مجله تحقیقات آب و خاک ایران
سال پنجاهم شماره 7 (پیاپی 45، آذر 1398)

The application of zeolite and superabsorbent in the soil can be useful in reducing water pollution. For this purpose, this research was carried out in 2018 with two treatments in a completely randomized block design. Each treatment consists of 3 different levels and 4 replications. Totally 24 polyethylene pipes with 10.5 cm in diameter and 50 cm in height were used under unsaturated conditions at research farm of Faculty of Water Sciencs Engineering, Shahid Chamran University of Ahvaz. Treatments in this study included potassium zeolite and A200 superabsorbent at three levels of 0, 2 and 5 g/kg of soil. Urea fertilizer was applied to the soil in irrigation 1, 6 and 12 from 15 irrigation events. At the end of each irrigation event, nitrate effluent was measured. The results showed a significant reduction (at 5% level) of nitrate leaching in the superabsorbent and zeolite treatments in all irrigation events (with the exception of No. 6 irrigation event in zeolite). Superabsorbent treatment (2g/kg of soil) had better performance than the zeolite treatment (2g/kg of soil) in terms of preventing nitrate leaching, with the exception of irrigation events of 6 and 7. In general, zeolite and superabsorbent treatments (2 and 5 g/kg of soil) reduced nitrate leaching (20 and 29%) and (48 and 64%), respectively, as compared to the control treatments.

Lake Urmia, as one of the most important lakes in the country, has an inappropriate environmental condition due to excessive consumption of water and climate change. The study of climate change and rainfall distribution in this area can improve water management in this basin. In this study, the information of 65 weather stations in the period of 1997-2016 were used for precipitation zoning of Urmia lake basin. For this purpose, the data of each month were standardized and arranged in a matrix with dimensions of (n*m) in which n is the number of stations (65) and m is the number of months (12). Principal Component Analysis (PCA) was performed on data matrix and the main components were determined according to their Eigen values greater than one. Then the principal component score (PCS) values were calculated for the selected components. These values were used as inputs in the Ward cluster analysis method. Then, the Procrustes method was used to determine the index stations. The results showed that the first two main components incorporated more than 87% of the all data variances. Based on the selected components, six distinct precipitation regions were identified throughout the basin. Moreover, it was found that four stations located in different points of the Urmia lake basin namely Mehmandar, Sarab, Babaroud and Santeh can be considered as indicator stations. These stations incorporated more than 84% of the all data variances of basin stations. The Mann-Kendall trend test showed that the rainfall in the autumn season has a significant increase trend, while annual precipitation has only a significant increase trend in one of the clusters.

Arsenic is a metalloid that is toxic to plants, animals, microorganisms, and humans. WHO has set the permissible limit of arsenic in drinking water at 10 μg/l and various literatures have reported this limit for the soil to be 20 mg/kg. The concentration of arsenic in water and soil at different parts of Iran (areas with concentrations higher than the permissible limit) have been reported to be 10-840 μg/l and 23.1-1775.2 mg/kg, respectively. The major sources of arsenic contamination in Iran are gold and copper mines (especially Takab and Kerman areas) and Urmia-Dokhtar volcanic formation, which contain various heavy and toxic metals. The most mines of Iran are located on this formation and the use of old mining techniques and equipment has increased the severity of the contamination. In addition, the use of pesticides, insecticides, and other agricultural inputs has led the entry of arsenic into these resources. Using the genetic diversity of plants (plants resistant to arsenic), remediation of arsenic contaminated environments and increasing the concentrations of plant nutrients such as iron, manganese, phosphate, sulfur, and silicon in the soil or growth medium, can greatly reduce the concentration of arsenic in plant tissues, especially in rice. The use of modern equipment in mining can be useful to reduce environmental pollution. Contamination of surface and subsurface water to arsenic in 13 provinces of the country indicates the serious threat of arsenic to people's health and this makes decontamination of water in these areas compulsory.

