مجله پژوهش آب ایران
پیاپی 26 (پاییز 1396)

Intake of river is used for different purposes such as irrigation, urban water supply, industry, electricity, etc. Side intakes are used directing water from river to the flat lands. The main purpose of an intake is to ensure a constant water supply that can be adjusted to local conditions. Designers have to consider the intake level below the minimum water level of the river. A protected side intake provides a stable place in the bank of a river or lake, from where water can flow into a channel or enter the suction pipe of a pump. It is built to withstand damage by floods and to minimize problems caused by sediment. One of the issues that designers of water structures are faced is the design of sediment control facilities in the inlet of drainage and irrigation networks. In this research, conjugate usage of spur dike and curved submerged vanes was considered and the effects of spur dike length, its location and angle on the amount of discharge and the maximum depth of scour hole's in the intake inlet were investigated. In this experiment, three different deviation discharges have been studied.
Experiments were performed in a flume with 14m length and 150cm width. The side intake had 75-degree angle to the main flume, with 60cm width. In all experiments, three rows of vanes were installed in front of the inlet. Dimensions, numbers and arrangement of the vanes were designed based on the recommended values by Odgaard and Wang (1997) Material of the vanes was metallic and their shape was trapezoidal
The Spur dike was placed on the right side of the flume wall. A number of piles, with a diameter of 7 mm, were used to create a permeable spur dike. The effect of three deviation discharge 15%, 20%, and 26% were studied. And in each three discharge effects of two abutment locations, three abutment lengths and two abutment angles were observed. Time of the experiments was equal to the duration of the time in which the first stack passed from the front of the intake. Finally, the bed topography at the inlet of the intake was calculated and analyzed by surfer software. In each experiment, information of water depth in the main flume, water depth in intake channel and the maximum depth of scour hole in the inlet of intake were plotted and analyzed. Dimensional analysis was done with the basic independent variables that characterized the system and arranges them into a parsimonious functional relationship. Then the coefficients determined by statistical analysis of the experimental data. In this analysis showed the relationship between calculated and observed depth scouring with the determination coefficient of, R2 =0.758 and the mean error of, MER = 27.4%. Also the relation between calculated and observed volume scouring with the determination coefficient of, R2 =0.938 and mean error of, MER = 4.1%.
The results of experiments showed that the position, the length and the angle of spur dike had a significant impact on the diverted discharge and the maximum scour depth. After running 48 tests and considering the control experiments, with and without installing vanes, the results showed that inserting spur dike on upstream of the inlet and in the position where the width was 1.2 of the intake width, provided better results in reducing scour hole's depth. Also, it caused an increase in the amount of discharge, in comparison to the position with doubled width of the intake, on the upstream. Moreover, it was observed that spur dike with a length of 27 cm (18% blockage) had the best result in all three flow deviation. The results showed that spur dike with the angle of 75 degrees to the flow direction, was more effective than vertical spur dike. Hence, the best condition occurred when spur dike with a length of 27 cm and the angle of 75 was placed on the upstream and in the section with the width of 1.2 of intake inlet. In this condition, three diversion flows of 15%, 20% and 26% led to, 34.6%, 30% and 58.8% increasing in the percentage of intake discharge, respectively and also it respectively caused 1.9%, 26.1% and 29.5% reduction in the maximum of scour hole's depth compared to the case of a vertical spur dike.

