R. Ghobadian; H. Shekari
Abstract
Introduction: The concentration changes of suspended load along the river reach and the contributing factors are of importance for hydraulic and environmental engineers. The first step to calculate the concentration of suspended sediment load is determining the flow hydraulic characteristics along a ...
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Introduction: The concentration changes of suspended load along the river reach and the contributing factors are of importance for hydraulic and environmental engineers. The first step to calculate the concentration of suspended sediment load is determining the flow hydraulic characteristics along a river reach. Although most of flow in nature are unsteady, the quasi-steady flow condition was considered to be simple in this study and the water surface profile along the river reach with irregular cross sections was calculated by standard step-by-step method. In order to calculate suspended sediment load under non-equilibrium condition, the advection-diffusion equation with source term was numerically solved. In the present sediment model, ten discretization methods, five relations for calculating capacity of suspended sediment load, eight relations for diffusion coefficients and eight relations to calculate particle fall velocity were used and their effects on suspended sediment distribution along 18480 m of Gharasoo river were investigated.
Results and Discussion: The HEC-RAS model output was used to calibrate the present hydraulic model. The models were run with the conditions as same as Manning roughness coefficient and river geometry conditions. The results showed that the calculated water surface profile along the river reach by two models are completely overlapped each other. In other words, the present model has a very good accuracy to predict the water surface profile in the river reach. As most commercial 1-D models (same as HEC-RAS) only consider the equilibrium condition for sediment transport and the bed or total load sediment, comparing the results of present sediment model with them seems not to be reasonable. Therefore, to validate the present suspended sediment model and finding the best method of discretization, an especial shape concentration hydrograph was introduced to the present model as input hydrograph and the model was run when the source term has been deleted deliberately. The volume below the input concentration hydrograph and calculated hydrographs in different cross sections was compared to each other. Comparing the hydrographs showed that the maximum error in calculating the volume of concentration hydrograph with the input hydrograph was 0.029% implying that the model satisfies the conservation laws as well as reliable programing. Among ten discretization methods, the best method for discretization of the advection-diffusion equation was Van Leer's method with the least error compared to other methods. After validating the model, effect of five relations for calculating capacity of suspended sediment load was investigated. The results showed that using the Wife equation estimated the amount of suspended sediment higher than other equations. The Toffaletti equation also estimated suspended sediment load lower than other equation. Among eight particle fall velocity formulas, Stokes relationship estimated the fall velocity larger than other equations. Hence, the Stokes equation application decreases the possibility of suspending the sediment particles. However, employing Van Rijn and Zanke relationships resulted in a greater suspended sediment load distribution along the river reach. Among eight relationships for diffusion coefficients, Elder and the Kashifipour - Falconer equations exhibited the lowest and the highest amount of diffusion in the concentration hydrograph, respectively. Furthermore, the calculated suspended sediment concentration under non-equilibrium conditions was 11.7 % higher than that under equilibrium conditions along the river reach.
Conclusion: Most 1-D numerical models only simulate the bed and total loads sediment transport under equilibrium condition while sediments are transported under non-equilibrium conditions in nature. Sediment transport under non- equilibrium conditions may be greater or lower than the equilibrium condition known as the capacity of sediment transport. In this research, a numerical model was developed to simulate the suspended sediment transport in a river reach under non-equilibrium conditions. The amount of suspended sediment concentration was calculated for each sediment grain size. The results showed that the distribution of suspended load along the river reach is not significantly sensitive to the fall velocity relations while the type of sediment transport equation affected the suspended sediment transport concentration. The concentration of suspended sediments for non-equilibrium conditions was also 11.7% higher than the concentration of sediments in equilibrium condition.
shahab ahmadi doabi; Majid Afyuni; Mahin Karami
Abstract
Introduction: Atmospheric dust is an important source of heavy metals, particularly in urban environments. Heavy metals can easily attach to dust particles and be distributed in large areas. Therefore, assessing the extent of heavy metals pollution present in nuisance dust is important for establishing ...
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Introduction: Atmospheric dust is an important source of heavy metals, particularly in urban environments. Heavy metals can easily attach to dust particles and be distributed in large areas. Therefore, assessing the extent of heavy metals pollution present in nuisance dust is important for establishing pollution control strategies and evaluating the results of previous measurements. Heavy metals contamination in atmospheric dust of Kermanshah provine has not been previously investigated. The main objective of this initial study was to determine the concentrations of heavy metals in atmospheric dust samples that were collected from Kermanshah province and to assess their contamination level. The results can provide a baseline for use in future environmental impact assessments and to guide pollution mitigation targets.
