سارا نظیف

Due to continuous changes in the quantitative and qualitative characteristics of wastewater influent in wastewater treatment plants (WWTPs), it is necessary to evaluate the performance of WWTPs under different conditions and adopt appropriate control strategies. The first step in evaluating and improving the performance of a WWTP is to model it. In recent years, there has been an increase in the application of simulation software and mathematical models for this purpose. Calibration is considered the most important step in modeling because improper calibration can lead to unrealistic results with a large error. The main objective of this research is to redevelop the BSM11 model and provide different calibration scenarios to model the carousel oxidation system on a real scale. The high-accuracy model can then be used for various purposes, such as implementing different control strategies and improving the performance of the WWTP under different operating conditions. The developed model was implemented on modules 5 and 6 of the WWTP located in the south of Tehran. After determining the suitable process models for different units of the wastewater treatment plant, model calibration based on the GMP2 protocol was performed under two scenarios: 1) simultaneous calibration of parameters, and 2) step-by-step calibration of parameters. In each scenario, two objective functions were considered to evaluate the effect of main variables, including COD, TSS, and TN, and secondary variables, including X (MLSS3 of the aeration tank) and Xr (MLSS of the return sludge). The genetic algorithm was used to optimize the objective functions during the calibration process. The results showed that in the static calibration, the average error of all variables, as well as the variables considered in the objective function in scenario 2, were significantly reduced compared to scenario 1. The values in scenario 2 for objective function 1 were 2.7%, 7.8%, 8.2%, and 4.3% for the variables mentioned. Additionally, by considering more variables in the objective function, the cumulative error of all variables was reduced. In dynamic calibration, the average error rates of the model for TSS, COD, and TN were 29.8%, 19.8%, and 10.3%, respectively.

Without hydrological models the investigation and management of watersheds can be time-consuming and costly. This study aims to explore various hydrological factors including runoff, sedimentation, evaporation, and transpiration in Pasikhan watershed located in Guilan province. The study also examines the impact of these factors on the Anzali Wetland. To achieve this, the research utilizes the SWAT model. Data on flow discharge, precipitation, and sedimentation for three hydrometric station in the Pasikhan watershed from 1999 to 2020 were obtained from the regional water company of Guilan province. The necessary maps for model execution were obtained using established methods. Predictions for various factors, such as flow rate, sedimentation, surface runoff, evaporation and transpiration, deep aquifer recharge, curve number, deep infiltration, and watershed runoff, were made for the years 2040 and 2071. Discharge-sediment from 1999 to 2011 is used for calibration and for validation used the data from 2012 to 2022 is used. The study also assessed changes in hydrological components caused by climate change using the RCP8.5 scenario and land use changes. The findings demonstrate variations in multiple hydrological elements and precipitation patterns within the catchment basin. The Nash Sutcliffe criterion yielded values between 0.60 and 0.80 for both the calibration and validation phases of the model in terms of flow rate and sedimentation. This indicated that the implementation of the SWAT model is satisfactorily accurate. Results showed that the maximum surface runoff within the basin will reach 485 mm in 2055, coinciding with a rainfall of 1431 mm. Additionally, the study identified the highest levels of evaporation and transpiration as 1707 mm within the RCP8.5 scenarios in 1996. Overall, the research emphasizes the negative impact of sediment generated within the Pasikhan watershed on the Anzali Wetland, highlighting the need for effective control measures to mitigate wetland degradation

In the last few decades, due to the growth of industries, drastic changes have occurred in the climate of the planet, and its average temperature has increased significantly. Land use changes and climate have had a great impact on discharge and sediment production in watershed. The increase in the production of sediments has many harmful environmental and constructional effects; among these effects we can mention the reduction of the useful depth of the dam and consequently the reduction of the life of the dam. The purpose of this study is to investigate the process of sedimentation along the Mubarakabad River (Emamzadeh Ebrahim watershed) and the effect of time on the increase in the sedimentation depth of the Lasak dam reservoir located in Guilan province using the HEC-RAS model in different states for the time range of 1997 to 2071.

