فهرست مطالب

Applied Research in Water and Wastewater - Volume:6 Issue: 1, 2019
  • Volume:6 Issue: 1, 2019
  • تاریخ انتشار: 1397/10/11
  • تعداد عناوین: 12
  • Behrang Beiranvand *, Mehdi Komasi Pages 1-7
    The performance of dams due to high operating costs and irreparable damages caused by failures in the construction phase and during the dewatering and exploitation period should verified and monitored by proper behavioural analysis. Dewatering the dams will result in the saturation of the embankment and supports and, consequently, the reduction of the stability coefficient. Therefore, in order to allow an earth dam to tolerate the new conditions easily and without problems, the rate of dewatering should be within the range. In this study, pore water pressure in the body of Eyvashan earth dam was evaluated. The water level inside the clay core due to changes in the reservoir water level during the first dewatering and using the actual specifications of the materials by Geostudio and Plaxis software and compared with the results of the instrumentation in the dam body. In order to adapt the observed and predicted data, a multi-variable regression was used and the coefficient of determination was used and respectively the value of R2=0.9834 and R2=0.9863 was obtained which shows a very good agreement between the observed and predicted data. Indicating that the cache water pressure values and their occurrence are in good agreement with the initial design conditions and that the barrier behaviour is stable in terms of pore water pressure. Installed piezometers upstream of the core show a higher pressure than the downstream, due to the high saturation state of the phreatic line. Also, the height of pressure in the downstream of cut off in the results of numerical modelling and in the observed results has suddenly decreased, which indicates the correct function of the injection cut off.
    Keywords: Pore water pressure, Dewatering, Eyvashan earth dam, Instrumentation, Cut off
  • Rahim Gerami Moghadam, Behrouz Yaghoubi *, Mohammad Ali Izadbakhsh, Saeid Shabanlou Pages 8-15
    Generally, Hydraulic jumps usually happen at the downstream of hydraulic structures like ogee spillways. In addition, one of the parameters affecting the proper design of stilling basin is calculation of the hydraulic jump length. In this study, a hybrid method (ANFIS-DE) was proposed for modeling hydraulic jumps on sloping rough beds for first time. This approach forecasts values of the jump length by combining the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Differential Evolution (DE) algorithm. First, the variables affecting the hydraulic jump length including the ratio of bed roughness, the Froude number, the ratio of sequent depths and the bed slope were identified. Then, by combining the input parameters, five different numerical models were introduced. Furthermore, the k-fold cross validation (k=4) was utilized so as to verifying the numerical models. The results of the analysis of different numerical models indicated that the model with four input parameters (superior model) simulated the length of the hydraulic jump with higher accuracy. For the best model, the mean absolute percent error (MAPE), the correlation coefficient (R) and the root mean square error (RMSE) were predicted 4.875, 0.978 and 0.807, respectively. Finally, two parameters including the ratio of sequent depths and the Froude number were identified as the most important parameters in modeling the hydraulic jump length on sloping rough beds.
    Keywords: ANFIS, Rough Bed, Sloping Channel, Hydraulic jump, Differential Evolution Algorithm
  • Seyed Mohammad Ashrafi *, Maral Mahmoudi Pages 16-24
    In this study, water resources system of Great Karun watershed is modelled as a semi-distributed system considering the diversity of demand sites downstream of Olya Gotvand and Dez reservoirs in southwest of Iran. The main aim of the present study is to develop a basin's decision-support system to assist decision-makers in examining the impacts of different operating policies prior to their implementation. According to the basic characteristics of the system, a decision-support system is developed applying water evaluation and planning system (WEAP) model. Calibration of the developed model is important based on the Demand sites diversity and the spatial scale of the modelled basin. To calibrate the simulation model, a Harmony Search (HS) Optimization Algorithm is applied in an innovative framework. The comparison of the achieved results with the observed data indicates the accuracy of the calibrated model. It is also clear that, regardless of the quality parameters of the flow, all urban, industrial, agricultural and aquaculture demands at the basin level have been satisfactorily fulfilled in the study period. Of course, it should be noted that by taking into account the qualitative criteria, the obtained results will obviously change.