Materials and Methods: Dust samples were collected from 49 sites across the province, during the summer 2013. Dust sampling sites were selected in different urban (35 site) and suburban (14 site) locations in Kermanshah, Songhor, Gilangharb, Ghasre-Shirin, Sahneh, Sarpolzahab, Kangavar, Paveh and Javanrood cities. Dust collectors were installed on the roof of buildings about 3–4 m above the ground level. Each collection tray consisted of a circular plastic surface (320 mm in diameter, 120 mm depth) that was fixed on holders with 33 cm height and covered with a 2 mm PVC mesh on top to form a rough area for trapping saltant particles. The dust samples were analyzed for their Zn, Cu, Ni, Cr, Mn and Fe concentrations using an Atomic Absorption Spectrophotometer. In the present study, geo-accumulation index (Igeo), enrichment factor (EF), pollution index (PI) and integrated pollution index (IPI) were calculated to assess the heavy metal contamination level in the atmospheric dust.
Results and Discussion: The results showed that except for Fe and Mn, all heavy metal concentrations of atmospheric dust in Kermanshah provine were higher than in the background soils of world, showing that these heavy metals are likely from anthropogenic sources. The order of mean Igeo values was Ni> Zn> Cu> Cr> Mn> Fe, similar to the order of their EFs and PIs, which can also be seen as the decreasing order of their overall contamination degrees in atmospheric dust of Kermanshah province. The mean Igeo for Ni points to moderately to strongly pollution. 59% of calculated Igeo for Ni falls into class 2 (moderately polluted) and 37% into class 3 (moderately to strongly polluted), while according to the Igeo values for Mn (98%) and Fe (100%), they were practically unpolluted (class 0). The maximum EFs of Zn, Cu and Ni were higher than 10, which show that Zn, Cu and Ni in atmospheric dusts mainly originate from anthropogenic sources. It seems that EFs can also be an effective tool to differentiate the natural origins from anthropogenic sources. The mean EF (11.2) and 94% of Ni EFs were in the range of 5–20 indicating that Ni was a main contaminant in studied samples. Mn had 41% EFs less than 2 and 59% EFs in the range of 2–5, with mean EF less than 2, indicating minimal enrichment. The analytical results of heavy metals Igeo are same as the analytical results of EFs. The PIs of Zn, Cu and Ni were in the ranges of 2.1 to 11.3, 1.7 to 18.3 and 3.3 to 13.6, with an average of 3.8, 3.3 and 6.9, respectively. These data indicate that Zn, Cu and Ni may cause serious pollution in atmospheric dust of Kermanshah. The IPIs of atmospheric dust samples vary from 1.9 to 6.2 with mean value of 2.9, indicating that all studied samples were polluted by heavy metals.
Conclusion: The concentrations of heavy metals that were investigated in this study were compared with the reported data of other cities and with the background values of elements in the world soils. The concentrations of Zn, Cu, Ni and Cr in urban dust samples, and Fe and Mn in suburban dust samples were higher than their respective values in the world soils. The results indicate that atmospheric dusts in Kermanshah provin have elevated metal concentrations in general. The calculated values of Igeo and EF of heavy metals revealed the order of Igeo and EF as Ni> Zn> Cu> Cr> Mn> Fe. The high Igeo and EF for Ni, Zn and Cu in atmospheric dusts indicated that there was a considerable Ni, Zn and Cu pollution (Especially nickel), which possibly originate from traffic and industrial activities. The Igeo and EF of Mn and Fe were low. The results of PI also supported Zn, Cu and Ni serious pollution in atmospheric dust. Similarly, IPI results confirmed atmospheric dust samples pollution by heavy metals. These findings indicated that more attention should be paid to heavy metal contamination of atmospheric dusts in Kermanshah, especially in case of Ni.
Bahman Farhadi Bansouleh; Alireza Karimi; Hoamyoun Hesadi
Abstract
Introduction: Evapotranspiration (ET) is one of the key parameters in water resource planning and design of irrigation systems. ET could have spatial variations in a plain due to the diversity of plant species and spatial variability of meteorological parameters. Common methods of ET measurement are ...