Petroleum hydrocarbons are considered as the most major aquatic and terrestrial ecosystem pollutants in the world. The US Environmental Protection Agency (EPA) has announced that it is harmful to the environment. It is toxic and cause cancer, too. Polycyclic aromatic hydrocarbons enter the soil and the groundwater through oil tanks leak, so cause environmental pollution. Polycyclic aromatic hydrocarbons (PAHs) are organic compounds that are mostly colorless, white, or pale yellow solids. They are a ubiquitous group of several hundred chemically related compounds, environmentally persistent with various structures and varied toxicity. They have toxic effects on organisms through various actions. Generally, PAHs enter the environment through various routes and are usually found as a mixture containing two or more of these compounds, e.g. soot. Some PAHs are manufactured in the industry. The mechanism of toxicity is considered to be interference with the function of cellular membranes, as well as enzyme systems which are associated with the membrane. It has been proved that PAHs can cause carcinogenic and mutagenic effects and they are also potent immune-suppressants. Effects have been documented on immune system development, humoral immunity and host resistance. PAHs can be formed both during biological processes and as products of incomplete combustion from either natural combustion sources (forest and brush fires) or by man-made combustion sources. Thus, PAHs are commonly detected in air, soil, and water. Therefore, PAHs are considered ubiquitous in the environment. The ubiquitous nature of PAHs in the environment has been well recognized in researches. The term “PAH” refers to compounds consisting of only carbon and hydrogen atoms. Chemically the PAHs are comprised of two or more benzene rings which are bonded in linear, cluster, or angular arrangements. Such molecular arrangements are considered toxic. Although there are many types of PAHs, most regulations, analyses, and data reporting focus on only a limited number of PAHs, typically between 14 and 20 individual PAH compounds. Petroleum contaminated is currently treated using three processes: physical, chemical, and biological. A range of cleaning techniques have been successfully developed to limit the environmental impacts caused by oil pollution, but timely and effective remediation is necessary to mitigate the detrimental effect of petroleum hydrocarbons on the environment. The present study aims to evaluate the efficiency of PAHs adsorption prediction of the groundwater contamination. Adsorption of these pollutants using the various natural adsorbents is among the crucial objectives of this study, as well. This investigation has been done in these steps: at first, the ecological characteristics of Tehran Oil Refinery have been identified and the water quality of its wastewater treatment plant was evaluated, briefly. In the second step, to estimate PAHs adsorption in soil and optimize the adsorption process using activated carbon, bentonite, talk powder, rice bran, and saw dust, we prepared a rectangular pilot plant with an interlaced plate as drainage at the end of it, and after packing it with each of the adsorbents in specific weight and height, oily wastewater containing (PAHs) influence on it. The column pressure head and its conditions have been stable during experiments. The adsorption of PAHs on these adsorbents was estimated by measuring the concentration of PAHs in effluents of the drainage, every 30 minute intervals up to 4 hour, and the bed of adsorbents at the end of experiments.
Since water has seriously been polluted by PAHs nowadays, PAHs adsorption by the Bentonite, Talcum powder and Clay is considered in this research. Then, PAHs distribution coefficient and the maximum adsorption have been determined according to the results, by Freundlich adsorption isotherms, and Langmuir isotherm. This study also compares the suitability of two predictive models, Freundlich isotherm and Langmuir isotherm, in analyzing the adsorption of PAHs on soil and the five types of adsorbents which were mentioned above. The results indicated, the adsorption data were well fitted by the Freundlich model. Also, Results show that the Bentonite has a high potential for PAHs adsorption. Distribution coefficient (kd) and the maximum adsorption are 0.008 lit/g and 0.101 mg/g. Since distribution coefficient for the absorbents including clay and Talk powder 0.0028 lit/g and 0.0023 lit/g, respectively. Furthermore, the maximum adsorption coefficient for the absorbents including clay and Talk powder is 0.042 mg/g and 0.003 mg/g in this research.

