JWSS - Journal of Water and Soil Science

The irrigation and drainage network of Zarrinehroud with an area of 65,000 hectares is the most important network of Lake Urmia basin, with the direct link to the lake. With the current crisis in the lake, an assessment of the existing network's performance is essential in the Urmia Lake Rescue Program. The purpose of this study was, therefore, to evaluate the transmission, distribution, and utilization efficiency and irrigation efficiency at the surface of the network. Three products were selected from the cultivar with the highest crop area (10% beet, 22% and 22%, and 38% wheat). The dominant method of irrigation was surface irrigation. At the network level, soil moisture in the field before and after irrigation, soil physical and hydraulic properties and water use volume for irrigation were measured. The results showed  that the average transmission efficiency in canals with the concrete coating of the network was about 79%, which was  in the range of 33% (in the  smaller channels) to 100% (in the  larger channels). The water distribution efficiency in the network was, on average, 76%, varying from 50% to 100%. Water use efficiency in the fields based on soil moisture balance analysis varied from 41% in the sandy loam soils to 66% for the clay texture. Based on the analysis of the data on the amount of harvest, production costs and product sales price, the water use efficiency (in kilograms of product per cubic meter of water used) varied from 0.4 for the  elderly hay to 5.1 for the  sugar beet. The amount of water used in this network (in Rials per cubic meter of water consumption) was between 2740 for alfalfa aged over 10 years and 6900 for wheat. It can be concluded that in the case of water constraints, wheat, sugar beet and alfalfa could be the most economic cultivar, respectively.

Due to the dry climate and limitation of fresh water resources, using fresh and salt water is a solution for crop production under salinity conditions. This study was conducted at Isfahan University of Technology as a randomized complete block design with three replications and five irrigation management treatments in 2014. The treatments included irrigation with saline water (with the salinity of 5 dS/m, based on the relative yield of 75%), irrigation with fresh water (municipal water), alternate irrigation (irrigation with saline water and the next irrigation with fresh water), conjunctive irrigation (half of irrigation with saline water and the other one with fresh water) and irrigation with fresh water to reach the raceme stage, and irrigation with saline water. The maximum wet yield, dry yield and grain yield were related to the fresh water treatment with 4.14, 2.45 and 0.588 kg/m² and the minimum values were obtained for water their water treated with 1.34, 0.765 and 0.0957 kg/m² respectively. The conjunctive treatment had the highest yield after fresh water treatment. The various statistical indices showed that this model could be used for sorghum in Isfahan. The determination coefficient for yield was 0.65.The priority of model for yield simulation was salt water at the last stage, alternate irrigation, saline water, conjunctive irrigation and fresh water treatments, respectively.

One of the major issues in the contemporary world is climate change. The behavior and characteristics of parameters affecting climate change can cause them to be seen and hidden. As one of the effective ways to detect overt and covert behaviors for periodic climatic data series, Spectral analysis can be used. It is the analysis of each of the wavelengths series, making this behavior clear. Accordingly, the present study was an attempt to use the method of spectral analysis, data cycles in the minimum temperature, maximum temperature and precipitation in Ramsar station (located in the western regions of Mazandaran province) an nd Babolsar (located in the central parts of this province) in a period from1961 to 2014. For this purpose, temperature and precipitation data were obtained from these stations; MATLAB software environment and the environment for the software were logged for each of the variable in the stations. The results revealed that the minimum temperature at both stations had significant cycles, with the return period being 2 to 5 years; Remote Link could be fit into the cycle parameters such as NAO, AO and ENSO. Analysis of the period gram showed cycles 8 and 5/13-year-old and 5-year-old period in Ramsar and Babolsar. During the rainy cycles, the difference between the two stations and the difference in the geographical position affected systems, and rain accounted for the difference in speed dual-zone climate indicator for Remote Link.

