جستجوی مقالات مرتبط با کلیدواژه « ضریب پخشیدگی » در نشریات گروه « آب و خاک »

Agricultural sector is the greatest user of water in Iran, and increase of the consumption efficiency is necessary by considering the limited water resources in the recent years. Hasanlu irrigation and drainage networks as a part of a larger project of Naghadeh plan is one of the country's largest projects in the field of development of pressurized irrigation systems. Hasanlu network supplies water to the systems of sprinklers, surface gravity irrigation, and hydroflums based on the available pressure head at the relevant sites. In this research, geographic information systems were used as a framework for storing, management, processing, analyzing and visualization of spatial information of Hasanlo project phase 1 to evaluate water management of this plan. For this purpose, the coefficient of uniformity and distribution uniformity in sprinkler irrigation calculation toolbox developed and added to GIS as an extension, to simulate and evaluate the single or multi riser uniformity tests. Also, the risers discharge and application pressure were recorded at the site during the operation of the project. Results indicated that the pressure of risers varied from 0.5 to 3.9 bar and average Christiansen’s coefficient of uniformity (CU) was under 50% that indicated poor water management in the farm level. Also the satisfaction of stakeholders was in medium level.

 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.

 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.

 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.

Understanding the processes of mixing and transporting materials in rivers has been accounted as a main activity in the water resources management. Among the mixing processes, the transverse diffusion is considered as the second important process, after the longitudinal diffusion, affecting the longitudinal and transverse distribution of pollutants in river flows. Determination of the rate of material diffusion and their density are usually carried out based on solving mass conservation equations. The available analytical solutions were only provided for uniform flows in straight channels, so there are needs for numerical methods to solve the governing equations for non-uniform flow in complicated forms of channel geometries. The results from studies on rectangular straight channels show that the transverse diffusion coefficient (TDC) increases with increasing friction factor, while no specific relation between TDC and the ratio of width to depth is provided. Meanwhile, based on laboratory studies, an empirical relationship for estimation of transverse mixing coefficient is introduced for straight channels in uniform flow. An equation is also introduced to show the relationship among the longitudinal dispersion coefficient of pollutants, flow depth, river width, flow velocity, and shear velocity of river flows. Since increasing the amount of roughness of the channel boundaries, provides additional flow turbulence, which in turn results in reducing the perfect mixing length of the pollutant, some laboratory researches have been carried out using the spatial artificial roughness in flumes with single or combined cross sections to investigate the effects of roughness on the coefficient of transverse mixing of pollutants. However, all related tests were mainly carried out within laboratory channels with small widths where the tracer injection was made in the middle of the channels. In this research, we carried out tests in a wider channel, including artificial roughness on the bed to reduce the effects of channel walls where the tracer injection was made from the channel center. In this study, the laboratory tests were carried out in a channel with a length of 7.3, and width of 0.6 meters. The channel had been installed on a metal platform with adjustable slope, but the tests were carried out using a fixed slope. A set of square wooden blocks in three rows and two layouts with upstream ramp were used to make artificial channel bed roughness for increasing the transverse mixing of the pollutants. Salt solution at a concentration of approximately 27 grams per liter was used as the pollutant and an electrical conductivity instrument was used to measure the density of samples taken from two sections (i.e. 135 and 365 cm) downstream of the injection point as well as the density of the tracer concentration inside the tank. For each layout, three discharges of 20, 30, and 35 liter per second have been considered. Due to time and financial constraints, and consequently, limitation on evaluating the various conditions of the flow, number of rows, and different points in laboratory-scale, the FLUENT software was used to improve the results of the present research. The results of the laboratory tests showed that the local roughness has a considerable effect on the reduction of full mixing length. Also, the results of the dimensional analysis showed that the transverse diffusion coefficient is directly related to the ratio of width to depth as well as friction coefficient. As a whole, the results of this research show that the friction factor and the flow depth have a significant effect on the amount of TDC of the pollutant, so that by increasing the amount of friction coefficient, the TDC was increased, the perfect mixing length was reduced and dilution was done in a shorter distance. Moreover, increasing the flow velocity led to increase in the pollutant transport by flow, reduce the amount of TDC of the pollutant, and consequently, increase the perfect mixing length. Based on the results from laboratory experiments and dimensional analysis, a new relationship was introduced to estimate TDC with a mean relative error of 0.059. As mentioned previously, to extend the applications of the results to various situations, using data obtained from laboratory experiments, the abilities of FLUENT software for simulating the different conditions were investigated. It is found that the FLUENT software is able to simulate and predict the mixing processes in rivers with a reasonable accuracy.