Triangular channel is widely used in irrigation and drainage systems. Also, the triangular channels with alongside weirs are used to control and measure the flow in irrigation and drainage networks and floodwater spreading projects. In this study, the pattern of the spatially-varied flow with decreasing discharge was investigated and compared in subcritical and supercritical flow regimes for triangular channels alongside weirs. Flow pattern in triangular channels alongside weirs is numerically simulated using the FLOW-3D software for both flow regimes. Also, variations of the free surface flow over alongside weirs are modeled by the volume of fluid (VOF) scheme. Furthermore, the turbulence of the flow field in triangular channels alongside weirs is numerically simulated using the RNG k- turbulence model. In the numerical study by these models, the specified amounts of discharge and flow depth are used for the "inlet" boundary condition of the triangular channel. Also, the specified amounts of the flow depth and the pressure are used in the main channel outlet boundary condition and all of the solid walls are defined as the "wall" boundary conditions. Then, the top layer of the air phase is considered as the "symmetry" boundary condition. The whole computational domain is gridded by a non-uniform mesh block consisted of rectangular elements. The distance from the first cell-wall was chosen so that the calculations below the viscous layer are eliminated. For this purpose, the first cell is located where the dimensionless parameter y is greater than 30. The results obtained from the numerical simulation in this study were verified by comparing them to the experimental measurements provided by Uyumaz (1992). A good agreement was obtained between the results of the numerical simulation and the experimental measurements for both flow regimes. The RMSE of the simulated water surface profile for the subcritical and supercritical flow regime was calculated 11.46% and 7.90%, respectively. Also, for free surface flow, the average percent relative error for both flow conditions were computed 10.8% and 6.87%, respectively. The specific energy was measured in the beginning of the side weir which was equal to 0.1661m and 0.2116m in subcritical and supercritical flow condition, respectively. The numerical model predicted the specific energy equal to 0.1565m and 0.2283m for both flow regimes. The specific energy relative error percent was 5.78% and 7.89% which showed suitable accuracy of the numerical model in predicting the specific energy. Generally, the flow depth increases from the upstream end towards the downstream end of the weir in subcritical conditions and decreases from the upstream end towards the downstream end of the side weir in supercritical conditions. A drop in the free surface in the first third of the side weir span and a surface jump in the final third of its length occurs. After this drop, the flow depth increases towards the downstream end of the side weir in subcritical flow regime, while in the supercritical flow condition the water depth gradually decreases towards the downstream end of the weir. The surface jump with a stagnation point occurs at the downstream end of the side weir for both flow regimes. Along the mentioned surface jump the amount of the kinetic energy increases and the potential energy decreases. Also, the water elevation is the highest at the stagnation point location. According to the simulation results, the maximum longitudinal velocity for subcritical regime occurred at the first third of the side weir length and for supercritical flow, almost in the middle of the side weir span. In both subcritical and supercritical flow regimes, the maximum transverse velocity occurred at the last third of the side weir length. According to the numerical simulation, the transverse velocity before the side weir was predicted negligible. In the vicinity of the side weir crest, the transverse velocity increased by flowing toward the span of the side weir. As the flow passed from the plane of the side weir, the amount of the transverse velocity decreased. The angle of the spilling jet was close to 90° at the upstream and downstream of the side weir in both flow regimes. The minimum angle of the spilling jet for subcritical and supercritical flow regimes occurred at the last third and the middle of the side weir length, respectively.

The water sources surrounding the industrial areas are easily contaminated by industries wastewater in Iran as around the world. Almost all wastewaters in industrial areas are discharged untreated directly into rivers, lakes and neighbor lands. Industrial wastes contain very high levels of both organic and inorganic compounds. Because of the complexity, presence of different kinds of toxic heavy metals and difficulties of refining process for industrial wastewaters, they have more challenges compared with urban wastewater. Depending to the type of industrialization, industrial wastewaters contain various heavy metals and organic chemicals that potentially can affect the human and ecosystem health by direct and indirect pathways. Recently, the Vetiver grass has been successfully introduced as an environmental protection, particularly in the field of wastewater treatment, due to its morphological and physiological properties and also its high tolerance to the adverse edaphic conditions. Its effectiveness, simplicity and cost-effective application made the Vetiver grass technology as a good alternative treatment for phytoremediation and rehabilitation of the domestic, municipal and industrial wastewater. This system of remediation has not deeply studied for industrial wastewaters in Iran. Therefore, the main objective of this study was to use the vetiver grass as a simple and an inexpensive method of phytoremediation to absorb and remove the heavy metals, comprising the As, Hg and Cr, from industrials wastewater.
The wastewater for this study was collected from wastewater outlet of Borazjan Industrial park. All pots were filled with the clay loam soils of Dalki alluvial plains and also 5 % (W/W) of manure was incorporated in each pot. The vetiver grass was grown outdoors and irrigated with usual irrigation water for 30 days. After that, irrigation water treatments have been done to a completely randomized design with 8 treatments in 4 replications for three times per weeks up to 75 days. The treatments were: 100 % usual irrigation water (A); 100 % wastewater (B); 50% usual irrigation water% wastewater (C); 70% usual irrigation water% wastewater (D); 30% usual irrigation water% wastewater (E); interval irrigation with usual irrigation water and wastewater (F); two times irrigation with wastewater and one time with usual water (G); and two times irrigation with usual water and one time with wastewater (H). Later on, concentration of Arsenic (As), Mercury (Hg) and Chromium (Cr) were measured in soils and also determined in the roots and shoots of vetiver grass by atomic absorption spectroscopy (AAS).