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Introduction: Evapotranspiration (ET) is one of the key parameters in water resource planning and design of irrigation systems. ET could have spatial variations in a plain due to the diversity of plant species and spatial variability of meteorological parameters. Common methods of ET measurement are mostly point based and generalization of their results to the regional level are costly, time consuming and difficult. During the last three decades, several algorithms have been developed to estimate regional ET based on remote sensing techniques. Verstraeten et al. (2008) classified remote sensing-based methods for ET estimation into four categories i) methods based on the surface energy balance, ii) Penman-Monteith equation, iii) water balance and iv) the relationship between surface temperature and vegetation indices. SEBS (Surface Energy Balance System), SEBAL, METRIC and SEBI are examples of the algorithms which is developed based on the surface energy balance approach. SEBS is developed by Su (2002) and has been evaluated by several researchers. However this algorithm has been examined in the several studies in the world,it has been used rarely in Iran. The aim of the current study was to assess the results of SEBS algorithm in Mahidasht, Kermanshah, Iran. The study area is located at the latitude of 34º 5' – 34º 32' N and longitude of 46º 31' - 47º 06' E.
Materials and Methods: A brief description of the SEBS algorithm (in Persian) as well as its procedure to calculate ET based on Landsat images were presented in this paper. All equations of the algorithm were coded in the ERDAS Imagine package software using model maker tools. Actual ET over the study area was estimated using SEBS algorithm during the growth period of grain maize in the year 2010. For this purpose, available LANDSAT TM satellite images during the growing season of maize in 2010 (25 June, 11 July, 27 July and 12 August) were downloaded free of charge from the http://glovis.usgs.gov website (last visited: 26 November 2015).
A Lysimetric study was carried out to obtain reliable amounts of ET to assess the accuracy of calculating actual ET by SEBS algorithm. Because of the absence of the weighing Lysimeters in the study area, Drainable Lysimeter was used. Since the maize was the major crop in the study area, 10 ha maize was planted on 15 May 2010 at the research farm of the Mahidasht agricultural research station. At the same time, maize was cultivated in the Drainable Lysimeter (1m*1.5m*1.5m) which was located almost in the middle of the research farm. Actual ET of maize was calculated with the Lysimeter for each irrigation interval (10 days) based on water balance equation.
The Results of the SEBS algorithm were evaluated on two levels (farm and regional). At the farm level, average of calculating ET at the pixels of research farm was compared with the average of measured ET at the Lysimeter. The absolute and relative differences between the calculated and measured values of ET was used to describe the accuracy of the algorithm. Due to the absence of regional ET measurement, maximum ET estimated by the SEBS algorithm in the plain was compared with the calculated potential crop reference evapotranspiration (ETO). ETO was calculated using the Penman - Monteith formula based on daily weather data obtained from Mahidasht weather station.
Results and Discussion: Results indicated that an average of ET in the study area increased from June to August which coincides with increasing air temperature and vegetation density in the irrigated fields of the study area. The highest and lowest values of actual ET over the study area were determined in the irrigated farms and mountainous area, respectively. The results of Lysimetric study indicated that daily actual ET of maize on 25 June, 11 July, 27 July and 12 August was 4.13, 7.74, 7.45 and 8.05 mm.day-1, respectively. The value of ET estimated by SEBS algorithm was less than actual measured ET by Lysimeter for the all mentioned dates. The maximum absolute difference between estimated ET by SEBS and measured ET with the Lysimeter was occurred on 27 July with the amount 0.34 mm.day-1. Considering the maximum relative difference of 4.56 % between calculated and measured ET, it could be concluded that estimated ET by SEBS algorithm can be acceptable.
Due to the absence of ground-based measurements of evapotranspiration at the regional level, the maximum amount of ET estimated by SEBS algorithm was compared with ETO. The highest and lowest ratio of maximum ET over ETO were calculated as 1.02 and 1.22 which are acceptable values for the crop coefficient (Kc) in the studied period. The maximum difference between estimated ET by SEBS algorithm with ETO was 1.53 mm.day-1 which is equal to 21.86% of ETO in the same date (12 August).
Conclusions: The results of the current study showed that the SEBS algorithm can estimate the actual ET of maize with the acceptable accuracy in the Mahidasht. In the absence of measured ET data at the regional level, it was difficult to have a reasonable judgment on the accuracy of the estimated values of ET by SEBS algorithm at this scale. It is recommended to do the same study on other remote sensing-based approaches of ET estimation.
shahab ahmadi doabi; Majid Afyuni; Mahin Karami; Safura Merati Fashi
Abstract
Introduction: Zinc (Zn) is an essential trace element for plants as well as for animals and humans. On the other hand, Zn is a heavy metal and its high concentration can cause some environmental problems. There are significant relationships between soils, plants and humans Zn status in a certain agro-ecosystem.Therefore, ...
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Introduction: Zinc (Zn) is an essential trace element for plants as well as for animals and humans. On the other hand, Zn is a heavy metal and its high concentration can cause some environmental problems. There are significant relationships between soils, plants and humans Zn status in a certain agro-ecosystem.Therefore, mass flux assessment of Zn in agro-ecosystem is important regarding to plant and human nutrition in one hand and environmental quality on the other hand. Therefore, assessing the Zn accumulation trend in agricultural soils is essential to prevent Zn deficiency as well as soil pollution by Zn.
