biological fertilizers including: control (BF0), PGPR (BF1), arbuscular mycorrhiza fungi (BF2), vermicompost (BF3), and biological package (BF4).The results indicated that the interaction effect of treatments was significant only for shoot dry weight. F4-BF4 and F2-BF4 treatments increased shoot dry weight up to 122% and 121% compared to the control (F0-BF0), respectively. The application of BF4 incresed the leaf area 55% and the application of F4 increased SPAD chlorophyll index 29% as compared to the control and they were the best for increasing such properties.  Among the biological treatments, the application of BF4 increased the uptake of N, P, K and Si in the shoot by 108.4, 224.7, 115.6 and 226.3%, respectively, and among the chemical treatments, the application of F4 increased the uptake of these elements by 58.7%, 14.9% 25.1% and 158% in comparison with control, respectively. The results of this study showed that in the soils with high pH, the nutrients uptake of tomato plant can be effectively improved via integrated application of vermicompot and chemical fertilizers under both optimum and even higher levels.

Risk-based optimization in flood diversion system is a framework that allows the designer to involve uncertainties in the decision-making process and determine the reliability of the hydraulic structure. This study was conducted to incorporate hydrological and hydraulic uncertainties in the probabilistic design of Karun-4 diversion system in Khuzestan province, southwestern Iran. The risk-based multivariate probabilistic model was developed for determining the effect of uncertainty sources on the characteristics of the flow diversion system. For this purpose, the time series of annual maximum peak flow and maximum flood volume data for a period of 37 years were prepared and evaluated. Archimedean copula function and non-dominated sorting genetic algorithm were adopted to minimize the overtapping risk and construction cost as objective functions. Diameter, slope, wall covering and tunnel entrance height, cofferdam height at upstream and downstream were searched as decision variables in the possible space of the problem. The results show that optimal values of upstream cofferdam height, downstream cofferdam height and the diameter of the first and second tunnels were estimated as 44.5, 12.5, 10.5 and 9.9 m, respectively, all corresponding to 25-year return period. Moreover, the results suggest that the proposed framework could be valuable for decision makers when economic, hydraulic and hydrological uncertainties are expected.

Irrigation interval and fertilizer amount have an important effect on sugar beet yield. This study was conducted to evaluate AquaCrop and WOFOST models in terms of simulation of sugar beet yield and water productivity at Qazvin agricultural research station during three years. For this purpose, two treatments were considered; irrigation water management in four levels (6, 9, 12; and 15 days) and Boron fertilizer amount in three levels (21, 30 and 39 kgha-1; as low, medium and proper amounts, respectively). RMSE values for yield simulated by WOFOST and AquaCrop models were 0.29 and 1.07 ton.ha-1, respectively. RMSE values for water productivity simulated by the proposed methods were 0.61 and 0.14 kg.m-3,, respectively. RMSE values for yield simulated by WOFOST and AquaCrop for irrigation treatments were in the range of 2.78-3.50 and 1.91-2.26 ton.ha-1, respectively, and for fertilizer treatments were in the range of 2.34-4.51 and 1.14-2.94 26 ton.ha-1, respectively. The amount of error for water productivity simulated by WOFOST and AquaCrop models for irrigation treatments were in the range of 0.34-0.48 and 0.16-0.38 kg.m-3, respectively, and for fertilizer were in the range of 0.30-0.56 and 0.15-0.41 kg.m-3, respectively. Thus, AquaCrop model had better accuracy compared to WOFOST model for separated treatments. In general, WOFOST accuracy was good. According to the results, it is recommended by caution to use WOFOST model to simulate sugar beet in the simulation of irrigation treatments with fertilizer.

Agriculture is directly affected by climate conditions and changes; therefore, it is essential to understand the effects of climate change on agricultural water resources in order to adapt negative effects on sustainable crop production. In this study using three scenarios; RCP2.6, RCP4.5 and RCP8.5 of the HadGEM2-ES climate model, the future climate data (precipitation, minimum and maximum temperatures) for two periods (2020-2039 and 2040-2059) were forecasted under climate change and based on a 20-years basic period (1985-2005) climate data using LARS-WG software. The base-period evapotranspiration was estimated using Hargreaves-Samani method and they were converted to Fao-Penman-Monteith method by Coefficient (G) in order to improve accyracy. According to this, irrigation requirement of rice (most important and major crop in Gilan province) and evapotranspiration were compared between the past and future. Results declared that the average annual maximum and minimum temperatures for the periods of (2020-2039) and (2040-2059) in comparison to the base period, will increase 2.2 and 2.1, 3.2 and 2.8 ˚C respectively. Also, the average monthly rainfall under all three scenarios will increase 11.8 and 13.6 millimeters for the proposed future periods, respectively. In addition, the net irrigation changes of rice for the both proposed periods will increase 0-31% and 0-45%, respectively. The trend of evapotranspiration changes is ascending and the range of changes during the two periods will be 0.4%-13.6% and 6.1%-27.6%, respectively. This method demonstrated the outlook of climate change impacts on irrigation to the farmers. The results of this study suggest that it is necessary to understand climate change impacts on agriculture, for improved agricultural management planning. The results of this study highlight the need to pay more attention to the effects of climate change on reliable agricultural management and planning.