    Keywords: Decision support system, Water resources, Model calibration, Harmony search algorithm
  • Majid Rahimpour *, Mohammad Reza Madadi Pages 25-31
    Friction factor is an important hydraulic parameter for design of pipeline systems. There are several formulations for calculating the friction factor, among which Colebrook–White equation is the most accurate and repute formula. Owing to the implicit nature of friction factor in Colebrook–White equation, iterative methods are required to calculate this factor. In this study, Regula Falsi iterative numerical scheme was used to solve the implicit nonlinear equation of friction factor in the Mathematica programming tool. Case examples including different series and parallel pipeline systems were presented and solved. The results indicated high capability of Regula Falsi method in solving both the parallel and series systems. It was found that the solution by Mathematica differ significantly from conventional methods and can be desirably used for solving different hydraulic problems. The use of Mathematica with its huge features permits the researchers to be more professional in formulations of engineering problems and interpretations of results.
    Keywords: Hydraulic design, Pipeline systems, Mathematica, Frictional head losses
  • Mohammad Zeynoddin, Hossein Bonakdari * Pages 32-38
    Given the climate changes, achieving rainfall forecast is of high importance and facing such challenges affected markedly in vast areas of societies. Accordingly, numerous nonlinear and linear methods have been developed. Most hydrological phenomena like rainfall are consisted of both linear and nonlinear parts. Modeling such phenomenon with stochastic methods like seasonal auto regressive moving average model (SARIMA), which are linear, demands data preparation prior to modeling. In this study, by investigating different forms of data preparation methods, variations in stochastic modeling results are scrutinized. The pre-processing methods used are categorized in two parts, normalization and stationarzition of data. The rainfall series is initially normalized by 4 transforms, namely: Manly(Mn), John-Draper (JD), Yeo-Johnson (YJ) and Scaling (Sc). The series, then, are stationarized by differencing, standardization (Std) and spectral analysis (Sf). After achieving preferred results by numerous tests, the preprocessed data are then modeled by stochastic SARIMA model. With regards to error and model sufficiency indices and graphs results, the acceptable results, but not the best, was obtained by the Sc-Diff combination, with SARIMA (0,0,1) (3,0,3)12 model and coefficient of determination, 0.355, variance accounted for, 0.353, root mean square error, 0.313, scatter index, 1.030, mean absolute error, 21.355), corrected Akaike Information Criterion, 1227.03. The results revealed that concerning the severe fluctuations in data, a supplementary method, like hybridization with artificial intelligence (AI) methods, is needed to achieve preferable results.
    Keywords: Linear regression, Spectral analysis, Standardization, Stoochastic, Kermanshah
  • Amir Hossein Salimi, Sayed Farhad Mousavi, Saeed Farzin * Pages 39-44
    Rivers serve as one of the main sources of water supply. Human activities, salts in the soil and rocks and urban runoffs, as well as air contaminants, lead to contamination of river water. In this research, Gamasiab river, which is the upstream of Karkheh river, was selected as a case study. Sixteen stations were selected along this river to determine the sulfate content of water samples. Samples were taken from these stations according to the guidelines (ISO 5667-5, 1991). The samples were then transferred to laboratory and were filtered using nanoparticles of natural clinoptilolite. The X-Ray Diffraction (XRD), Transmission Electron Microscopy (TEM) andFourier-Transform Infrared Spectroscopy (FTIR) images were taken to determine the properties of the adsorbents. The images indicated that the selected methods for preparation of the nanoparticles were correctly implemented. After examining the filtered samples, the adsorption efficiency was 95% for clinoptilolite. Whatman filter paper 42 was used for desorption of the natural nano-clinoptilolite. Adsorption isotherm of the natural clinoptilolite was Freundlich with a determination coefficient of R2=0.918. By using Design Expert software and assumption of two pH factors and adsorbent to contaminant ratios (D/C), optimum adsorption points were found and theoretical adsorption values were calculated as well. Results showed that the optimum adsorption points for clinoptilolite were pH = 9.51 (mg)adsorbent/(mg/l)initial and D/C=18.91(mg)adsorbent/(mg/l) initial. Comparison of the adsorbent function indicated that clinoptilolite had good performance in removal of sulfate ion from river water samples.