In this study, in order to analyze the trends of annual precipitation, the information from 21 synoptic meteorological stations located in the Urmia Lake basin in a 30-year time period (1986-2015) was used. For this purpose, the Sequential Mann-Kendall test was used. The date of sudden change (if exist) in the precipitation time series of each station was identified. Significance of the trend in each of the time series and its direction (decrease or increase) in each of the stations were tested at 0.05 level. The results showed that 10 out of the 21 stations had a significant decreasing trend. Three stations (Sarab, Bostanabad and Sardasht) had significant increasing trends. Precipitation trends of eight stations were insignificant. Also, the study of sudden breaking points in the annual rainfall time series of the selected stations revealed that about 57.143 percent of the stations (12 stations) showed a significant sudden change in their annual rainfall series. In other words, more than half of the selected stations exhibited a   sudden change in their time series. The date of the sudden change of precipitation in eight stations (namely, Bonab, Sarab, Urmia, Oshnavieh, Kahrizi, Miyandoab, Bokan and Saghez) belonged to the middle part of the time series (i.e. 1996-2005). The sudden change date  of t hree stations (namely, Sardasht, Nagade and Tekab) belonged to the first decade of time series (i.e. 1986-1995) and only the sudden change date of  one station (namely, Maragheh) belonged to the last decade of time series (i.e. 2006-2015).

Alginate biopolymer, due to possessing a high capacity and affinity for heavy metals, is a suitable material for the removal of metals from polluted waters; however, the weak structural consistency of alginate hydogels limits the practical application of this natural polymer in water purification practices. In this study, sepiolite clay mineral was used as a solidifier of alginate hydrogel to produce hybrid materials with different clay:alginate ratios (1:2, 1:4 and 1:8). Subsequently, the sorption of Pb by the prepared hybrid materials was studied in different Pb concentrations (25 to
2000 mg/L) and temperatures (15, 25, 35 and 45 °C). The results showed that the Langmuir and freundlich equations could significantly describe Pb sorption data on the sorbents. Based on the Langmuir model estimation, alginate showed and sepiolite showed the highest and lowest capacities for Pb sorption, respectively; also, the hybrids were intermediates in this respect. The capacity and affinity of all sorbents were enhanced with increasing the temperature from 15 to 45 °C. Standard enthalpy changes (ΔH°) were found to be positive, confirming that the process of Pb sorption on the sorbents was endothermic. Positive values were also obtained for the standard entropy changes (ΔS°), suggesting increased randomness at the solid-solution interface during the sorption of Pb ions on the sorbents. The values of the standard free energy change (ΔG°) were negative for all different temperatures, thereby indicating that sorption on the sorbents was spontaneous and favorable. Overall, it could be concluded that modification of alginate with sepiolite might cause the decreased sorption capacity of alginate; however, the hybrid materials are good candidates for the Pb removal from aqueous solutions because of their high sorption capacities.

The objectives of this study were to estimate the concentration of lead (Pb) and cadmium (Cd) in agricultural products and the health risks of them on the human healths around the Irankooh Mine in Isfahan Province. The soil samples (0-20 cm of surface layer) and crop samples (rice and wheat) were collected using the composite and random sampling method. The total concentrations of Pb and Cd in soil were found to be 71.18 and 1.57 mg kg^-1. The mean Pb concentrations in rice and wheat were 7.81 and 2.31 mg kg^-1, respectively. These values for Cd were 0.15 and 0.124 mg kg^-1, respectively. The mean daily intake of Pb through the consumption of cereals was more than the dietary reference intake (3.6 μg kg⁻¹ day⁻¹), but the daily intake of Cd was less than the dietary reference intake. The hazard index (HI) mean value for Pb and Cd for children and adults was 4.60 and 4.64, respectively. It showed that the consumption of the entire foodstuff could lead to potential health risks for consumers. There is also the cancer risk associated with exposure to lead.