Mubarakabad River is one of the main branches of Pasikhan River, which is the most important river supplying water to Anzali wetland. This watershed has various uses, including forest, degraded pasture, medium pasture and good quality pasture, residential, paddy field, etc. To carry out this study, land use changes in the years 1997, 2007, 2020, 2040 and 2071 were used. In order to measure the runoff, sediment and flow rate in the coming years (2022 and 2071) with the help of the LARS-WG statistical model in two scenarios (RCP 4.5 and RCP 8.5) and SWAT tool was investigated. To implement the HEC-RAS model, three models of surface reduction were used: Borland and Miller's method, Moody's surface reduction method and surface increase method. The input variables of the model are loaded in three sections: topographic map, discharge information, discharge-sediment, and sediment grading. The model was calibrated using discharge and sediment data during the study period. In this study, changes in sedimentation along the Mubarakabad River from upstream to the construction site of Lasak Dam were investigated. Also, the sedimentation depth of the dam reservoir was investigated in different years using the HEC-RAS model.

The simulation results of this study showed that with passing of time, the percentage of residential areas will increase significantly and the area of pastures located in the southern part of the basin will decrease. Currently, in this basin, the total area of 1.87 km2 has been allocated to the residential sector, which includes several villages. While in 2071, this amount will reach 21.45 km2. Also, pastures with dense coverage in this basin in 1997 were equal to 99.65 km2, and in 2071 this amount will decrease to 4.82 km2. The results of this study showed that from the source to the construction site of the dam, sediment deposition has increased due to the reduction of the slope, and the largest amount of sediments have accumulated in the reservoir of the dam. It was also observed that with passing time, the depth of sediments behind the dam reservoir has increased significantly, which reduces the efficiency of the dam. The results of this study showed that there is an increasing trend in the sedimentation depth of the reservoir, so that its maximum value was obtained in 2071, equivalent to 39.1 meters from the height of the dam intake. The results of this study show that in the years 2071 and 2040, 2.02 and 1.92 million tons of sediment will settle in the Lasak dam reservoir, respectively.

According to the results obtained from the HEC-RAS model simulation in the Emamzadeh Ebrahim watershed, it can be seen that if detailed and executive planning is not done in this area, land use change will occur severely. This change of uses causes the increase of soil erosion and production of sediment in the watershed, in other words, this change of uses can be considered as an alarm for the destruction of Anzali Wetland. In general, due to the conditions of the watershed and its high erosion upstream, the life of the Lasak dam will not be long, and its construction will reduce the water rights of the Anzali wetland and lead this international wetland to complete destruction at a faster rate.

The purpose of the current research is to investigate the quality of governance in Iran between 1996 and 2021, and to organize the research, four questions are raised: How has the quality of governance in Iran performed in the period under review? How has the governance quality model been in Iran? What is the prediction about the future of Iran's governance? And finally, what are the most important factors in determining the quality of governance? In order to answer the research questions, time series techniques and structural equations are used. The results of the research indicate that the quality of governance, which means the use of power, interaction and accountability, and examines the efficiency of political systems, has had periodic performance with a downward trend in the period under review in Iran, so that its best performance is related to It was the initial year, and during the following years, the level of governance quality has never been equal to it; In addition, the worst performance of the quality of governance in Iran is related to the last year of the period, which is a confirmation of the declining quality of governance in Iran. Among the six dimensions of governance quality, political stability and corruption control have been identified as the most important influencing factors. The time series forecast also indicates that the continuation of the existing processes will lead to the continued decline in the quality of governance in Iran, which has the potential to create dissatisfaction among Iranians.