Results showed that the highest and lowest concentrations of heavy metals were observed in B and A treatments, respectively. The highest concentration of As, Hg and Cr in soils was 401.75, 0.019 and 0.6 (mg kg-1), respectively. The lowest observed concentration of As, Hg and Cr were 3.5, 0.001 and 0.017 (mg kg-1), respectively. Moreover, the highest and lowest concentration of As, Hg and Cr in roots of vetiver grasses were 85.68 and 0.62 (mg kg-1), 0.01 and 0.001 (mg kg-1) and 7.09 and 0.0005 (mg kg-1), respectively. The accumulation of Hg in roots and shoots has not any significant differences between treatments. The Hg contents in roots are significantly higher in plants irrigated with wastewater compared with usual irrigated water and it was not translocated from roots to shoots in all treatment, showing the high ability of Vetiver grass to accumulate Hg in roots. The highest and lowest concentration of As and Cr in shoots were 4.19 and 0 (mg kg-1) and 0.15 and 0.0006 (mg kg-1), respectively. Due to negligible translocation of heavy metals, especially Hg, to shoots of vetiver grass, they can be used as alternative forage crops for Animal husbandry in arid and semi-arid regions suffering from water scarcity. The ratio of As in shoots to the total absorbed As in plants was lower compared with literature but this ratios for Cr and Cr were consistent with literature. The order of heavy metal concentrations was as soils>roots>shoots. The information presented herein demonstrates that the vetiver grasses can be grown normally in areas irrigated by industrial wastewater. Results confirmed that vetiver grasses are a green and environmental-friendly system with low-cost maintenances. These grasses have several uses including animal fodder and material for organic farming. Furthermore, the biomass of vetiver grasses can be considered as a promising raw material for biofuel production but needs further investigations for its possibility.

Rapid drawdown is one of the key factors that can threat the stability of earth dams and neglecting it can lead to serious damages. This factor causes the earth dam break by inducing slip potential in upstream slope. Rapid drawdown occurs when the water level in reservoir of an earth dam reduces in a short period of time with a high rate, whilst the water level in the core cannot follow the water level of the reservoir. This phenomenon could happen for any reason, such as an earthquake, sudden formation of large cracks, arching phenomenon, flood, withdrawal of large amount of water for various purposes and etc. Due to discharge and decrease of water level in the reservoir, the hydrostatic pressure on the external surface of the upstream slope fades away while the balancing hydrostatic pressure inside the dam still remains. This remained hydrostatic pressure is one of the most important factors of slipping risk on the upstream slope. Nevertheless, breakage of a dam not only eliminates the funds spent for its construction, entirely, but also wastes the collected water in the dam without deployment and above all, destroys many facilities and people property and also brings casualties. On the other hand the majority of dams in our country are among earth types which are exposed to rapid drawdown condition for various reasons. Therefore, a comprehensive study in this field is needed and a definition for the drawdown condition has to be defined, in which the stability of the dam is not endangered. In this research, stability of earth dams exposed to rapid drawdown is studied by employing finite element method (using Geo studio software) which is one of the most accurate and recent methods for the analysis of earth dams. For this purpose, the Shahrchay dam’s cross section was selected as a case study and modeled by SLOPE/W and SEEP/W from the Geo-Studio software package. Then, numerical model was calibrated by the instrument data using back analysis technique. The analysis was conducted by considering circle failure planes for the condition of water drawdown from normal water level up to the bottom level of water intake. In the performed analysis, the effects of changes in hydraulic conductivity coefficient of the core, rate of water withdrawal in the reservoir and also impact of upstream drainage on the rate of water drawdown in the core, were evaluated. Also, water surface level in the core were calculated and plotted for various states. The results showed that safety factor in the upstream slopes decreased as the water withdrew from the reservoir. However, the safety factor increased after a certain time by complete withdrawal of water through the core. When the discharge rate is higher, the safety factors variation graph is more V-shaped like and critical safety factor occurs at earlier time. Also, when the full discharge of reservoir is necessary in case of emergency, it is recommended that the Shahrchay dam be discharged up to 32 cm per day to prevent the risk of the upstream slope failure. According to analyzing different drawdown conditions with different functions (linear, step and variable-speed nonlinear function), changing of the linear drawdown function to step drawdown function leads to 5 percent increase in the safety factor of the upstream slope, while altering the linear drawdown function to non-linear drawdown function increases safety factor of the upstream slopes by 7 percent, approximately. Studying changes in the core conductivity coefficient observed that when the core conductivity coefficient is equal to 5×〖10〗^(-10) m⁄s , the water level inside the core won’t drop, even at very low discharge rate. This can be very dangerous and cause instability in the upstream slope. Also, it was observed that while locating the upstream drainage system, the drain space is enclosed inside the dam, and considerable amount of pore water pressure is dissipated as the water level is the reservoir drops. By locating the drains 1, 2 and 3, the safety factor increases, respectively, up to 10, 13 and 7 percent. Through comparing horizontal and vertical drainage systems, it was found that the horizontal drainage system is 6 percent more efficient for draining water from the dam body and therefore reducing pore water pressure in drawdown condition.