Because of the undesirable effects of lead on soil properties and human health, evaluation of its remediation methods seems to be essential. In order to evaluate the effect of humic acid (HA) on the  decontamination of lead (Pb) spiked-soils in the presence of wormwood plant (Artemicia absantium), an experiment was carried out in a completely randomized  block design with three replications. Experiment factors including different concentrations of Pb (Pb(NO₃)₂ in the  solid form) (0, 250, 500 and 1000 mg kg^-1) and levels of HA (0, 100 and 200 mg kg^-1) were considered. At the end of the growing period of plants, some soil and plant properties were measured. According to the results, BR, MBC, root and shoot dry weights, RWC and Fe and Zn concentrations in the shoot were decreased by increasing the soil Pb concentration. So, the mean values of BR and MBC in Pb₁₀₀₀ treatment was 60 and 51.1 percent lower than those of Pb₀, respectively. Pb accumulation in the root and shoot was enhanced as a result of the increase in the soil Pb concentration. The maximum Pb concentration of shoot (37.10 mg kg^-1) and root (38.1 mg kg^-1) was seen in the Pb₁₀₀₀ treatment. Also, the results suggested that humic acid had a positive effect on the shoot of Fe, Zn and Pb concentrations. So, the concentration of these elements in HA₂₀₀ treatment showed an increase 1.25, 1.64 and 1.66 times more than that of HA₀, respectively. Leaf proline amount was increased significantly by elevating the soil Pb concentration; however, application of 200 mg kg^-1 humic acid decreased leaf proline by 54.5 percent, as compared to the control (HA₀). Therefore, humic acid effect on increasing the plant Pb uptake, improving soil biological properties, and increasing availability and dissolution of Pb showed its ability in promoting the phytoremediation efficiency. According to the obtained results of this study, woodwarm plant (Artemicia absantium) is a non-accumulator that could not be used for phytoremediation purposes.

Subsurface drip irrigation systems, compared to other irrigation systems (basin and furrow), enhance the delivery of water and nutrients directly into the root zone. The purposes of this study were to determine wetting front advancement in a subsurface drip irrigation and to compare the results with the HYDRUS 2D model simulation. In this study, the irrigation using T-Tape was carried out on a sandy-loam soil by two emitters at different irrigation times. The Wet moisture meter device was used to determine the soil water content. Evaluation of the simulated and measured soil water content was performed by using the adjusted determination coefficient (R²), relative error (RE), and the normalized root mean square error (NRMSE). Based on the results, the NRMSE of soil water content prediction for the emitters at the depths of 20 and 40 cm was calculated to be in the range of 10 to 19 and 10 to 13 percent, respectively. Also, RE for the emitters at depths of 20 and 40 cm was in the range of -16 to -5 and 8 to 11 percent, respectively. The average R² for the emitters at depths of 20 and 40 cm was calculated to be 0.87 and 0.98, respectively. Also, five scenarios (F1, F2, T1, T2 and S1) were evaluated to assess the amount of water stored in the soil profile and water mass balance. The results indicated that the model could be used to predict the soil water content subsurface drip irrigation.

The effect of the uplift force in the hydraulics structures is against stability. So, determining and controlling this force can be very important. One of the ways to achieve this purpose is to decrease this force by using the hole drains; in this way, we can build perpendicular pipes with different diameters, leading to the durability of the structure. Therefore, an experimental model of concrete dam was constructed in the hydraulic laboratory. The dam's model was divided into five sections by using 4-hole drains with a thickness equal to the dam's foundation. By running experiments with the maximum water level at the upstream, dam hole drains were opened in their position. Hydraulic potential was estimated by using the Piezometer built in the flume body. Finally, by opening some hole drains, the uplift force was calculated from the equipotential lines. Therefore, the best case (which had the minimum force) was determined, which was a/L=0.4, to create the most proper hole drain in the dam foundation. (a: distance of drain to heel and L: length of the dam's foundation). To place the hole drain in this position, by applying the zero potential in this position, the up lift force was increased

The effects of climate change can be released from the surface to the soil depth, thereby affecting soil thermal regime. Thermal energy in the soil plays a very important role in causing climate changes. In this study, for the assessment and detection of  the climate changes, soil depths temperature, the measured data related to the  daily air temperature at a height of 2 meters (screen) during the years (1951-2014), and the soil depths daily temperature (5-10-20-30-50 to 100 cm), for 3, 9 and 15 hours, were obtained during a period (1992-2014) in Shahrud station. The climate change detection was employed to compare the treatment mean. As well, for detection of trends related to the annual, seasonal and monthly time series and their relation to the soil depths temperature, parametric methods (regression analysis and Pearson) and nonparametric (Mann-Kendall, Spearman) were applied. The results showed that the soil temperature was increased in all months except January, February and March. Also, in the seasonal time series, the soil depths temperature was increased in all seasons except winter. In fact, based on the results, the soil temperature in spring, summer and autumn was increased. Detection trends of the annual soil depths temperature showed that, except for the Pearson correlation coefficient method, soil temperature was increased at all soil depths.