Climate change and its intensifying impact on the hydrological cycle have been acknowledged in recent years. Considering the importance of available snow to the water resources recharge, especially in semiarid regions, evaluating climate change impacts on snow cover area (SCA) has gained significant attention. In this study, a methodology is presented which is capable of evaluating the impact of climate change on SCA. To collect historical data, MODIS snow products are used. To evaluate the impact of climate change on SCA, the turning points of SCA time series are detected using the Standard Normal Homogeneity Test; and the trend of historical data is analyzed using Mann-Kendall and Sen’s slope tests. To project the future SCA (2021-2099) under climate change considering precipitation and temperature as inputs an Artificial Neural Network-based model is developed. The proposed methodology is tested in sub-basins in Iran. Analyzing the present SCA (2000-2020) the results showed that the SCA’s turning points are only detected in two sub-basins of Tashk-Bakhtegan-Maharloo in 2007 and Gavkhooni in 2008, respectively. Moreover, a significant decreasing trend of SCA is detected during winter in the majority of sub-basins. According to the results, most sub-basins will experience a significant reduction in their future SCA under all climate change scenarios. In other words, compared to the historical SCA, the average future SCA will increase by 100 percent in RCP 4.5 scenario while decreasing by 20 percent in RCP 8.5 scenario.

Flood routing is an important issue in river engineering. The flood routing methods are categorized into two groups of hydraulic and hydrologic methods. Hydraulic routing methods require considerable input data and time-consuming calculations. But hydrological methods need less input data and are less complicated in comparison with hydraulic routing methods. The hydrological routing methods are based on the continuity equation and a relationship between inflow/outflow values and flood storage. Linear Muskingum is a hydrological routing method commonly used in rivers routing. However, as the relation between channel storage and the inflow/outflow is nonlinear, the nonlinear form of this model is developed which has received special attention in recent years and several types of it have been proposed. Using the Muskingum method, while saving time, valuable information about the flood depth and hydrograph is obtained. However, the performance of these models is highly dependent on the optimal estimation of their parameters considering the study area characteristics.

Although the nonlinear Muskingum models have special advantages over the linear Muskingum model. The hydrologists avoid from the nonlinear Muskingum models, because of the difficulties in estimation of their parameters. Therefore, researchers have attempted to estimate these parameters using the optimization algorithms. In this research, the nonlinear Muskingum model type 5 (NL5) is considered for flood routing and Nonlinear programing (NLP) is used for estimation of the optimal values of model parameters. The results are compared with the metaheuristic optimization algorithms of genetic algorithm (GA), particle swarm optimization algorithm (PSO) and Gray wolf optimizer (GWO). The objective function of the optimization algorithms was set to minimize the sum of squares of the difference between the measured and simulated values of flows (SSR). Wilson flood hydrograph (first case study), Wy River flood hydrograph in England (second case study) and the hydrograph presented by Vatankhah (2014) (third case study) were used as the case studies of this research.

The performance of NL5 model was very good in the all considered cases. In the first case study, the maximum absolute error is less than seven percent. Also, in the second and third case studies, the maximum absolute errors are less than 20 percent and 10 percent, respectively. MARE, NSE, CC, DPO and DPOT measures were used to further evaluate the model performance. The closer values of MARE, DPO and DPOT to zero and the closer the values of the NSE and CC measures to one, show the better the performance of the model (Kult et al., 2014). In the first case study, the MARE values for NLP, GWO, PSO and GA algorithms are 0.011, 0.011, 0.012 and 0.012 m3/s, respectively. For the second case study, the MARE values are 0.104, 0.105, 0.103 and 0.104 m3/s, respectively; The values of this measure in the third case study for the mentioned optimization methods are 0.0301, 0.0301, 0.0301 and 0.0303 m3/s, respectively. The values of this measure show the perfect performance of NLP, GWO, PSO and GA techniques in estimation of NL5 parameters. DPO, DPOT, NSE and CC indices also show the same finding. SSR values in the first case study for NLP, GWO, PSO and GA optimization methods are 5.44, 5.44, 5.47 and 5.88, respectively. Also, SSR values for the second case study are 30837.6, 30848.2, 30880.1 and 30929.1, respectively. For the third case study, these values are 7356.7, 7432.1, 7391 and 7412.3. The simulation times for NLP, GWO, PSO and GA methods show that the processing time in the NLP method is much less than the other methods. The optimization methods are ranked based on their results accuracy and simulation time. NLP method is ranked first in the regard while is followed by GWO, PSO and GA in the next ranks, respectively. The comparison of the obtained SSR values in the current study and the previous studies which used the cases one and two, show that the NLP optimization method has better performance in estimation of NL5 model parameters. In this study, for the third case study (Vatankhah, 2014 data), which has not been routed by the Muskingum method previously, the results of routing with NL5 are compared with the results obtained with the Rang Kota method (Vatankhah, 2014). The SSR value when using NLP as the optimization tool for estimation of NL5 model parameters is 7356.8 m6/s2, while in the Rang Kota method it is 14441.3 m6/s2. Therefore, in this case study, the NL5 model has performed better than the Rang Kota method.