The Easiness of mining from the rivers and its low cost have increased use of these resources. In the present study, the effects of pit migration and development on the bridge inline piers were investigated experimentally. The circular and sharp rectangular shapes of the piers have been employed in this study. The results showed that the pit holes are developed to the downstream and upstream bridge piers in order to achieve sediment balance, which causes piers scouring at downstream and upstream. Also, the development of the holes towards upstream pier is more than the downstream pier. Regarding to aero-dynamical shape of the rectangular sharp nose bridge, the magnitude of the scouring hole at the up and downstream is reduced 24.5 and 31.55% respectively as compared to circular piers. Finally, the empirical relationships related to the maximum length and depth of scouring were derived. By using these relationships, the geometric and effective statistical parameters on the pier scouring, as well as the relative error percentage and RMSE of the obtained functions were evaluated and the depended graphs were depicted. It was found for both sediment dimensions, by reduction of the hole depth and Fr number, the dimensionless parameter of the H/y(the pit holes depth to flow depth) is decreased and the L/y and B/y (the pit holes length and width to flow depth) parameters are increased. Finally, the parameters affecting the maximum length and depth of the pit scouring were identified and introduced for both sharp piers.

One of the most commonly used devices for flow measurements in open channels is the flume, in which the flow velocity increases due to the lateral contraction, raising the bottom of the channel, or a combination of both them. SMBF is a flume with the above mentioned properties, having two semi-cylinders on the side walls of the channel that contract the cross-sectional area of the flow. In this study, the SMBF flume has been studied for measuring the flow in free and submerged flow conditions. Using the experimental data (575 runs) of two rectangular channels, and using eight SMBF flumes, the proposed discharge equations were examined for the wide ranges of flow discharge, upstream depth, and contraction ratio. In the present study, based on the numerical and experimental analysis, and by measuring the velocity distribution at the throat section, non-uniformity of velocity distribution and depth in the contracted section, as well as the two-dimensional nature of flow were studied. Then, by considering the flow correction coefficients in the throat section and applying them into the energy equation, an equation was developed for estimating the flow discharge‎ under free flow conditions. Also, two equations were developed to determine the submergence threshold (as a function of upstream depth and throat width) and for the discharge estimation under submerged conditions. The mean absolute relative error of the estimated flow discharge of the SMBF flumes in free flow conditions and based on three experimental data series (channel 1, channel 2, and other researcher’s data) were respectively estimated to be 2.82, 3.19 and 1.52%. Additionally, the mean absolute relative error of the estimating flow discharge in the submerged conditions was 5.51%. The results showed a feasible application of SMBF structure, as a portable measuring instrument under free and submerged conditions.

Spatial variability of soil organic carbon in different land uses could be effective in interpreting and simulating the behavior of ecosystems in encountering the climate and environmental changes. The hilly lands of the study area are unique ecosystem with particular importance due to the effect of slope in creating microclimates with different vegetation. The spatial variability of soil organic and inorganic carbon contents and storages were studied at various depths. The effects of land use, parent material, topographical properties and some of soil characteristics on soil organic and inorganic carbon contents and storages were investigated in 56 soil pedons. In average, the highest (SOC=196.6 Mg/ha, SIC=88.2 Mg/ha) and lowest (SOC=59.9 Mg/ha, SIC=11.3 Mg/ha) storage contents of soil organic and inorganic carbon were found in Mollisols and Entisols, accordingly. The highest average total carbon storage also was found in Mollisols (284.9 Mg/ha) while the lowest was in Entisols (71.2 Mg/ha). Increasing soil inorganic carbon with increasing soil organic carbon indicates that inorganic carbon originates from soil organic carbon. In forestland, most amounts of soil organic carbon stocks are located in surface horizons, in fresh and semi-decomposed forms and in combination with silt fractions. Therefore, forest soils are more fragile in response to the changes in management rather than rangelands that contain most of their organic carbon stocks in subsurface horizons and in combination with clay fractions.

The existing Muskingum models vary only in the form of the storage equation. So far, for accounting the nonlinearity characteristic of flood wave, the form of the storage equation has been modified based on the experience and in a trial and error manner in order to capture the overall flood propagating characteristics more accurately. One of the theoretical based method for considering the nonlinear characteristics in Muskingum model is to use the fractional derivative in the continuity differential equation. This study presents a new Muskingum model in which the linear storage equation and the continuity equation with fractional derivative are used. As shown in this study, the new model can simulate flood waves with both linear and nonlinear behaviors. The proposed Muskingum model with fractional derivative order was implemented and tested on three different sets of flood data. The results of this study indicate that the proposed Muskingum model improves the results and estimates the flood wave characteristics more accurately than the traditional linear Muskingum models.

