Journal of Applied Research in Water and Wastewater
Volume:7 Issue: 1, Winter Spring 2020

In the article, through the adaptive neuro-fuzzy inference system (ANFIS), a sensitivity analysis is conducted on the variables affecting the discharge capacity of the weir. To this end, the variables affecting the discharge capacity of labyrinth weirs are initially identified. Then, using these input parameters, seven ANFIS models are developed for conducting the sensitivity analysis. After that, the most optimal membership function number for the ANFIS model is chosen. In other words, by conducting the trial and error process, the best number of the membership functions in terms of time and modeling accuracy are selected. Then, the sensitivity analysis is performed for the ANFIS models and the superior ANFIS model is chosen finally. The accuracy of the superior model in both the validation and testing artificial intelligence (AI) methods is in an acceptable range. For example, the scatter index (SI), correlation coefficient (R) and the Nash-Sutcliff efficiency coefficient (NSC) for the model in the testing mode are obtained 0.049, 0.964 and 0.924, respectively. It should be noticed that the outcomes of the sensitivity analysis show that the ratio of the weir head to the weir crest and the Froude number are introduced as the most effective input parameters. Eventually, a computer code is proposed to estimate the discharge capacity of labyrinth weirs by this model.

Alluvial rivers interact mostly with underlying groundwater bodies. These interactions that varies spatially and temporally, have recently received more attentions. This paper aims to evaluate the interaction between groundwater and surface water along the Dez river in the north part of the Dezful-Andimeshk district through developing a numerical simulation. For this purpose, the groundwater flow and river- groundwater interaction were simulated using a mathematical model in MODFLOW/GMS environment. The WetSpass model was used to estimate the groundwater recharge. The cluster analysis method, also, was utilized to identify the different zones of aquifer hydraulic characteristics. The results show that the Dez river has a losing connected nature and recharges groundwater. The river recharge to the aquifer was about 12 MCM during the 2013 and 2014. This recharge varies spatially and temporally and its maximum amount occurs during the 2014 March to June. Furthermore, the recharge rate was affected by the water release pattern from the Dez dam and topographic characteristics of the riverbed sediments. So that the maximum water exchanges occur in areas near the Chamgolak town and Dezful city with an average rate of 3.2 MCM per year.

In this study, for the first time, groundwater level (GWL) variations of the Sarab-e Qanbar well located in the city of Kermanshah, are simulated over a 13-year period by a hybrid model named WANFIS (wavelet-adaptive neuro fuzzy inference system). In order to develop the hybrid model, the wavelet transform and the adaptive neuro fuzzy inference system (ANFIS) model are utilized. Furthermore, the 9 and 4 year data are used for training and testing the artificial intelligence models, respectively. Moreover, the effective lags are detected by the autocorrelation function (ACF) and then eight different models are developed for each of the ANFIS and WANFIS models using them. After that, all mother wavelets are evaluated and Dmey mother wavelet is chosen as the most optimal. For this mother wavelet, the values of scatter index (SI), variance account for (VAF) and Root mean square error (RMSE) are obtained 0.192, 94.951 and 3.117, respectively. Next, the superior model is detected through the analysis of the results obtained by all ANFIS and WANFIS models. The superior model estimates the objective function values with reasonable accuracy. For example, the correlation coefficient (R), Scatter Index (SI) and variance account for (VAF) for this model are obtained 0.974, 0.192 and 94.951, respectively. The modeling results indicate that the wavelet transform noticeably enhances the ANFIS model accuracy. Finally, the lags of the time series data for the Sarab-e Qanbar well including (t-1), (t-2), (t-3) and (t-4) are introduced as the most effective lags.

The optimal design of urban water distribution networks is a significant issue that has been of critical interest in the water industry for many years. The optimal design of the distribution network aims to find the best solution for transferring water from the reservoir to consumers at the lowest cost. In this study, optimization of the water distribution network (ZONE 1 of Ilam city, Iran) was performed using the fast messy genetic algorithms (FMGA) tool in the hydraulic model for three different pipe networks. Also, these networks were optimized by using a combination of EPANET and an in-house developed binary genetic algorithm in MATLAB. The costs of the optimized hydraulic networks of polyethylene and polypropylene pipes were lower, respectively, by 20.56 % and 52.94 % compared to the consulting company's original designs, while for the glass fiber reinforced plastic pipe (GRP) pipe network the cost increased by 12.61 %. Also, the results of a developed algorithm for polyethylene pipe decreased by 22.13 %.