In the present study, NLP technique and powerful GWO algorithm were used to estimate the optimal values of NL5 model parameters and the results were compared with GA and PSO algorithms. The performance evaluation results indicate that the NLP method, in addition to being more accurate, also requires less time to estimate the optimal value of the parameters. The values of the objective function for the first case study for NLP, GWO, GA and PSO methods are 5.44, 5.44, 5.88 and 5.47 m6/s2, respectively, while these values for the second case study are 30837.6, 30848, 30929.1 and 3088.1 m6/s2 and for the third case study are 7356.7, 7432.1 7412.3 and 7391 m6/s2. NLP processing time is at least 10% less than the other considered optimization methods. Therefore, the NLP method is the best choice for estimating the optimal parameters of Muskingum type five by considering two factors of accuracy and speed of simulation even though all of the methods showed a very good performance. Also, in the third case study, which was not routed previously, by the Muskingum method, the results were compared with the Rang-Kota method, and the results showed that the NL5 model, which was solved by the NLP method, performed better. After NLP, GWO, PSO and GA methods had the better performance in estimating the NL5 parameters, respectively.

This article has been carried out to explore the concept of childhood through one of the most symbolic cultural tools i.e. children television programs in a period of Iranian political and social history that is more than anything in the control of conflicting signifiers such as conflict in politics and identities which occur in the new lifestyle of the social arena. Shantal Mouffe attempts to discover the agonistic domains of irreconcilable distinctions between our and/or their collective identities with the help of the empirical theoretical framework using a network of meaningful intertextual relationships. Press semiotics has been used to discover hegemonic (though incomplete and vulnerable) forms of identity in children. The question of how children are represented in Iranian television production programs and how they represent them in relation to the ruling power is the question of the present article. Investigating the semantic conflict of the 1980s led to the representation of two different ‘others ‘, one critical in the absent signs of the new style of life and the other in the representation of our identities. The hegemonic discourse of the 1980s was considered as the decisive point of textual analysis. The findings indicate the representation of children as a political subject and the potential position of resistance to compromise with superior power that explains the child’s relationship with political power within self-critical discourse.