    Keywords: Gamasiab river, Natural nano-clinoptilolite, Sulfate ion, Adsorption, Design expert software
  • Somayeh Heydari *, Leili Zare, Hamideh Ghiassi Pages 45-50
    The present study demonstrates the effective removal of diazinon pesticide from aqueous solutions by means of magnetic bentonite nanocomposite. The product was characterized by advanced techniques like scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDX) and infrared spectroscopy (IR). Operational parameters affecting the removal efficiency, including the pH level, contact time, agitation speed and adsorbent dose, were screened through Plackett-Burmann design to determine the significant factors. Then, significant parameters, including the pH level and adsorbent dose, were further optimized using Central Composite design to predict optimum removal conditions. Under the optimal conditions, the maximum adsorption capacity of the nanocomposite for diazinon was found to be 92.50 %. The kinetic of pesticide sorption and equilibrium studies were performed. The experimental data could be well fitted to the Freundlich model. The magnetic bentonite nanocomposite was successfully applied for the uptake of diazinon from industrial wastewater and groundwater samples and separated easily by means of magnetic separation.
    Keywords: Magnetic bentonite nanocomposites, Diazinon removal, Aqueous system, Plackett–Burman design
  • Vahab Ghaleh Khondabi, Alireza Fazlali *, Mojtaba Zolfaghari Pages 51-55
    On average, 67 % of household wastewater is made up of greywater, which includes wastewater produced in household other than toilets. There are different biological treatment processes for greywater treatment. One of these systems is the sequencing batch reactor (SBR), which has proven to be an effective way of treating wastewater. One of the amendments to the SBR process is the intermittent cycle extended aeration system (ICEAS). The purpose of this study was to investigate the performance of an advanced-SBR in the bathroom greywater (BGW) treatment. For this purpose, a rectangular SBR reactor (402020 cm) with a working volume of 12 liters was developed and utilized. The primary microorganisms of this reactor were prepared from the active sludge return to the aeration pond of the Arak municipal wastewater treatment plant. The reactor was fed with the effluent from the initial settling ponds of the same treatment plant. After the system was set up and sufficient microorganisms were grown, the exploitation phase began with synthetic greywater. The experiments were carried out in three cycles of 4, 6 and 8 hours. The concentrations of linear alkyl benzene sulfonates (LAS), chemical oxygen demand (COD) and biochemical oxygen demand (BOD5) at the inlet were 6.8 mg/L, 385 mg/L and 170 mg/L, and in the outlet, 0.95 mg/L, 19.25 mg/L and 8.5 mg/L, in a 8-hour cycle. Therefore, the removal efficiency of the system in 8 h cycle was 86 %, 93 % and 95 %, respectively.
    Keywords: Activated sludge system, Bathroom greywater, Intermittent cycle extended aeration system, Linear alkyl benzene sulfonates, Sequencing batch reactor
  • Zahra Jamshidzadeh *, Majid Tavangari Barzi Pages 56-61
    Treated wastewater reuse for agriculture is an effective solution to cope with water scarcity conditions in arid and semi-arid areas. The aim of this study was the performance evaluation of a bench scale recirculation sand filter (RSF) for organic matter and nutrients removal from restaurant greywater at the University of Kashan. The average percent removal of 96.9 %, 96.3 %, 98.3 %, 92.8 %, and 70 %, corresponding to five-day biological oxygen demand (BOD5), chemical oxygen demand (COD), turbidity, total nitrogen, and total phosphorous indicated satisfactory performance of the system for treatment of restaurant greywater with higher concentrations of pollutants compared to typical households greywater. Substrate removal kinetics of the system were assessed by measuring BOD5 and COD values of septic tank, recirculation tank, and filter bed effluents. First order and second order kinetic models were applied to obtain COD and BOD5 removal kinetic coefficients for the recirculation tank and the filter bed. Kinetic parameters of the recirculation tank were determined using regression analysis and the results showed that both models were appropriate to describe the substrate removal in the recirculation tank. The reaction rate constants of K=1.9 1/d and 0.4 1/d respectively for BOD5 and COD were obtained by the first order model, while the corresponding values for the second order model were K=0.004 L/mg.d and 0.0003 L/mg.d. For the filter bed, the first-order reaction rate constants K=1.3 1/d and 1.73 1/d were found for BOD5 and COD, respectively. The second order model was not well qualified for evaluation of the filter bed performance. The results of kinetic models can be used to predict the behavior or design of the recirculation sand filter in full scale applications.