River's flow prediction and its flood are the important subjects related to the flood projects, hydroelectric power production and water allocation for agricultural, industry and drinking uses. In the present study, wavelet analysis combined with Artificial Neural Network (ANN) was performed to simulate Gamasiyab River flow, located in Nahavand.The analysis was done in daily and monthly scale. For this purpose, the original time series, using wavelet theory, decomposed to multi time sub-signals. Then, these sub-signals were used as input data to the ANN to simulate flow and then the outputs compared with the ANN’s results. In this study, we used the precipitation, temperature, evaporation and flow data of Varayeneh station during the period of 1969 to 2011.Then, 75% of the data was used for training and 25% was considered for simulating data.
In this research, the amount of N and, L were determined 516 and 2 recpectivly. Also, 1 to 4 decomposition degrees were examined to be more precise. The number of neurons in the first layer depends on the degree of wavelet decomposition. The number of input neurons to the network is “m*(j )” in which “j” is the wavelet decomposition degree and “m” is the number of input parameters. For example, for j=1, according to the input parameters which in this study is 4 (precipitation, flow, temperature and evaporation), the number of input neurons is equal to 8. The output layer also has one neuron. The number of the middle layer neurons is variable and is obtained by trial and error. However, in this study, the number of neurons analyzed in the middle layer was varied from 3 to 20. In this case, modeling was done using different training functions and transfer functions for different neurons of the hidden layers. For daily period, input parameters were also decomposed with wavelet function with the levels of 5 to 9 and used as the input data of ANN. Also, the results concluded that 5 architectures had the best performance and it was also observed that the number of neurons of the middle layer was less than 10 in the superior structures. This means that the optimal solution can be reached with a lower number of neurons. Different training functions were examined, but useing all training functions is not suggested because it is time-consuming. Therefore, as proposed in this article, the three models of “Levenberg-Marquardt”, “BFGS Quasi-Newton” and “Bayesian Regularization” due to their better performance are recommended for future studies. After examining different stimulus functions, it is concluded that four types of “Tansig”, “Logsig”, “Satlin” and “Poslin” stimulus functions are suggested to be used for future studies.
Signal decomposition with wavelet increased correlation between observation and simulation data compared to Artificial Neural Network model, so the R2 was increased by 3 percent during the daily period and 24 percent during the monthly period. Two Artificial Neural Network and Wavelet – Artificial Neural Network (WANN) models in the daily period had almost similar performance but Wavelet – Artificial Neural Network model had a better performance in predicting minimum points. Moreover, after examining different structures, is the results determined that 5 architectures, functioned better in the various models and in the daily and monthly periods of the architecture. It means that using the data of evaporation and temperature makes the performance of the models better than the architecture in which these data are not used. Accordingly, the use of temperature and evaporation parameters is suggested in further studies in addition to flow and precipitation parameters.
The results showed that hybrid model of Wavelet-Artificial Neural Network (WANN) outperformed the Artificial Neural Network model. The reason of this preference of the WANN hybrid model is that the separation affects the time series inputs before interring to the network and primary signal decomposed to the various sub-signals. By doing this, we can use the analysis that contain short term and long term effects.