One of the methods for determination of infiltration equation parameters in border irrigation is the double rings. In this method, the parameters of the infiltration equations can be obtained by measuring the amount of infiltration at different times. Moreover, in recent years, the scale-up has been used to express the dynamics of water in the soil and reduce the required measurements. The objective of this study is to obtain the parameters of the Kostiakov-Luis infiltration equation using minimum field measurements. This research was performed using data from 15 double ring testing in different borders of the field in Zabol University. In this research to obtain the infiltration equation in each point, a reference infiltration equation with only one infiltration measuring time was used. In order to evaluate the accuracy of the method, the mean square error (RMSE) and coefficient of determination (R2) were used for estimating cumulative infiltration. The results showed that the reference curve choice was arbitrary and each of the 15 test points could be selected as the reference curve. The closeness of (R2) to one (0.99) and also low RMSE (0.001) indicate the high accuracy of the method presented in this study. Also, the scale factors obtained based on different infiltration times (0.5, 1, 2, 3 and 4 hours) are not very different. The advantage of the relationship presented in this study is requiring less input data and easier measurement as compared to other previous functions.

Intensive cropping of sugarcane and no application of potassium (K) fertilizer resulted a reduction of K pools in the soil. In order to evaluate the potassium uptake efficiency in two different fertilizer managements, new plantation of sugarcane and ratoon, and to investigate the effect of indigenous plant growth-promoting rhizobacteria on potassium uptake, a pot experiment with three replications was carried out in greenhouse condition. Treatments were the combination of two P rates (including: blank (P0) and 200 kg/ha (P200)), and two plant growth-promoting rhizobacteria strains (including: Enterobacter cloacae R13 (B13) and Enterobacter cloacae R33 (B33)). The morphological characteristics of sugarcane and root and potassium in the rhizosphere were evaluated at three harvesting times (60, 95 and 140 days after planting (DAP)). In management similar to plantation of sugarcane, higher K uptake and influx were found in P200B0 and P200B13 treatments, while the highest root length was observed in P200B33 treatment. In management like to ratoon, the greatest K uptake and influx were observed in P0B33 treatment. At the second harvesting period (between 95 and 140 DAP), K influx decreased severely in P0R0 treatment in comparison with the first harvesting period, while it was not occurred in the inoculated treatments. Therefore, in new sugarcane plantation condition, Enterobacter cloacae R13 improved K uptake efficiency, while in ratoon stage, Enterobacter cloacae R33 abled to increase uptake and uptake efficiency of K. Also, the result showed that the influx was the main mechanism of K uptake in sugarcane in inoculated treatments.

Knowledge of the soils capacity to utilize them in the form of different major uses in agricultural ecosystems and natural resources requires the accurate recognition of the physico-chemical and biological properties of the soil, ensuring the sustainable use of the lands. Therefore, this research was conducted to evaluate the soil quality using quantitative models in the Kane Sorkh lands of Mehran as a part of arid and semi-arid lands of Ilam province (Iran). Soil samples were taken from the depth of 0-30 cm and weighted average for the depths of 30-100 cm of the soil profile. Physicochemical properties were measured based on the standard methods. Using principal component analysis (PCA), among a total 16 soil characteristics (TDS), eight properties were selected based on the eigen values and the correlation coefficient as the least properties affecting soil quality (MDS). Then, soil quality assessment was performed using two models of integrated quality index (IQI), Nemoro Quality Index (NQI), and each in two sets of TDS and MDS. The results showed that the top layer (0-30 cm) have a moderate quality class and the sub layer (30-100 cm of the profiles) have poor quality with severe constraints. According to the results, the most important factors limiting soil quality were organic matter deficiency, high percentage of calcium carbonate, gypsum, gravel and soil salinity. Determination coefficients (R2) for the top and sub-layer samples between the two TDS and MDS sets in both IQI and NQI models were 0.79 and 0.79, 0.95 and 0.94, respectively, indicating the reliability of using MDS set instead of TDS in both models. Therefore, the use of most effective soil properties in the soil quality assessment studies is not only time consuming but also it is cost-effective for sustainable monitoring of agricultural land use.