Materials and Methods: This investigation was conducted in order to model Zn accumulation rate in agricultural soils of Kermanshah province using inputs and outputs fluxes mass balance. Mass Flux Assessment (MFA) model were applied for the modeling accumulation rate of Zn uses a random method of element balance with the combination of Latin Hyporcube method and Mont-Carlo simulation, in several agricultural ecosystems of some townships (Kermanshah, Songhor, Gilanegharb, Ghasreshrin, Shaneh, Sarpolezahab, Kangavar, Paveh and Javanrood). In this study, mass flux assessments were done at both provincial and township scales. Various routes of Zn considered in this study were livestock manure, mineral fertilizers, pesticides, atmosphere deposition, municipal waste compost (input) and uptake by plant (output). Agricultural information, including crop type, crop area and yield, kind and number of livestock, application rates of mineral fertilizers, compost, pesticides and atmospheric deposition rates and also a metal concentration in the plants, livestock manure, mineral fertilizers, compost and dust was used to quantify Zn fluxes and Zn accumulation rate. Given that the other sources of Zn input such as sewage sludge and output such as leaching are not important fluxes in the study area, the calculations performed here presented a good estimation of the average net effects of the dominating Zn inputs and outputs of the Zn status in agricultural soils of the study region.
Results and Discussion: The results showed that the maximum and minimum of the Zn accumulation rate were seen in agricultural soils of Paveh (1172 g ha-1yr-1 in average) and Kermanshah (-26 g ha-1yr-1 in average)respectively. The average net flux of Zn accumulation rate for Kermanshah province was also 1538 g ha-1yr-1. The negative Zn accumulation rate of Kermanshah soils implies depletion of this element that is due to higher uptake of Zn by plants, especially crops with high performance such as maize and sugar beet. The calculated accumulation rates were less than the critical accumulation rate (calculated for the next 200 years in the study area). The results showed the high range (difference between the simulated maximum and minimum) of the Zn accumulation rate in Paveh was 1307 g ha-1yr-1, and the lowest in Songhor was 175 g ha-1yr-1. The major part of the uncertainty in the Zn balance resulted from manure source. According to the calculated SRCAP (Standardized Regression Coefficients Aggregated in Percent) values, Zn input with manure and then Zn output with crop removal were the main sources of Zn net flux uncertainty at township and province 9 levels. The uncertainty associated with livestock manure fluxes explained 67-94% of the total uncertainty. This large contribution was mainly due to large uncertainty in the numbers of dominant livestock, in particular cattle and poultry, and in the Zn:P concentration ratios of their manures. The influence of crop removal on Zn net fluxes uncertainty ranged from 3-29% among the townships. Differences in contributions of individual crops to the total cultivated area and in the Zn concentration of dominant crops as well as uncertain crops yield data were the main reasons for this large variation among townships.
Conclusion:The most important routes of Zn entry into the agricultural soils were livestock manures (69-93%) and atmosphere deposition (9-28%) in township level, while in provincial scale, they were compost (61%), livestock manures (33%), and atmosphere deposition (5%) respectively. The uncertainty analysis results indicated that livestock manure was the most effective rout on Zn accumulations rate uncertainty (79% in province scale and 67-94% in township scale). The results also indicated that current agricultural management generally leads to accumulation of Zn in soils of the study area (with exception for Kermanshah township soils). This can cause some difficulties such as soil contamination or soil fertility loss by nutritional elements imbalance in future.
M. Esmaeili; Bahman Farhadi Bansouleh; M. Ghobadi
Abstract
Introduction: Expansion of the area of oilseed crops such as soybean is one of the policies of Iranian agricultural policy makers as Iran is one of the major oilseed importers in the world. However, the area of this crop in Kermanshah province is negligible, but it could be cultivated in most parts ...
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Introduction: Expansion of the area of oilseed crops such as soybean is one of the policies of Iranian agricultural policy makers as Iran is one of the major oilseed importers in the world. However, the area of this crop in Kermanshah province is negligible, but it could be cultivated in most parts of this province. The quantity and quality of the produced grain could be affected by environmental factors such as weather parameters and water availability. The aim of the current study was to investigate the effects of levels of deficit irrigation on the quantity and quality of soybean crop yield in Kermanshah, Iran.