The study of rivers’ water quality is extremely important. This issue is more important when the rivers are one of the main sources of water supply for drinking, agriculture and industry. Unfortunately, river pollution has become one of the most important problems in the environment. When a source of pollution is transfused into the river, due to molecular motion, turbulence, and non-uniform velocity in cross-section of flow, it quickly spreads and covers all around the cross section and moves along the river with the flow. The governing equation of pollutant transmission in river is Advection Dispersion Equation (ADE). Computer simulation of pollution transmission in rives needs to solve the ADE by analytical or numerical approaches. The ADE has analytical solution under simple boundary and initial conditions but when the flow geometry and hydraulic conditions becomes more complex such as practical engineering problems, the analytical solutions are not applicable. Therefore, to solve this equation several numerical methods have been proposed. In this paper by getting the pollution transmission in the Severn River and Narew River was simulated.
The longitudinal dispersion coefficient is proportional of properties of Fluid, hydraulic condition and the river geometry characteristics. For fluid properties the density and dynamic viscosity and for hydraulic condition, the velocity, flow depth, velocity and energy gradient slope and for river geometry the width of cross section and longitudinal slope can be mentioned. Several other parameters are influencive, but cannot be clearly measured such as sinuosity path and bed form of river. To derive the governed equation of pollution transmission in river, it is enough to consider an element of river and by using the continuity equation and Fick laws to balancing the inputs and outputs the pollution discharge. To calculate the dispersion coefficient several ways as empirical formulas and artificial intelligent techniques have been proposed. In this study LDC is calculated for the Severn River and Narew River and some selected empirical formulas have been assessed to calculate the LDC.
Dispersion Routing As mentioned previously, calculating the LDC is more important, so firstly, the longitudinal dispersion was calculated from the concentration profile by Dispersion Routing Method (DRM). Using the DRM included the four stage.1-considering of initial value for LDC .2-calculating the concentration profile at the downstream station by using the upstream concentration profile and LDC.3- Performing a comparison between the calculated profile and measured profile.4- if the calculating profile is not a suitable cover, the measured profile of the process will be repeated until the calculated profile shows a good covering on the measured profile.
Numerical The ADE includes two different parts advection and dispersion. The pure advection term is related to transmission modeling without any dispersing and the dispersion term is related to the dispersion without any transmission. To discrete the ADE the finite volume method was used. According to physical properties of these two terms and the recommendation of researchers a suitable scheme should be considered for numerical solution of ADE terms. Among the finite volume schemes, the quickest scheme was selected to discrete the advection term, because of this scheme has suitable ability to model the pure advection term. The quickest scheme is an explicit scheme and the stability condition should be considered. To discrete the dispersion term, the central implicit scheme was selected. This scheme is unconditionally stable.
The results of longitudinal dispersion coefficient for the Severn River and Narew River were calculated using the DRM method and empirical formulas. The results of LDC calculation showed that the minimum and maximum values for the Severn River was equal to the 12.5 and 41.5 respectively and for the Narew River were reported as 18.0 and 56.0 respectively. The value of the LDC derived using the DRM was used as one of the input parameters for developing the computer program. For validation of numerical model, a comparison was conducted with results of analytical solution. This comparison showed that the performance of numerical method is quite suitable. For assessing the performance of numerical model the pollution transmission in the both mentioned rivers was simulated. The calculated LDC and time steps and distance steps was considered as 4m and 2s. The results of simulation showed that the performance of developed computer model is suitable for practical purposes.
In this paper the Finite volume method such as numerical model for Discretization the ADE and also estimating the LDS the Dispersion routing method has been used. To primary evaluating of the model the compression between the model result and analytical solution of ADE has been done. To assess the accuracy of the model in engineering work the results of the model compared with two rivers data observations (Severn and Narew). Final result showed that the performance of model is suitable.