The knowledge about K forms and its distribution in different soils can help to apply properly K fertilizers. This study was performed to investigate the different K forms in the soil and their relationship with physical-chemical properties and clay mineral diversity of the soil. The results showed that the amount of soluble K had negative correlation with clay content but exchangeable or available K value had positive correlation with clay content. Also, the fixed K value had good correlation with type and among clay content in these soils. Structural K had positive and significant correlation with Fe and clay content but negative correlation with gypsum. Total K had good correlation with clay content and consequently with Fe, Al, and Si that are the main performed elements of the clay particles. The amount of K in the soil was increased with increasing of illite content but it was decreased with increasing the chlorite and palygorskite. The results showed a significant difference between the K values with the presence and absence of OM, CCE, and gypsum in the soils. Generally speaking, the available K content was corresponded to the parent material (clay mineral type), cultivation type and age, heavy irrigation and leaching which causes a reduction in illite clay mineral in these soils.

Recently, the amount of rainfall underwent serious changes in different areas, particularly in arid and semi-arid regions. Therefore, estimation and pattern recognition of rainfall in a long term period can give sufficient information to hydrologists and water engineers. In this study, for the first time, long-term rainfall pattern in Anzali city for a 67 years period was simulated using a hybrid model so-called “Wavelet-Adaptive Neuro-Fuzzy Inference System” (WANFIS). Rainfalls of 37-, 20- and 10-years period were applied for training, testing and validation of the numerical model, respectively. Firstly, the optimized membership function of the ANFIS network was obtained using the analysis of the numerical results. In other words, the number of optimized membership function was computed to be equal to 8. Then, the various wavelet families were evaluated which the dmey mother wavelet was introduced as the most optimized wavelet family. Next, using the autocorrelation function (ACF), the partial autocorrelation function (PACF) and different lags, 15 WANFIS models were developed. According to the sensitivity analysis, the superior model and effective lags were identified. The superior model estimated the rainfall with high accuracy. For instance, for validation mode of the superior model, the correlation coefficient, scatter index and Nash-Sutcliffe efficiency coefficient were computed to be 0.962, 0.258 and 0.899, respectively.

The present study was conducted to investigate the possibility of growth of native bacteria isolated from some kerosene-contaminated soils in Khuzestan province for degradation of oil spills. After the primary stages of enrichment, isolation, and screening, bacteria were identified based on the gene sequences of 16S rRNA gene. The ability of native bacteria as the bacteria using hydrocarbons in the presence of oil products such as kerosene and crude oil at 1% concentration of solid and liquid minimum salt medium (MSM) was measured. A split-plot experiment with a factorial design was conducted with factors such as oil (kerosene and crude oil), bacteria, and time in three replicates, using the microbial inoculation inoculum (with a population of 108 CFU/ml) in both liquid and solid growth environments. The degradation ability of hydrocarbons in solid and liquid growth environments was investigated using colony diameter assessment and turbidity, respectively. In this research, five bacteria belonging to the genera of Microbacterium phyllosphaerae (ZS1.9), Bacillus megateriuns (ZS2.12), Staphylococcus epidermidis (ZS3.170), Streptomyces albogriseolus (ZS4.9), and Bacillus subtilis (ZS5. 210) were identified. The results revealed that the bacteria had the highest and lowest growth in the presence of kerosene and crude oil, respectively. Among the oil products used in this study, kerosene had the highest degradation rate. Furthermore, the ability of bacteria for degradation oil products increased by increasing incubation period. The findings of this study revealed the ability of different bacterial species in bioremediation of environmental pollution to various hydrocarbons.

One of the valid methods for simulation of the complex and non-linear process of rainfall-runoff is to use hydrological models. The purpose of this paper is to investigate the performance of three conceptual and lumped rainfall-runoff models; AWBM, Sacramento and SimHyd for simulating daily runoff at the outlet of the Amameh watershed using automatic calibration optimization genetic algorithm. Similar to other hydrological models, the range of parameters' variations is high in all three models and due to the difficulty of calibrating with trial and error-based methods, in this paper, the use of automatic calibration optimization methods for the hydrological models investigated. Preparation of required maps carried out by the GIS software version 10.4.1. Daily rainfall, potential evapotranspiration and observation runoff data of 2001-2005 used for calibration and 2006- 2007 data for simulations verificasion. The evaluation criteria including Nash-Sutcliff coefficient (NSE), coefficient of determination (R2) and root mean square error (RMSE) used to evaluate the proposed models. The statistical and graphical results of calibration and verification steps showed that SimHyd model performed better than the other two models with Nash-Sutcliff coefficient of 0.575 and 0.731, determination coefficient of 0.61 and 0.80 and the root mean square error of 1.033 and 0.829 respectively in the calibration and verification periods, using the automatic calibration optimization of the genetic algorithm and good graphical matching with the observational values. Also, AWBM and Sacramento models have satisfactory and desirable graphical and statistical results in the selected watershed and emphasize the good performance of automatic calibration optimization of the genetic algorithm.