Besides, wavelet function of “Db4” has a better performance than other wavelet functions in each time period. It has the best performance in the daily period in the 5 level and in the monthly period in the second level. Also, the results showed hybrid model outperformed to estimate extent points than artificial neural network model.

Soil moisture deficit (SMD) is a key factor in evaluation of infiltration, estimation of saturated zones and surface and subsurface flow according to Hortonian and Dunne-Black mechanisms. The parameter SMD in each point of a watershed can be estimated by TOPMODEL. The hydrologic response of hillslopes depends on their plan shapes (convergent, parallel, and divergent) and profile curvatures (convex, straight, and concave). In this research, geometry of the complex hillslopes was concerned as new parameters in TOPMODEL to extend the equations governing the model. Also, the effects of complex hillslopes geometry on SMD and subsurface flow were studied. The TOPMODEL introduced by Beven and Kirkby (1979), provides a simple approach to parameterize the effects of topography on the distribution of subsurface moisture and runoff generation, and has been added into models of catchment hydrology and forest ecology. It has been widely applied to a variety of water resource theories, developments and applications [e.g., Beven and Wood, 1983; Beven et al., 1984; Wood et al., 1990].TOPMODEL has been used to soil moisture mapping, geochemical fluxes, subsurface flow and erosion. Examples of TOPMODEL applications in a range of locations may be found in the following works: Beven et al. (1984); Hornberger et al. (1985); Beven (1986); Wood et al. (1988); Robson et al. (1992); and Quinn and Beven (1993). Beven and Kirkby (1979) were among the first to work on TOPMODEL subject. They employed topographic index methods to predict variable contributing areas. The topographic index, , where a is the area drained per unit contour length and is the slope of the ground surface at the location, has been found by Beven and Kirkby to compare favorably with observed patterns of surface saturation. In this research the equations relevant to TOPMODEL were studied and developed considering geometry of hillslopes. Fortunately, TOPMODEL was capable to consider plan shape and curvature of complex hillslopes. We gave an account of saturation index sigma introduced by Troch et al. (2002) which is computable for the nine complex hillslopes and in close relation to geometry of hillslopes. The mode of the saturation index equation bore much resemblance to that of SMD in TOPMODEL. In this article, the relationship between these indexes was scrutinized and an equation was presented obtaining SMD from sigma. An equation regarding convergence, divergence, convexity, and concavity was introduced to calculate SMD for complex hillslopes.
Curvature influences on the velocity of water flow into soil and decreases travel time. Plan shapes of the hillslopes effects on flow width as well as drainage area. SMD in TOPMODEL is depended on the drainage area and slope of the hillslopes. At the first step, SMD was computed in two simple cases (regardless of geometry) and in the complex case along the hillslope to compare the results. Accordingly, the most changes corresponded to the convergent convex, and the least were of the concave parallel hillslope. The convergent hillslopes affected the SMD, 20% more than the divergent ones, on average. Also, the convex hillslopes reacted more relatively to the concave ones. At the second pace, the effects of convergence, divergence, convexity, and concavity on SMD were studied more accurately.
The main goals of this research were: Development of Topmodel equations to consider geometry of complex hillslopes in the nature; Studying the effects of complex hillslopes geometry on soil moisture deficit; Computing subsurface flow of complex hillslopes using COMPLEX TOPMODEL.
According to the results, the convex convergent hillslopes had the greatest variation in SMD, while the parallel concave hillslopes had the least. Convergent hillslopes showed more reactions to geometry comparing to the divergent hillslopes, and the same fact holds for the convex hillslopes relative to the concave ones. The more rainfall recharged rate, the faster saturation occurred along with less SMD. An increase in SMD happened when SA enlarged as long as the other conditions of hillslope were constant. TOPMODEL having vast applications in estimation of flows under sub-catchments (corroborated by the previous studies), could yield better results in the complex cases. Precise computation of SMD has great importance in the rainfall-runoff models. In this research the subsurface flow equations were developed for complex hillslopes, and an equation was presented by which the subsurface flow profile and the average discharge in each hillslope could be computed based on the sigma index.