    Keywords: Recirculation sand filter, Greywater, Substrate removal, Kinetic study
  • Hossein Hazrati *, Zahra Sadat Sajadian, Nader Jahanbakhshi, Mohammad Rostamizadeh Pages 62-66
    In this paper, the effect of different sludge retention times (SRTs) on membrane fouling of membrane bioreactor (MBR) systems including synthesized ZSM-5 nano-adsorbent was investigated. Three MBRs including nano-adsorbent were applied in SRTs of 10, 50 and 100 d during six months for wastewater treatment. Soluble microbial products (SMP) and extracellular polymeric substance (EPS) concentration analyses were conducted on the sludge of the bioreactors. Particle size distribution (PSD), Fourier-transform infrared (FTIR) spectroscopy, excitation- emission matrix (EEM) fluorescence spectroscopy, gel permission chromatography (GPC) were performed for determining the properties of the formed cake. Based on GPC test, at SRT of 10 d, organic compounds with varied molecular weights had the low concentration, while compounds with lower molecular weight were found more at SRTs of 50 and 100 d. FTIR and EEM analyses also revealed high concentration of protein compounds in MBR. Consequently, the membrane fouling was decreased in MBR at SRT of 10 d compared to SRTs of 50 and 100 d. In fact, transmembrane pressure (TMP) was 15, 21 and 25 kPa for SRTs of 10, 50 and 100 d, respectively. The EEM results showed that in addition to reduction of proteins by nano-adsorbent in SRTs of 10 and 50 d, the humic compounds were also reduced. The results showed the high efficiency of ZSM-5 nano-adsorbent for reducing of membrane fouling at the low SRT.
    Keywords: MBR, ZSM-5 nano- adsorbent, Membrane fouling, SRT, Cake properties, Wastewater
  • Danial Nayeri, Seyyed Alireza Mousavi *, Azadeh Mehrabi Pages 67-72
    In this study, oxytetracycline removal from aqueous solution by activated carbon prepared using corn stalks has been investigated. The adsorbent was characterized using Fourier transform infrared spectrophotometer (FTIR) and scanning electron microscope (SEM). The effects of main variables; adsorbent dose, contact time, pH, and initial oxytetracycline concentration on the efficiency of adsorption efficiency were investigated. Results confirmed the effects of main variables and the maximum removal of antibiotic (99.9 %) achieved at initial concentration of 10 mg/L, pH of 9, and contact time of 60 min, when adsorbent dose was 1.5 g. The results of isotherm and kinetic studies showed that the oxytetracycline adsorption onto activated carbon prepared from corn stalks follows Freundlich isotherm (R2 = 0.98) and pseudo-second order kinetic model (R2 = 0.99). The maximum adsorption capacity of oxytetracycline was 522.6 mg/g. In brief, the activated carbon that has been prepared from corn stalks as low cost, non-toxic and environment friendly adsorbent shows a good ability for removal of oxytetracycline form water and wastewater.
    Keywords: Adsorption, Activated carbon, Corn stalks, Antibiotic, Wastewater
  • Yahya Choopan, Somayeh Emami Pages 73-79

    In this study, barley yield has been estimated via radial basis function network (RBF) and feed-forward neural networks (GFF) models of artificial neural network (ANNs) in Torbat-Heydarieh of Iran. For this purpose, a dataset consists of 200 data at three levels of irrigation with well water, industrial wastewater (sugar factory wastewater), a combination of well water and wastewater in two levels (complete irrigation and irrigation with 75 % water stress) and soil characteristics of area were used as input parameters. To achieve this goal, based on the number of data and inputs, 200 barley field experiments data set were used, of which 80 % (160 data) was used for the training and 20 % (40 data) for the testing the network. The results showed that RBF model has high potential in estimating barley yield with Levenberg Marquardt training and 4 hidden layers. Also the values of statistical parameters R2 and RMSE were 0.81 and the 33.12, respectively. In general, the results showed that ANNs model is able to better estimate the barley yield when irrigation water level parameter with well water is selected as input.

    Keywords: artificial neural network, Barely yield, RBF model, GFF model, Modeling