The normalized water productivity parameter is one of the AquaCrop model’s input, upon which the crop biomass yield is simulated on a daily basis. The necessitate of this research is that the amount of normalized water productivity for spinach has not been determined so far. This research was carried out at the Abourihan Campus farm of the University of Tehran which is located in Pakdasht. The experiments were performed during cultivation year of 2017-2018 with six planting densities of 12, 16, 17, 22, 25 and 33 plants per square meter and four replications with full irrigation. The biomass yield was measured seven times during the cultivation season. Considering the measured data of biomass and relative transpiration, the normalized water productivity was obtained for five treatments. The highest amount of normalized water productivity (12.4 g/m2) was related to 25 plants per square meter density. A relationship function was found using normalized water productivity and planting density data. This function was tested using the remaining treatment and placing the normalized water productivity in the Aqua Crop model. The mean root square error and the mean bias error between the measured and simulated data were 20.9 and 6.6 g/m2 at the test step. The results of this study showed that the planting density affects normalized water productivity and it is increased by increasing planting density (optimum density) and then it is decreased. Finally, this study suggests that the normalized water productivity regarding to planting density is entered to the AquaCrop model.

Regarding to various sources of climatological data, identification of suitable sources and investigation of their usage effects on hydrological simulation is an important issue. Moreover, given that hydrological models employ different methods for preparation of climatological data, e.g. spatial interpolation of point climatological data, evaluation of the effects of different methods on hydrological simulation’s result is an important issue. Accordingly, this paper deals with different data sources and spatial interpolation of precipitation that are investigated in hydrological simulation of Mahabad Chai River Basin using SWAT model. Different climatological sources, i.e. field measurements of meteorological stations of MOE and IRIMO as well as reanalyzed data of CFSR project, and different interpolation methods, i.e. nearest neighborhood (NN) and inverse distance method (IDW) were employed and compared for preparation of inputs of SWAT model using a developed computational module in Module Builder framework of ArcMap. Then parameters sensitivity analysis, estimation and model validation were performed based on a period of 36-years monthly streamflow record. Results showed using CFSR data leads to Nash-Sutcliffe (NS) value of 0.58 as compared to climatological stations’ data which leads to NS value of 0.38. Additionally, IDW method showed a better performance significantly than the NN method, so that their NS index values were 0.79 and 0.56, respectively.

The acquisition of continuous and precise river flow velocity is a high-priority issue for water resources management. In Iran, the river flow velocity is estimated using mechanical propeller flow meter. In this research, for the first time in Iran, the river flow velocity at the Chamtagh hydrometric station of the Zayanderud River was measured using Fluvial Acoustic Tomography System (FATS) technology. The reciprocal sound transmissions were performed between a pair of acoustic stations, located on both sides of the hydrometric station. Acoustic frequency was 30 kHz and the sound pulses were transmitted every 30 seconds. The measured stream flow discharge was 9.9 m3/s, while, the estimated flow rate by propeller flow meter was 10.3 m3/s. In this experiment, the maximum uncertainty of FATS was less than 15%. Moreover, the error analysis of the FATS was investigated for different rivers and the optimal setting of FATS was introduced.