Water repellency of soils is a property with significant consequences for agricultural water management, water infiltration, vertical soil-water transport, contaminant transport, and for soil erosion. It is caused by the presence of hydrophobic organic materials on soil grains and aggregate surfaces. Dry soil usually absorbs moisture but hydrophobic soil resists or reduces water infiltration into soil. Water repellency potentially affects wetting front and solutes transport in soil. This research was conducted in hydrophobic soils in order to investigate wetting pattern. The soil was collected from the region in the vicinity of sewage pilot of Fouladshar, Isfahan, Iran. Different amounts of urban sewage sludge including 25, 50, 65 and 80 weight percent were added to hydrophilic soil and S25%, S50%, S65% and S80% were obtained. After almost one year, soil water repellency was determined by using water drop penetration time method. In this procedure Three drops of distilled water from a standard medicine dropper are placed on the smoothed surface of a soil sample, and the time that elapses before the drops are absorbed is determined. In general, soil is considered to be water repellent if the WDPT exceeds 5 s. In this way the following classes were distinguished: wettable or non-water repellent (

Rock fill materials are among the useful materials in operation of hydraulic structures that are being frequently used by engineers and designers of hydraulic structures, because of lower cost and environmental sustainability. Knowing of water profile is valuable for practical purposes and designing, sometimes observed that because of mining or roadway operations in vicinity of rivers, the rock materials were fallen to river bed and changed the flow regime from open channel flow to the None-Darcy inner flow. Another use with these materials is in building of rock fill detention dams for flood mitigation in river downstream, which nowadays become so common in Iran. These dams temporary reserves the flood in its low capacity reservoir and then passes from its body with delay. Flow through large porous media could be interpreted with both equations of pipe and open channel flow. Since the flow in rock drains or detention dams have a free surface, it is usual to apply open channel equations like GVF in profile estimation. Different types of numerical or theoretical equations have been employed by previous researchers for its solving, but it should be mention that in these type problems, the method would be valuable which could be applied easily. Therefore, single step direct numerical methods were selected in the present study. Furthermore, because of nature of water surface profiles inside the rock fill dumps, the method of calculation could be capable for estimation of the flow depth according to the profile length.
For laboratory data collection, an experimental setup was created in which the semi crashed riddled rock materials placed between two vertical screen walls such that a grid of Piezometric tubes had been positioned in the centerline of rock media. By changing of media size and length, the different type of physical configurations created. Then by employing of four different discharges, the surface profile acquired. The photography and digitizing technic have been used for experimental data extraction. Moreover, water supply system of the flume has been connected to the constant head tank of laboratory, and the discharges were measured by means of pre-calibrated V notch. In this research, water surface profiles were obtained experimentally by two rock diameter, two media length and four operation discharges. Then, by using of gradually varied flow equation and three numerical methods including Euler, modified Euler and 4th order Range-Kutta, The water surface profiles were simulated numerically and compared with experimental profiles. In all of these methods the exit point height from the experimental data series were employed as the boundary condition. The flow condition at that point is generally different from other parts of rock body. Different researchers have presented some relationships for exit height, but most of them related it to the critical height in the particular discharge. By focus on experimental observations, Because of existing of large slope in surface profile, the flow regime changes rapidly and the GVF equation may be unsuitable in the mentioned regions but because of low length of it the discrepancy in profile calculations is negligible. Therefore, more research is needed to investigate it in details and disquisition around it is not from the purposes of this research. One of the most important subjects of profile estimation is to calculate pore velocity which is dependent on media size and porosity. Previously, several types of pore velocity equations have been presented, but the most famous one is the Wilkins relationship. Because of None-Darcy and turbulent nature of inflow, the relationship between hydraulic gradient and pore velocity is quadratic and the effect of first term of Forchheimer’s equation is negligible.
After acquisition of experimental surface profile in different flow and physical configuration of laboratory setup and programming of the selected numerical methods in MATHLAB software, the comparisons of results were done. Then it was observed that 4th order Range-Kutta method with 4th order accuracy has the better estimation accuracy rather than other two methods with average RMSE equal to 1.19 and average R2 equal to 0.9. Also, it should be mentioned that because of the large magnitude of hydraulic grade in exit regions of porous media, use of Range-Kutta method imposes some errors in the profile estimation in the exit region. Therefore, application of modified Euler at the aforementioned zone has the better conclusions.