This research was carried out to assess the origin and clay minerals characteristics and their relationship with potassium forms in the calcareous soil of this region, with the humid climate conditions. Based on aerial photos and topographic maps, physiographic units were separated and soil sampling was done in each diagnostic horizon. The results showed that smectite was the main and dominant clay mineral in the study area. In well-drained pedons, the convincing process for smectite abundance seemed to be mainly the transformation of palygorskite and mica. According to the results, the exchangeable potassium in the surface horizon was higher than that of the subsurface horizons. The main reason for the higher level of exchangeable K in the soil surface, was more smectite and organic carbon. The results revealed that unlike exchangeable and non-exchangeable K, because of the suitable conditions like temperature and humidity in surface horizons, the relative mean of structural K in the surface soils was less than that in the subsurface. Also, since an increase in calcium carbonate resulted in a decrease in amount of clay and the amount of relative clay minerals (dilution effect), the amounts of exchangeable, non- exchangeable and structural K were decreased.

Channels and surface water are ways for the transfer of pollutants to the environment and human. When any pollutant is spilled into the channel, the pollutant concentrations are decreased after the travel. Reducing the distance is an engineering expedient. To reduce the distance, mixing in water should be increased. Thus, the main goal of the present study was to investigate the effect of the triangular vane on transverse mixing used for control bank erosion. Experiments were carried out in an 80cm width flume. The vane, which was triangular, was made of Plexi-glass with a 30% width of the flume length, 15cm height and 50cm far from the tracer injection. Salt solution was used as the soluble tracer. The experiment was carried out to investigate the effect of the triangular vane for two conditions: with and without vane. The transverse mixing (e_z) and complete mixing length were estimated for the two conditions of with and without vane. The results showed with installing the triangular vane, the transverse mixing was increased up to 2.5 and the length of mixing was decreased by 60%, as compared with the tests of no vane.

Evaluating the possible relationships between vegetation and environmental characteristics can assist managers to identify effective factors influencing plants establishment and to characterize various vegetation communities. This study was aimed to evaluate the effects of long term grazing exclusion ( more than 33 years) and the controlled grazing system (resting – rotation grazing system) on the vegetation distribution and some soil properties in the Hamzavi research station in Hanna area-Semirom, Isfahan. Six transects (three parallel transects and three transects perpendicular to the general slope of the area) were established in each area and 10 square plots with the size of 2m² were placed along each transect; then, the cover percentage, production and list of all plant species were recorded. In each area, eighteen plots were collected randomly and in each plot, five soil samples were collected from 0-30 cm of the soil and then the samples were mixed and one sample of the compound was selected as an evidence plot. Soil properties such as pH, EC, CaCO₃, organic carbon, absorbable phosphor, total nitrogen, K, Ca, Mg, soil saturated percentage, cation exchange capacity, soil clay, silt, sand and fine sand contents were measured in the soil laboratory. The independent t test was used to compare the vegetation characteristics in two areas. Cation exchange capacity, CaCO₃, gravel percentage, soil phosphor content and grazing management were identified as the most discriminative factors in separating vegetation communities based on Canonical correspondence analysis (CCA) and cluster analysis. Controlled grazing management significantly modified some soil characteristics and increased the production (352 versus 184.2 kg/ha) and vegetation cover percentage (25.46 versus 18.37), as compared to the exclusion area (α= 5%). The vegetation density was increased significantly in the exclusion rather than controlled grazing area (3.03 versus 2.02 plant/m²). This study, therefore, revealed that controlled grazing management was more effective on improving some soil quality and vegetation characteristics rather than p long term grazing exclusion in the semi-arid ecosystems. So, avoiding long term grazing exclusion in semi-arid rangelands is suggested.

One of the factors leading to the contamination of water resources is human activity, producing waste materials. In this paper, the effects of contamination on the water quality of Taleghan River, was simulated using of Qual2k model and the seasonal changes were evaluated. The qualified data collected during two months, August (as the dry season) and February (as the wet season), were used in the modelling. The results showed that the dissolved oxygen change was in the range of 4.5-6.52 mg/L in August. However, it changed between 4.8-5.3 mg/l in February and this reduction in the wet season was due to the run off deposition and the seepages of farmland near the river. Furthermore, BOD in the wet season and the dry season changed by 6-31 and 10-26 mg/l, respectively. These changes were due to the sewage dilution in flow during the wet season. Evaluation of the pH values in wet and dry seasons also showed that water of the river was more alkaline in the wet season, which is due to the effect of non-point resources or the fertilizer entrance after farm land bleaching by rain. Evaluation of Taleghan river EC variation also showed these changes were not significant during the wet and dry seasons. Water temperature was altered by 3-10⁰C and 19-25⁰C, respectively, in February and August.