The hydrous bed of the rivers covered with coarse alluvial materials is a goodresource along with other resources to provide the needs of the water. Therefore,studying and investigating the flow behavior around wells excavated in these bedsand determining their discharge capacity is very important. Since the flow to thewells is radial and previous research on coarse, porous media, there has beenmainly for parallel flows, and yet any equation replacing the Laplace relationship incoarse, porous media, is not provided for non-Darcy radial flows with a free surface,Therefore, the extraction of the differential equation ruling on these types of flowsin the cylindrical coordinates and a method for numerical solution of them in thisresearch has been followed. Based on the research carried out in this research, thepower (exponential) equation as the most suitable basic relation for the analysis ofradial flows was determined and used. Also, in order to solve the governingequations a numerical model was developed using finite volume method. Thedeveloped numerical model act well for the analysis of radial flows in the coarsealluvial beds. The results of the implementation of the numerical model indicate thatthe pressure distribution can be considered hydrostatic.

Optimizing the crop cultivation pattern, in order to reduce water consumption, in arid and semi-arid regions such as Iran, due to water scarcity and food intake, is an essential solution for food intakes needs. Optimizing the crop cultivation pattern, in order to reduce water consumption, in arid and semi-arid regions such as Iran, due to water scarcity and food intake, is an essential solution for food intakes needs. In this study, new methods based on the election algorithms (EA) and gray wolf optimizer (GWO) algorithms were used to determine the optimal cultivation pattern in Moghan plain during the statistical years of 2007-2016. The objective function in the agricultural sector was based on each product and its yield, net from each product and the cultivar. Then, maximization of the objective function was performed using GWO and EA algorithm. The results of using GWO algorithm in determining the optimal crop pattern in Moghan plain showed that using economic policies such as changing the cultivar pattern, we can obtain a better result compared to EA algorithm in the agricultural sector. In general, the results of GWO algorithm showed that in the Moghan plain with 0.9, 140 billion rials, that is, about 42 % will have economic growth. In sum, the results showed that GWO algorithm with high values of statistical criteria (R2=0.96, RMSE=0.022 and NSE=0.75) has a higher efficiency in optimizing the crop cultivation pattern of Moghan plain, which can be applied to the correct planning for other cultivation areas to be employed.

The local scour around the bridge piers is the main cause of their destruction. Based on this, extensive studies have been done to understand this phenomenon. Most of these studies have been done under steady flow conditions. This is while the flow in the river is unsteady. Therefore, the experiments of this research were carried out under unsteady flow conditions. The purpose of this research is to investigate the scour around the dual bridge piers at different distances of the piers from each other in a uniform flow as well as unsteady flow using symmetric hydrographs. The hydrographs used in the experiments are stepped hydrographs in 5 steps. The experiments were conducted under clear water conditions and U/UC=0.95. In all experiments, the diameter of the bridge pier (D) was constant and equal to 2.5 cm. The center-to-center distance between the dual bridge piers (S) was selected as 2D, 3D, 4D and 5D. In the unsteady flow, with increasing relative distance between the dual bridge piers, the maximum dimensionless scour depth of the first and second piers was increased and its maximum was measured at a relative distance of S/D=5 (in the range of relative distances studied in the research). But in the uniform flow, the maximum dimensionless scour depth of the first and second pier was observed at S/D=3 and S/D=4, respectively. Also, at a constant distance between the piers, increasing the peak and base flow of the hydrographs step-by-step, increased the maximum dimensionless scour depth of the first pier of dual bridge piers with an increasing rate. However, increasing the peak and base flow of the hydrographs step-by-step, increased the maximum dimensionless scour depth of the second pier with a decreasing and increasing rate, respectively.

Industrial activities are one of the most important emission sources of greenhouse gases at a global level. The process of production, transportation, electricity consumption, and industrial wastewater are the four major components in producing greenhouse gases. Industrial wastewater management (collection, treatment, and disposal) results in direct emission of greenhouse gases (including carbon dioxide, methane, and nitrous oxide). Also, energy consumption in the wastewater treatment process causes indirect carbon dioxide emissions. The present study aimed to estimate the contribution of industrial wastewater treatment plants in Iran from this emission, in addition to identifying sources of greenhouse gas emissions in the industrial wastewater treatment plant and estimating greenhouse gas emissions from the industrial wastewater sector in Iran. In this research, the emission calculations were conducted by using the methodology of Intergovernmental Panel on Climate Change (IPCC) guidelines for calculating greenhouse gases emission. Based on the estimations performed in this study, 1,305.98 kt of CH4 were emitted directly from wastewater in 2017 in the entire industrial wastewater sector. Further, the results indicated that industrial wastewater treatment plants in Iran’s industrial parks generate 46.53 kt of CH4 directly and 259.5 kt of CO2 indirectly. According to the studies, the food industry, especially the industries involved in processing agricultural products (with 48.74 % of total methane emissions) has the highest greenhouse gas emissions in the country, followed by the paper production industry (with 27.46 % of total methane emissions) in the second place. One of the best strategies for reducing greenhouse gas emissions in industrial wastewater treatment plants is energy production from methane produced in large treatment plants and implementing necessary amendments in production processes to decrease wastewater production.