Increasing frequency and intensity of flooding in urban areas have led to serious damage in urban areas. One of the major challenges in urban flood analysis is the two dimensional simulation of surface runoff caused by surcharged flows from urban drainage systems. Thus, development of an urban flood simulation model, which can rout the water flow on complex topography of urban catchments and determine flooded areas with acceptable computational time and accuracy is very important. In this study, a flood simulation model based on cellular automata approach is developed to reduce time and computational effort in compare with other 2D conventional hydraulic models. The developed model performance is compared with HEC-RAS, shallow water equation and TUFLOW models which simulate the water movement using conventional numerical schemes. Also the model’s stability is assessed by considering different time step and mesh size. The obtained results show that the proposed model, using topographic and surface roughness data as inputs, can simulate water movement with acceptable accuracy one- and two-dimensionally. In addition, the computational time is reduced up to roughly 60 times compared to the model which is based on shallow water equations. Increasing frequency and intensity of flooding in urban areas have led to serious damage in urban areas. One of the major challenges in urban flood analysis is the two dimensional simulation of surface runoff caused by surcharged flows from urban drainage systems. Thus, development of an urban flood simulation model, which can rout the water flow on complex topography of urban catchments and determine flooded areas with acceptable computational time and accuracy is very important. In this study, a flood simulation model based on cellular automata approach is developed to reduce time and computational effort in compare with other 2D conventional hydraulic models. The developed model performance is compared with HEC-RAS, shallow water equation and TUFLOW models which simulate the water movement using conventional numerical schemes. Also the model’s stability is assessed by considering different time step and mesh size. The obtained results show that the proposed model, using topographic and surface roughness data as inputs, can simulate water movement with acceptable accuracy one- and two-dimensionally. In addition, the computational time is reduced up to roughly 60 times compared to the model which is based on shallow water equations. Increasing frequency and intensity of flooding in urban areas have led to serious damage in urban areas. One of the major challenges in urban flood analysis is the two dimensional simulation of surface runoff caused by surcharged flows from urban drainage systems. Thus, development of an urban flood simulation model, which can rout the water flow on complex topography of urban catchments and determine flooded areas with acceptable computational time and accuracy is very important. In this study, a flood simulation model based on cellular automata approach is developed to reduce time and computational effort in compare with other 2D conventional hydraulic models. The developed model performance is compared with HEC-RAS, shallow water equation and TUFLOW models which simulate the water movement using conventional numerical schemes. Also the model’s stability is assessed by considering different time step and mesh size. The obtained results show that the proposed model, using topographic and surface roughness data as inputs, can simulate water movement with acceptable accuracy one- and two-dimensionally. In addition, the computational time is reduced up to roughly 60 times compared to the model which is based on shallow water equations. Increasing frequency and intensity of flooding in urban areas have led to serious damage in urban areas. One of the major challenges in urban flood analysis is the two dimensional simulation of surface runoff caused by surcharged flows from urban drainage systems. Thus, development of an urban flood simulation model, which can rout the water flow on complex topography of urban catchments and determine flooded areas with acceptable computational time and accuracy is very important. In this study, a flood simulation model based on cellular automata approach is developed to reduce time and computational effort in compare with other 2D conventional hydraulic models. The developed model performance is compared with HEC-RAS, shallow water equation and TUFLOW models which simulate the water movement using conventional numerical schemes. Also the model’s stability is assessed by considering different time step and mesh size. The obtained results show that the proposed model, using topographic and surface roughness data as inputs, can simulate water movement with acceptable accuracy one- and two-dimensionally. In addition, the computational time is reduced up to roughly 60 times compared to the model which is based on shallow water equations.

The investigations in recent two decades have demonstrated the global sea level rise which is much more related to climate change phenomena and its impacts. In this study the impact of climate change on sea level rise at the southern coastal line of Iran is evaluated. The climatic output data of a GCM (General Circulation Model) named CGCM3 under climate change scenario of A1b was used. Among different variables simulated by this model, those of maximum correlation with sea level changes in the study region and least redundancy among themselves are selected for sea level rise prediction using stepwise regression. Two models of Discrete Wavelet Artificial Neural Network (DWNN) and Discrete Wavelet Adaptive Neuro-Fuzzy Inference system (DWANFIS) are developed to explore the relationship between climatic variables and sea level changes. In these models wavelet is used to disaggregate the time series of climatic variables as well as sea level data into different components and then ANFIS/ANN are used to relate the disaggregated components of predictors and predictands to each other. The results of this study show a significant increase of sea level in future under climate change impacts which should be incorporated in coastal areas management. The selected model (Anfis-Haar), which had a high performance index, showed that the sea level changes from 48 centimeters in the west of the Persian Gulf to 16 centimeters in the east of the Oman Sea. The changes in shallow and enclosed waters appear to be greater than other parts of studied area.