The need for optimized exploitation of water resources has been increased due to the limited water resources and the different section´s competition. For this purpose, data of six selected synoptic stations including Mashhad, Shiraz, Tabriz, Kermanshah, Khorramabad and Urmia stations were used. Input variables consist of mean temperature (T), relative humidity (RH), sunshine hour (S) and wind speed at 2 m elevation (U2). The M test method was used to determine the length of test period. Since, both Gama index and Standard Error are closed to the axis at the end of figures, the last five-year results were used to test the models. According to the gamma test results, the best input parameters for Mashhad, Shiraz, Tabriz, Kermanshah, Khorramabad and Urmia are respectively (S, U2, RH), (T, U2, RH, S), (T, U2, RH, S), (T, U2, RH), (T, RH, S), (RH, S) under the combined conditions and in a same way, the lowest gamma are 0.005, -0.01, 0.001, -0.002, 0.008, 0.009. Local Linear Regression (LLR), Dynamic Local Linear Regression (DLLR), ANN (conjugate gradient) and ANN (BFGS) models were used to estimate the annual evapotranspiration. The R, MAE, RMSE, MBE, Jakouvidiez (t) and Sabagh (R2/t) criteria were used to evaluate the proposed models. The results showed that the best performance was obtained for the stations; Mashhad, Kermanshah, Tabriz and Shiraz using the best inputs, so that the correlation coefficients for neural network model conjugate gradient were 0.91, 0.98, 0.96 and 0.97, respectively. The general results showed that the non-parametric methods are able to estimate the annual ET, properly.

The need for good quality water resources, in line with population growth and the diversity and multiplicity of pollutants and contaminants dictate the quantitative and qualitative management of water resources. In this regard, water resources monitoring and the real time availability of spatial and temporal information can play an important role in water resources management. Real time remote sensing technology using satellite images with proper accuracy is able to determine some of the qualitative parameters of water affecting the temperature or spectrum of light from the surface of the water. The aim of this study was to investigate the accuracy of water quality monitoring of Anzali wetland using remote sensing. For this purpose, after field study of Anzali wetland and rivers leading to it, suitable sites for sampling were selected. After selection of suitable points for sampling, in order to increase the accuracy of the regression models, satellite images were used in different seasons of the year (November, 2002, February, 2002, May 2003 and August 2003). During the satellite (landsat 7 and 8) passing above the area, samplings were done and the quality parameters including nitrate, ammonium, soluble phosphorus, total dissolved solids, suspended solids, conductivity and acidity were measured. After extracting satellite images and their reflections, the effective bands on water quality values were determine and regression models of the images were obtained. The results showed that the use of remote sensing technique in Anzali wetland could be able to estimate the acidity, total suspended solids and temperature well (with root mean percentage of normalized error less than 10%). Other qualitative parameters including nitrate, salinity, total soluble solids and ammonium (with root mean of normalized error less than 30%) and orthophosphate (with root mean percentage of normalized error greater than 30%) were estimated fairly and poorly, respectively. Therefore, the remote sensing technique is able to estimate most of the qualitative parameters with acceptable accuracy. Surely increasing the number of sampling points and frequencies, the accuracy of regression models and consequently the accuracy of estimation of qualitative parameters will increase.

Kochia is one of the most salt and drought tolerance plants that can be used in forage production for livestock in the absence of suitable water and soil resources. This study was conducted to evaluate the yield and yield components of Kochia under salinity and water stress condition. The main plots included salinity levels of Karoon water (2.5), 10, 15 and 20 dS/m, and subplots included three irrigation levels; 100, 75 and 50% of the crop water requirement. The studied traits were weight of the aerial part of the plant, fresh and dry weight of leaf and stem, fresh and dry weight of a bush and plant height. Results showed that the salinity stress had a significant effect on the proposed traits at 1% level. Also, different irrigation treatments had a significant effect on the studied traits. Individual effects of salinity and deficit irrigation stresses showed that the control treatments including salinity (Karoon water) and full irrigation (100% water requirement) produced 52 and 49 tons of fresh forage per hectare, respectively, which were superior among stress treatments in terms of all traits measured in the research. The interaction effect of salinity and drought stresses on fresh weight of one plant, fresh weight of leaf and leaf dry weight were significant at 5% level, on plant height were significant at 1% level, and on the other traits were not significant. Kochia plant under favorable conditions and under severe salinity and drought stresses could produce 57 and 34 tons per hectare fresh fodder respectively. Finally, the correlation among all traits were evaluated. The results showed that the all proposed traits including; total weight of the fresh plant, fresh and dry weight of one plant, dry and fresh weight of leaf and stem, plant height, stem diameter and the numbers of branches showed a positive and significant correlation with the salinity and drought stresses.