In this study, Ni+2 removal from aqueous solution was investigated by concurrent usage of Fe3O4 nanoparticles and a high frequency ultrasound (1.7 MHz). In addition to Ni+2 removal, presence of the high frequency ultrasound led to being cooled photovoltaic (PV) module. Studied variables were pH and adsorbent dose (AD). Results indicated that the Ni+2 removal efficiency increased with an increase in the pH ranging from 2 to 9. Furthermore, the Ni+2 removal efficiency boosted by an increase in the AD. However, no significant enhancement in Ni+2 removal efficiency was observed at the AD above 9 g. Generally, the maximum Ni+2 removal efficiency was about 79 % for contact time of 50 min at pH=9 and AD=9 g in the presence of ultrasound. At the efficient condition (pH=9, AD=9 g and contact time=50 min), using ultrasound showed 16-20 % enhancement in Ni+2 removal efficiency compared to no ultrasound usage. From heat transfer view, it was observed that propagation of 1.7 MHz ultrasound into nanofluid significantly has cooled the photovoltaic (PV) module. Moreover, an increase in concentration of nanofluid (AD) showed a positive effect on reduction of heat from the PV module surface and maximum generated power. Obtained data demonstrated that agitating nanofluid by 1.7 MHz ultrasound decreased temperature of the PV module up to 15.5 % compared to no cooling system.

Hazelnut shell was used as a green adsorbent and environment-friendly for magnesium ions (Mg2+) adsorption from hard water solution in batch system. The characterization of the biosorbent was entirely evaluated using SEM, XRD and FTIR analyses. Design of experiments (DOE) decreased the number of non-significant experiments, which resulted in reducing the time and cost of studies. Response surface methodology (RSM) was applied to dynamic assessment of the adsorption process. The effects of variables (pH, adsorbent dosage, Mg2+ concentration, time) and their interactions were investigated by central composite face design (CCFD). In addition, the numerical optimization was also analyzed. The results demonstrated that maximum efficiency, 56.21 %, and adsorbent capacity, 5.729 mg/g, occurred at initial concentration of 200 mg/L, adsorbent dosage of 1 g and pH 10 in duration of 59.816 min which were in good agreement with experimental results. In order to validate of the dynamic model, artificial neural network (ANN) was employed. Although RSM had a superior capability in developing of the model in comparison with ANN, it was acceptable to forecast the magnesium ions removal by both RSM and ANN approaches. Finally, the studies of the adsorption isotherms, kinetic models, reusability tests of the adsorbent and comparison with walnut shell were also done

In this study, removal of heavy metals from synthetic wastewater has been investigated using silica aerogel-activated carbon composite. The synthesized adsorbent was characterized by FE-SEM, FTIR and BET techniques. The effect of amine functional groups embedded on the surface of silica aerogel-activated carbon 0.5 wt. % composite, optimal initial pH of removal of ions, impact of initial concentration of the solution containing heavy metal ions, adsorbent amount and contact time on removal percentage of ions were investigated. The results showed the optimal pH of 8, optimal adsorbent amount of 0.3 g for the removal of cadmium ion and 0.06 g for the removal of lead ion and optimal contact time of 80 min for cadmium and 60 min for lead ions. Adsorption data were investigated using Langmuir and Freundlich isotherms and maximum adsorption capability for cadmium and lead was obtained at 38.16 and 175.44 mg/g adsorbent, respectively.

A new polyethersulfone (PES) microfiltration (MF) membrane was fabricated via phase inversion method using a melamine-modified zirconium-based metal-organic framework (MOF). The wettability and permeability of the membrane were measured using water contact angle and pure water flux (PWF), respectively. By introducing the MOF additive (0.1 wt. %) to the membrane matrix, the performance of the membrane in the separation of the oil-water mixture (different oil concentrations of 300 and 500 mg/L) was enhanced. The flux recovery ratio (FRR) of the modified membrane was significantly increased to 90.76 % compared to that in the bare membrane (20.41 %). Furthermore, the antifouling property was considerably improved.