Power relations were changed in Iran during the 1980s and 1990s due to the occurrence of the Islamic Revolution. Controversial sign systems created around power relations in revolutionized Iran and affected the social life of children can be identified. The paper deconstructed sign systems and the semantic contention of them in the child and adolescent TV programs of IRIB in two decades after Iranian revolution using the political framework and cultural theory of the child in the Pearce semiotic method, so that the hegemonic identity discourse of each decade would be extracted. The findings showed that during the 1980s, Islamic revolutionary symbols dominated the anti-consumerism, simplicity, and social solidarity within family and educational relationships. The sign systems social implicit area, by instilling a revolutionary identity in conflict with “Other” (the West), prepared children to accept authoritarian relations based on domination. And in the 1990s, overcoming the modern sign system vs traditional sign system, eliminate the patriarchal authority and dominated a relationship with the logic of dialogue on the system of family relations. The audiences’ identity was floated on the pivot of objectivity and subjectivity due to contradictory conception and made it impossible to achieve the concept of childhood.

Typically, management and operation of wastewater treatment plants are based on comparison of the effluent quality with the defined standard values. Under this approach, only after the occurrence of a failure, the problem in system performance is recognized. In the present study, a new methodology is proposed to predict the wastewater treatment plant performance as well as its units, based on the inflow characteristics. For this purpose, first, the wastewater treatment plant simulation model is developed. After that, the relative importance of each inflow characteristic on the performance of the system is evaluated. Then, performance indicators are defined. In the present study, the chemical oxygen demand (COD) and suspended solids (SS) removal efficiency have been used for this purpose. This process reduces the costs and risks of the system failure. The proposed methodology in this study was implemented on a real case study. The selected indices well response to the inflow variables (such as flow and SS). As a result, it is possible to estimate and check the total and unit performance of wastewater treatment plant with acceptable accuracy. Finally, it can be used effectively to adopt preventive policies for improving the performance of wastewater treatment plants and risk management.

The subject of this study concerns Urmia Lake which is one of the most valuable water habitats in Iran and investigation of crisis in the drop n of water level, significant decrease in the lake’s surface area and increase in its salinity.. In order to have better understanding of the processes that affect the lake's water level fluctuations and assess the contributions of every responsible parameter, System water consumption was designed. System water consumption was designed in The Lake Basin in the Vensim and the effects of each variable on the water level of the lake were evaluated using a set of different scenarios The findings suggest that in comparison to other variables, the operation of dams (26%) as well as an increase of water requirement (16%) by variables have played a role in reducing the input to the lake. Climate variables had an effect of 16% within the time span of 1999-2014. Although Hydrograph indicates the aquifer deterioration in some of them, the entrance to the lake water budget is negligible

The latest investigations have demonstrated the climate change is definitely happening. As the climate change strongly impacts the global temperature and rainfall, and their variabilities, it highly affects water resources, thus the environment, as well as agricultural and industrial activities. In this study, the climate change impacts on the Gavehrud basin runoff during the 2016-2099 periods was investigated using the outputs of the HadCM3 GCM model under the A2 scenario. The SDSM (statistical downscaling model) was used for the statistical downscaling of temperature and rainfall. For simulation of the future runoff using the downscaled data, HYMOD model was used. The HYMOD was calibrated using the DREAM model for considering its parameters uncertainty. The SDSM results indicated a considerable change in temperature and rainfall, in the future as compared with the historical time horizon of 1989-2000. The mean temperature increase in the future would be about 5% to 8.5%, while the mean rainfall decrease would be about 3% to 5%. The results of this study indicated that a 5% to 23% decrease in the future average runoff in comparison to the historical values.