Catchment prioritization in terms of natural disaster intensity as well as prevention and control practices plays a main role in the natural resources and watershed management. In this study, a total of 24 sub-catchments in the Zohreh-Jarrahi basin were prioritized according to their morphometric parameters and using the mixed model of TOPSIS-Multivariate regression. A total of 12 morphometric parameters including constant component of channel maintenance, drainage density, ruggedness number, infiltration index, stream power index, stream frequency, slope, drainage texture rate, relief rate, form factor, bifurcation ratio and topography wetness index, in addition to rainfall, were studied and scored. Parameters were weighted by using multivariate regression and the spatial distribution of the observed flood events. TOPSIS model was used for the prioritization process. The results obtained from the weighting analysis showed that the ruggedness number, slope and rainfall had the highest effect on flooding in the study area with the score of 0.068, 0.024, and 0.016, respectively. According to the prioritization results, sub-catchments of Seidoon, Emamzadeh Jafar, and Takht Deraz, which had the minimum distance to the positive optimum (0.0028, 0.0029, and 0.0029, respectively) and the maximum distance to the negative optimum (0.0097, 0.0098 and 0.0095, respectively), showed the highest flooding intensity with the score of 0.7745, 0.7690 and 0.7625, respectively. In order to validate the results, prioritization results were compared to the observed flood events. Validation results also indicated the efficiency of the mixed model in delineation of catchments prone to flooding. Three sub-catchments of Seidoon, Emamzadeh Jafar and Takht Deraz were observed to have the highest number of observed flood events, thereby showing the high effectiveness of the model and also, the role of the morphometric parameters in flooding.

Land use/cover maps are the basic inputs for most of the environmental simulation models; hence, the accuracy of the maps derived from the classification of the satellite images reduces the uncertainty in modeling. The aim of this study was to assess the accuracy of the maps produced by machine learning based on classification methods (Random Forest and Support Vector Machine) and to compare them with a common classification method (Maximum Likelihood). For this purpose, the image of the OLI sensor of Landsat 8 for the study area (Sattarkhan Dam’s basin in the Eastern Azerbaijan) was used after the initial corrections. Five land uses including urban, irrigated and rain-fed agriculture, range and water body were considered. For conducting the supervised classification, ground truth data were used in two sets of educational (70% of the total) and test (30%) data. Accuracy indexes were used and the McNemar test was employed to show the significant statistical difference between the performances of the methods. The results indicates that the overall accuracy of Support Vector Machine, Random Forest, and Maximum Likelihood methods was 96.6, 90.8, and 90.8 %, respectively; also the Kappa coefficient for these methods was 0.93, 0.81 and 0.83, respectively. The existence of a significant statistical difference at the 95% confidence between the performances of the Support Vector Machine algorithm and the other two algorithms was confirmed by the McNemar test.

Regional flood frequency studies are initialized by the delineation of the homogeneous catchments. This study was based on "Region of Influence" concept, aiming to find the similar catchments in the south of Caspian Sea. The methodology utilized the Particle Swarm Optimization Algorithm, PSO, to optimize the fuzzy system over a dataset of catchment properties. The main catchment variables in relation to flood were determined by the principle component analysis method and employed as the inputs in the fuzzy system. Catchments grouping was performed over these fuzzy input variables by the iterative process. The optimum similar groups were obtained by PSO, and the heterogeneous L-moment index was used as the termination criterion for the optimization process. A total of 61 hydrometric stations located in the study area were selected and their relevant catchments' physical, climatic and hydrologic properties in relation to flood were studied. Principle Component Analysis by Variomax Rotation Factor over the catchments datasets tended to four out of 16 physical variables, including area, mean elevation, Gravelious Factor and Form Factor, as the main parameters in terms of homogeneity with 84 percent of accumulative variance. These variables, as well as mean annual rainfall, were used as the input data to define the fuzzy system. PSO algorithm was then employed to optimize the developed fuzzy system. The developed algorithm tended to yield the best result in the 9th iteration with 26 and 22 for the minimum average and the optimum values of cost function, respectively. The topology of the resulting algorithm included inertia weight, local and acceleration rates, the number of generations and population size, with the values of 0.7298, 1.4962, 1.4962, 10 and 5, respectively. This study tended to a total of 61 regions of influence, proportional to the relevant 61 sites. According to the geographical location of the catchments in the region, it could be concluded that the geographical proximity doesn't necessarily involve homogeneity. The obtained results indicated the efficient potential of PSO-FES in the delineation of the homogenous catchments in the study area.