Materials and Methods: For this purpose, a field study was conducted as randomized complete block design with four replications and four irrigation treatments at the research farm of Razi University, Kermanshah in 2012. The size of each plot was 4 * 4 m. Irrigation treatments consisted of four irrigation levels: 20% over irrigation (T4), full irrigation (T3 as control), 20% less irrigation (T2) and 40% less irrigation (T1). The reason to choose T4 treatment was the lack of confidence in estimated crop evapotranspiration as there was no local calibration of crop coefficient (Kc) for this crop. The required water for T3 treatment was calculated based on daily weather data using FAO-Penman-Montith equation. Daily weather data was recorded in a weather station which was located in the research farm and is available in the www.fieldclimate.com. As there was no rainfall during the crop season, all of the required water was supplied through irrigation. The required water for treatments of T1, T2 and T4 was considered as 60%, 80% and 120% of T3 treatment. The required water was applied using a hose connected to a volumetric flow meter with a liter precision. Total amount of applied water during the crop season was 4399, 5865, 7331 and 8797 m3.ha-1 in the treatments. Fertilizers were applied based on the recommendations of soil fertility experts. Weeds were controlled manually. Finally, the area of two square meters in the middle of each plot was harvested in order to determine crop yield in terms of grain, biomass, stem, pod, seed protein content and fat percentage and also water productivity index. Dry weights of the samples were measured after drying samples in the oven for48hours at 70° C. The percentage of fat and protein in the grains are also measured in the laboratory. Water productivity index was calculated for each treatment by dividing crop yield (in terms of grain, biomass, protein and fat) over seasonal water use. Statistical analysis of the results is also done using MSTATC software.
Results and Discussion: The highest and lowest crop yields were measured respectively in the treatments T4 and T1.The mean value of grain yield was 1084, 1367, 1716 and 1940 kg.ha-1,respectively in the treatments T1, T2, T3 and T4. These results showed a 36% decrease in the grain yield by decreasing 40% in the amount of supplied water. However, biological yield was decreasedby the level of irrigation, but the rate of reduction was lower than that of grain yield. By reducing irrigation application, thepercentage of grain protein content increased while the percentage of fat in the grain decreased. Considering simultaneous reduction in grain yield and fat content in the grain, severe reductions in fat yield (oil content) were observed under water stress conditions. Crop yield in terms of fat was reduced by 26.2 and 50.1 %, respectively in treatments T2 and T1 in comparison with T3 (control treatment). The maximum and minimum percentages of protein in the treatments were 31% and 27%, respectively in the treatments T1 and T4. Maximum water productivity in terms of grain, biomass and protein was achieved in T1 treatment respectively with the amounts of 0.24, 0.81 and 0.077 kg.m-3. Maximum and minimum fat percentage was 0.052 and 0.040 kg.m-3, respectively in the T4 and T1 treatments. In addition,the results indicated that water productivity index in terms of grain, biomass and protein increased while they decreased in terms of fat yield.The results of statistical analysis indicated that water productivity index in all terms except protein had significant differences (at 5%) with T3 treatment.
Conclusion: Crop yield and water productivity (except in terms of fat) was increased by increasing applied water. Considering all indices of treatment T2 (20% deficit irrigation), itwas suggested as the best treatment.
A. Aazami; K. Zarafshani; hossein dehghani; A. Gorji
Abstract
The purpose of this integrative (quantitative-qualitative) descriptive survey study was to determine factors influencing farmers’ attitude toward sprinkler irrigation systems. A researcher made questionnaire was used to collect data. A sample of 274 farmers who were equipped with sprinkler irrigation ...
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The purpose of this integrative (quantitative-qualitative) descriptive survey study was to determine factors influencing farmers’ attitude toward sprinkler irrigation systems. A researcher made questionnaire was used to collect data. A sample of 274 farmers who were equipped with sprinkler irrigation systems during the past three years participated in the study. The face validity of the questionnaire was tested using experts in Department of Irrigation Improvement in Water and Soil Division in Ministry of Agricultural Jihad as well as experts in Agricultural College. Corrections were made in the research instrument as needed. The reliability was tested using a pilot study with 50 farmers outside the population. An Alpha Coefficient of 0.75 proved to be reliable. Results revealed that 80% of farmers held positive attitude toward their irrigation systems. Moreover, farmers’ level of education, experience with the systems, cost if installation, training, changes in income, and land holdings explained 64% of variance in farmers’ attitude toward irrigation systems. The qualitative results revealed some problems and issues perceived by farmers. Long process in filling application, lack of expertise among engineering firms, ineffective training classes, low quality spare parts, lack of water resources, and inefficiency in allocating resources were challenges by most farmers. Since attitude is predicts behavior, the result of this study can assist sprinkler irrigation policy makers to develop irrigation development in the region.