Nowadays, mathematical modeling is increasingly used in order to evaluate the spatial and temporal changes of the concentrations of water quality parameters in rivers and reservoirs. In this research, the FASTER model was used for water quality modeling. For simulation of the hydrodynamic conditions of flow, continuity and momentum equations (known as Saint- Venant equations), are numerically solved using the Crank-Nicholson central scheme with a staggered method and varying grid size. The Advection Dispersion Equation (ADE) has been solved using the finite volume technique. According to the available data, the parameters of nitrogen and dissolved oxygen (DO) for a reach of Karkheh River between Paye-Pole and Hamidiyeh stations were analyzed and simulated and Abdel khan hydrometric station was selected as a survey station. For solving the hydrodynamics of flow, it is necessary that Manning roughness coefficient (n) be calibrated in FASTER model. With adjusting of this factor, value of 0.028 was chosen. In this study 4 Dispersion Coefficients (DL), including Fischer et al, Seo and cheong, Kashefipour and Kashefipour and Falconer equations were used. Comparison of the measured nitrogen and dissolved oxygen concentrations and the corresponding model results showed that the Fischer dispersion model and Kashefipour- Falconer dispersion model performed relatively well for nitrogen and dissolved oxygen, respectively. Also according to the concentrations of water quality parameters that have been evaluated in this specified reach of Karkheh River, the concentration of dissolved oxygen is desirable for public purposes for different conditions of water temperature and river discharge. The concentration of nitrogen has low limitations for consumption.

A detailed description of the behavior of cohesive fine-grained sediments is a very complicated task. Simulation of cohesive sediment movement has been successfully treated in the past using the macroscopic properties of the water-sediment system. In this study, a 1-Dimensional equation of cohesive sediment has been proposed for deposition term and dispersion coefficient of mass transfer equation. This equation has been solved by Control Volume method and calibrated with laboratory data. The tests have been done in a flume with 0.3m diameter, the slope 0.00008, discharge between 3~5.7 liter per second and the concentration of 4~8 gram per liter. The model shows that the dispersion coefficient is a function of Reynolds number and rate of velocity to shear velocity.

Accurate information concerning soil hydraulic characteristics is needed for an understanding of the process of water flow and solute transport through soils. One of the soil hydraulic characteristics is its hydraulic diffusivity in unsaturated conditions. A simple method of determining soil hydraulic diffusivity is a simple procedure in which soil moisture measurement is not required and instead only by measuring the wetting front versus time, cumulative infiltration versus wetting front as well as infiltration rate versus inverse wetting front, soil hydraulic diffusivity function can be determined. In this method, the depth of soil column affects the accuracy of the results. Therefore, in this investigation one dimensional horizontal infiltration soil column was used to determine the minimum length (depth) of soil column for three soil textures (light, medium and heavy) employing the above mentioned simple method. Results indicated that for lighter soils, a deeper column of soil would be needed. So that a minimum column length (depth) for heavy and medium soils would be 8, and 15 cm respectively, and while for a light type of soil the column length must be more than 60 cm. Mean diffusivity coefficients for soils with varied initial moisture contents and for different soil textures (in different infiltration and evaporation states) have been presented. Mean hydraulic diffusivity coefficient decreased from light to heavy soil, the same way as did the hydraulic diffusivity coefficient.