Flood discharge estimation with different return periods is one of important factors for water structures design and installation. On the other hand, a lot of rivers existing in Iran watersheds have no complete and accurate hydrometric data. In these cases, one of the suitable solutions to estimate peak discharges with different return periods is the regional flood analysis. In this research, 55 hydrometric stations were used. For this purpose, at first, peak discharges in different return periods were estimated using the EasyFit software. Then, the effective variables on the peak discharges were collected and the input variables of the models were selected by using gamma test with the help of the WinGamma software. Finally, data modeling was performed using the support vector machine, artificial neural networks and nonlinear multivariate regression techniques. Quantitative and qualitative assessment of the results using various indices including Nash-Sutcliffe Efficiency Coefficient (NSC) showed that SVM modeling method had the most accuracy in comparison to the other two modeling methods to predict the peak discharges in the Namak Lake Watershed.

In the vast majority parts of the Earth, a prospect now visible is the mostly synthetic thinking and fabrication by the human hand. Collision and impact of humans on the natural environment in the short and long-term courses for obvious geographical features have changed a variety of spaces. One of the consequences of human impact on the natural environment during the current period is the phenomenon of climate change. One of the climatic parameters that plays an important role in agriculture, energy, urban, tourism and road transport is the minimum temperature. In this study, an attempt was made using the minimum temperature data from 5 meteorological stations in the West Mazandaran province, as well as HADCM3 model data, to show how to change this parameter in the future periods based on simulation by the SDSM model. Accordingly, after selection of the suitable climate variables and model calibration, the accuracy of the created model in the base period was evaluated; after ensuring the sufficient accuracy of the model according to A2 and B2 scenario, data minimum temperature in 2100 was simulated. Based on the simulation results showed that the values of minimum temperature in the region over the coming years would increase. This parameter was such that the average seasonal periods 2016 to 2039, 2040 to 2069 and 2070 to 2099, as compared to the baseline period would increase, on average, by 1.8, 3.5 and 6 percent. The largest increases in the minimum temperature in the western and southern parts of the region could occur. It was also found that unlike other months of the year, the minimum temperature in January would be a decreasing trend.

Changes in Climate parameters have been accelerated in the coming age, which can affect agricultural activities directly and indirectly. Temperature and precipitation are the most complex climatic factors. Spectral analysis is a scientific and efficient technique used to recognize and detect the hidden behaviors of these variables. In this research, in order to study and analyze the temperature and precipitation return periods using spectral analysis, the statistics of climate parameters (precipitation, mean, maximum and minimum temperature) for a period of 27 years (1989-2015) were used for the sustainable land management. For this purpose, the climatic data of temperature and precipitation entered the MATLAB software environment and Periodogram of each of the climatic parameters was drawn in a separate way. The results of each Periodogram study showed that the absolute minimum of temperature had significant cycles with the return periods of 3.8 and 2.4 years; the absolute maximum of temperature had a significant cycle with a return period of 2.1 years and the mean temperature was significant with a return period of 2.7 years. Also, the review of the Periodogram related to precipitation showed a significant cycle with a return period of 3.4 years. The Results from studying cycles indicated the existence of short-term return periods for climate variables in the region. Given this issue and the need to protect agricultural products, especially garden products, it should be done by applying water and soil resources management methods, including creating terraces and increasing soil roughness; Also, cultivation of appropriate plant species for the suitable regional climatic conditions, Drought resistant and low water requirement, the most optimal conditions could be created for the cultivation of horticultural and agricultural products.