The increase in dust storms occurrence in recent years in southwestern Iran, especially in Khuzestan province, and consequently the decrease in air quality in these areas, has doubled the importance of forecasting and linking this phenomenon with climate variations. The aim of this study was to investigate the efficiency of hybrid Genetic-Annealing (GA-SA) and Genetic Algorithm (GA) methods for selecting optimal input variables in forecasting the frequency of days with dust storm (FDSD). For this purpose, hourly dust data and meteorological organization codes, as well as climatic data including maximum temperature, minimum temperature, average temperature, total rainfall and maximum wind speed on a seasonal scale with a statistical period of 35 years (1984-2018) in seven synoptic stations in Khuzestan province were used. Then, by having a time series of FDSD index and other climatic variables, it was compared to the efficiency of different modes of input variables, in order to forecasting the frequency of days with dust storm in the next season. The results showed that the hybrid Genetic-Annealing method (GA-SA) had the best performance among all the modes of selecting the input variables; In this case, the evaluation criteria of R, MAE and RMSE varied from 0.91, 0.29, and 0.44 to 0.99, 0.13 and 0.17 in the studied stations, respectively. Also, the average frequency of days with dust storm on a seasonal scale in the studied stations varied from 1.68 to 4.10, respectively, so that with increasing FDSD index in the study station, the predictive accuracy of all modes increased so that in the first forecast state (based solely on the FDSD index), the correlation coefficient between the observational values of the days associated with dust storms and its computational values increased from 0.87 to 0.95. For the second case (forecast based on frequency of days with dust storm and all Auxiliary Characteristics, ie FDSD & AC), the third mode (based on the optimization of the Genetic Algorithm) and the fourth mode (based on the hybrid Genetic-Annealing method) the correlation coefficient also varied from 0.93 to 0.94, 0.91 to 0.97 and 0.94 to 0.99 in the studied stations, respectively. In general, by comparing the modes used, the hybrid Genetic-Annealing method (GA-SA) performed the best, followed by the Genetic Algorithm (GA). The results of this study can be useful in managing the consequences of dust storms and desertification programs in the study areas.

Determining the trend of soil temperature change is of special importance due to the close relationship with sustainable agricultural management. In this study, in order to investigate the trend of soil temperature change in three stations of Kangavar, Kermanshah and Sarpolzahab, which have different climates, a series of daily soil temperature data for 25 years (1993 to 2018) of these stations were obtained from the meteorological organization of the country. Using daily averages of soil temperature, the averages of warm period (spring and summer) and cold period of the year (autumn and winter) and the averages of annual were adjusted and calculated based on the solar calendar. Mann-Kendall and Sen’s slope estimator tests were used to analyze the soil temperature trend at 95 and 99% confidence levels. Analysis of Kangavar synoptic station data series showed a significant upward trend using the both tests for annual soil temperature averages. In Kermanshah station, despite the increase in soil temperature values ​​at all depths, no significant trend in the average annual soil temperature was observed. Sarpolzahab station also did not show any trend. In Kangavar and Kermanshah stations, the increasing trend in soil surface temperature showed a higher value, which is due to the greater influence between soil surface temperature and air temperature. The average of temperature increase in 5-cm soil depth for Kermanshah and Kangavar stations were estimated to be 0.04 and 0.10 degree of Celsius per year, respectively. The increase in the average annual soil temperature of stations with increasing trend was recognized in the warm period of the year, mainly due to heat storage.

Predicting volume of water stored in reservoirs in the future periods plays an important role in planning and managing the optimal use of water resources systems. In this study, time series analysis method was used to predict the monthly inflow to Yamchi and Sabalan reservoirs in Ardabil province. The monthly flow data measured at hydrometric stations, located at the dam's entrance for 21 years (1994 to 2015) were used to build and test an appropriate model. The structures of the seasonal models were identified according to the auto-correlation charts (ACF) and partial auto-correlation (PACF), and then the appropriate model for each hydrometric station was selected based on the Akaike Information Criterion (AIC), Akaike Information Criterion Correction (AICC) and Bayesian Information Criterion (BIC). By fiting the model to the observational data, the parameters of each model were determined and the adequacy of the selected models was also examined by diagnostic tests. The results showed that ARIMA (1,0,0)(0,1,1)12 and ARIMA (1,1,1)(0,1,1)12 models, respectively for the monthly flow data of Yamchi and Arbabkandi stations have the lowest root mean square error (RMSE) and mean absolute error (MAE) and the highest determination coefficient. The values of these indicators in the model related to Yamchi hydrometric station were 1.04, 0.606 and 0.63, respectively, and for Arbabkandi hydrometric station were 1.35, 0.8 and 0.74, respectively. Therefore, the selected models accurately predict the monthly inflows to Yamchi and Sabalan reservoirs. Comparing the predicted results with the observational data showed that the selected models are not very accurate in predicting high discharge values.