The complete time series of meteorological data with enough length is one of the most fundamental issues in environmental and hydrological studies. However, weather stations often have statistical gaps due to lack of measured data or technical problems (Tardio and Bertie, 2012). Precipitation data are so important for climate studies and frequency analysis of hydrologic events such as floods, droughts and also water resources planning and management. Estimation of missing values has been a subject of interest to meteorologists, hydrologists and environmental experts. Recently, artificial intelligence models support vector machine (SVM) and Artificial Neural Network (ANN) has been used to reconstruct the rainfall data. SVM is a supervised learning method that can be used for classification and regression. This method, developed by Vapnik (1998), is based on the theory of statistical learning. The other method which is widely used to predict the characteristics of non-linear and complex phenomena is artificial neural network. Artificial intelligence and neural network models were proposed by McCulloch and Pitts (1943), for the first time, to predict precipitation. Golabi et al. (2013) compared the performance of different algorithms of artificial neural networks for modeling seasonal rainfall in Khuzestan province. In this study, MLP and RBF networks with applying some changes in the middle layers, neurons, and training algorithms MOM, LM and CG were used to predict seasonal rainfall. The main purpose of this study was to compare the performance of artificial neural network (ANN) and Support Vector Machine (SVM) in reconstructing of precipitation in rain gauge stations of Hamedan Province. For this purpose, the monthly precipitation data of four rain gauge stations, including Aghajanbolaghi, Sarabi, Aghkahriz and Maryanej, were used during the period of 1991 to 2010.
SVM regression model is depended on a functional dependence y to a set of independent variables x estimated. It is assumed that other issues such as regression, the relationship between the dependent and independent variables by a certain function f noise, plus an additional amount are determined. In this study, SVM model was used to reconstruct the missing data by using non-linear kernel function of RBF Statistica10 and with more than 100 replicates. The Kernel function were used because higher accuracy in the reconstruction of the monthly precipitation data. Optimal characteristics of SVM model include Ɛ, C and ɣ should be determined. For this purpose, characteristics C and Ɛ by was calculated by the network search optimization algorithm and variable ɣ by trial and error. An artificial neural network is composed of neurons. The smallest units of information-processing are neurons or nodes which form the basis of the performance of neural networks (Minhaj, 2005). Each neuron receives input and then processing them, generate an output signal. Thus, the neurons in the network act as a center for processing and distribution of information, its own input and output (Sadorsky, 2006). The study of artificial neural networks Multilayer Perceptron (MLP) is used by the propagation algorithm. The precipitation data of four stations including Aghajanbolaghi, Sarabi, Aghkahriz and Maryanej, were used in this study. These stations were chosen based on their close distance and high correlation in monthly precipitation data. To determine the best input pattern for the network, the various factors that may affect the phenomenon should be considered. To reconstruct rainfall data in neural network, programming in Matlab software is used. In order to evaluate the performance of Support Vector Machine (SVM) and artificial neural networks (ANN) in reconstructing the missing precipitation values, the Coefficient Determination (R2) and root mean square error (RMSE) were calculated for observed and estimated precipitation values.
In this study, the MLP artificial neural networks and RBF Support Vector Machine models were used for reconstruction of monthly precipitation data of rain gauge station of Sarabi in Hamedan province, during the years 1991 to 2010. Three modes were intended as training models. Models for training in the first case used only one station data (Aghajanblaghy), the second used two stations data (Aghajanblaghy and AqhKahriz) and for the third training data from three stations were used (Aghajanblaghy, Aqhkahriz and Maryanaj). Also, Sarabi was considered as reconstruction station. The results of this study indicated that when the data for one and two stations were used for training in modeling, the Support Vector Machine model showed better performance than SVM. While, using the data from three stations in the models, the artificial neural network model was better than the Support Vector machine with a little difference. Reconstructing of monthly precipitation, the best performance was obtained by using data from three stations for training ANN and SVM. Coefficient Determination and RMSE for the models were 0.88 and 12.33 mm for ANN and 0.87 and 12.89 mm for SVM. Reconstructing of seasonal precipitation, the best results was gained by using data from three stations for training ANN and SVM models. Coefficient of determination and mean squares for these models were 0.95 and 26.62 mm for ANN and 0.94 and 18.82 mm for SVM. Although both models in three different educational models performed almost the same in the reconstruction of monthly data (Sarabi), the results showed that when the number of stations in learning more models increased, the models performance improved.