Land suitability assessment is essential for optimal use of agricultural lands. In this research, Root Mean Square (RMS) method and Analytical Hierarchy Process (AHP) have been used to evaluate the land suitability of Alghoorat region (with an area of 133.2 km2 located in South Khorasan Province) for Jujube and barberry. 12 control profiles were studied out of 50 primary profiles. Questionnaires for barberry and jujube were prepared and completed by farmers and experts. First, some physical and economical properties (income subindex) were studied. According to the results of the questionnaires, weights were given for each factor and separately for each type of productivity, based on its effect on land suitability. Finally, the weights and degrees of suitability for each property were combined together in the Expert Choice software, and suitability classes were determined according to the FAO standards. The results showed that the suitability of climate was high (S1) and the most important soil limitations were slope, lime and texture. The climate and moisture indices had the highest (0.355) and the lowest weight (0.044), respectively. The range of land indices for barberry and jujube were 10.7 to 75.6 and 11.2 to 77 using RMS method and were 13.4 to 77.1 and 14.5 to 79.4 using AHP method, respectively. Although this difference is very small, the conditions of the region for cultivation of jujube seem more suitable than for barberry. The calculated explanation coefficients between observational production and land indices estimated by RMS method for barberry and jujube were 0.96 and 0.94 and by AHP method were 0.98 and 0.92, respectively.

The purpose of this research is to present a method based on global and experimental algorithms for estimating relative humidity in Sistan and Baluchestan province. For this purpose, Terra MODIS images and products (MOD05, MOD07) of 10-years (1-Jan-2009 to 31-Des-2018) under cloudless conditions were used as selected data. To validate the obtained layers (near ground surface temperature, ground surface pressure, total perceptible water, TPW, and relative humidity), the ground station and the radio sound data were used. The R2 and REMS values of the recorded layers from the sensor and the ground data were acceptable and the sensed data were in good agreement with ground station measurements. Results show that the altitude factor play an important role in temperature measurement. The minimum amount of TPW has been recorded to be 6 mm in the Khash, Mir Java and Saravan regions in the cold season and the maximum amount of TPW has been recorded to be 49 mm in the coastal areas in the warm season. The average relative humidity in the province is in equilibrium in the cold season, while it is out of equilibrium in the hot season, so that it is above 60% on the coast of Oman and less than 10% in the central province (Khash, Mir Java and Zahedan).

The electrokinetic method is classified as one of the physical and chemical methods of purification of contaminated soils. This is one of the most widely used methods for purifying soil and sludge. To improve purification by electrokinetic method, a geotextile membrane was fabricated by the chemical polymerization method based on Pyyrole polymer and copper oxide nanoparticles. The membrane was placed in direct contact with the copper electrode in the electric field.  To evaluate the effect of membrane in the electrokinetic removal process, a physical model was designed and filled with copper contaminated kaolinite with concentration of 200 mg/kg. For desorption of copper, 0.01 M potassium chloride was used as anolyte and catholyte solutions. 0.1 M hydrochloric acid was injected into the catholyte chamber at a constant rate of 0.6 mL/h. According to the results, Employing the fabricated membrane in an electric field accelerated the removal of copper by the electrokinetic process. In spite of reducing the outflow (in the test employing the fabricated membrane), the residual copper concentration in the outflow was six times of the residual copper in the control test. The removal efficiency of copper adjacent cathode electrode was increased from 29.5% in the control test to 38% in the test employing the fabricated membrane, which indicates the ability of fabricated membrane in electrokinetic purification. The amount of copper accumulation in the test employing the fabricated membrane was reduced adjacent anode electrode and reached 29% compared to the control test.

This study was conducted to investigate the effects of coated nanosilicon oxide with humic acid (coHA-nSi) on yield, ion composition and salt tolerance of black cumin (Nigella sativa L.) in 2017-2018. The experiment was performed in the form of split-plot based on Randomized Complete Block Design with four replicates under greenhouse condition. The main plot was salinity levels including 2 (control), 3.5 and 5 dS/m. The sub plots was SiO2-nanoparticles including Control (without nanosilicon oxide), uncoated nanosilicon oxide (0.5 g/l) and coated nanosilicon oxide (0.5 g/l) which were applied in multi leave stage (15 days after planting) and flowering stages (50 days after planting). The results demonstrated that the salinity stress decreased yield and its compouents significantly. The application of coated nano silicon oxide increased significantly the seed weight (18.9%) and biomass dry weight (8.9%), dry root weight (23.7), number of capsules (24%) and number of seed (15.9%), harvest index (10.5%) and relative leaf moisture content (20.7%) and decreased significantly the ionic leakage (IL, 18.1%) compared to the uncoated nanoparticles. Also, it increased the uptake of leaf nutrients such as nitrogen, potassium and calcium. Therefore, it is concluded that the silicon nanooxide coated with humic acid could increase the effect of this nanoparticle on salinity tolerance indices, quantitative and qualitative traits of black seed under saline conditions.