The importance of water distribution networks in social health and their role in urban and rural public service has resulted in many studies on these networks performance. Most of the studies focused on hydraulic and qualitative aspects, while the environmental aspects are less considered. In this study, the environmental impacts of production, transportation and installation of Polyvinyl Chloride (PVC), High-Density Polyethylene (HDPE), Ductile Iron (DI) and Fiber cement pipes were investigated. Furthermore, considering specific trench for each pipe, environmental impacts of different trenches were compared in installation phase. In this paper, SimaPro 8 was used to evaluate the life cycle of scenarios. The results indicated that DI and PVC pipes have respectively the highest and lowest environmental impacts in the whole process of production, transportation and installation. The results of this study could be considered as a guideline in designing and implementing water distribution networks with the lowest environmental effects. In this paper, a part of water distribution network of Tehran is chosen as the case study to estimate the reduction potential of environmental impacts.

Recent years have witnessed a growing interest in the optimal operation of water distribution networks (WDNs) as a result of their enhanced quality and reliability with due regard for the economic limitations faced. For this purpose, the present study was designed and implemeted to realize the two objectives of minimizing disinfection costs and maximizing reliability of water quality in water distribution networks using the multi-objective form of ACO algorithm as the optimization method. Different system analysis methods based on DDSM (demand driven simulation method) and HDSM (head driven simulation method) were also employed to investigate and compare the effects of constant versus time-dependent chlorine injection and pump speed. Results indicated that, compared to the condition with constant parameters of chlorine injectuion and pump speed, great improvements could be achieved in enhancing the reliability of water quality and reducing disinfection costs by using variable speed pumps (vsp) and time-dependent chlorine injection regimes without the need for buster pumps. Comparison of the analytical methods employed also indicated that application of HDSM led to reduced chlorine injection costs and improved reliability of water quality.

In integrated water resources management at the basin level, integrated view of the system and taking into account the interactions between the various components is essential. System dynamic model is a management tools according this approach that in addition to describing complex systems of water resources provide the possibility of user involvement in the development model. This study have been done in Urmia Lake's basin with emphasis on the drop in the water level of Lake. In the present study, we tried to study water level behavior under the influence structure designs. For this purpose, a conceptual model was designed in Vensim model for Water Resources with considering variables that affect water balance equation in dams for estimation of the overflow of dams and environmental flows to the Lake. After calibration model, two scenario was designed to investigate the effect of any of the structural project, as well as water demand pattern in seven main basins. The results showed that structural projects in the basin have reduced 42% of the inflow to the lake of which approximately 26% related to the operation of the seven main dam and 16% in relation to agricultural development and enhance the operation of the basin's water requirements.

The design and upgrade of sludge treatment systems generally depend on the decision made regarding the appropriate system from among the options available. The selection process has become increasingly important and complex due to recent technological developments that have led to increased diversity in the available options which offer a wide variety of capabilities. The multi-criteria decision making method is one of the techniques recently developed which takes into account all the criteria involved in the decision making process. The Ghods Town WWTP in the west of Tehran located in the vicinity of residential areas has given rise to claims by citizens due to the odors emitted by the sludge sand drying bed، which justifies the replacement of the present sludge dewatering system. For this purpose، the multi-criteria decision making method based on the fuzzy synthetic evaluation method was used to identify the optimal sludge dewatering system appropriate for the WWTP under consideration. Furthermore، weighting of the subjective (social، environmental، and administrative) criteria was accomplished using the analytical hierarchy process and the objective (i. e.، economic) criteria were weighted using the entropy concept. In this method، the triangular fuzzy membership function was also used to take into account the uncertainty associated with each of the decision making parameters. Based on the results obtained، the belt filter press dewatering system and the filter press were identified as the preferred solutions.

In the water resources planning and management، rainfall is considered as the main representative factor of region''s hydroclimate system. There is a high level of spatial and temporal variability in rainfall events. Rain gauges are used for precipitation measurement in different points of the region. Due to limitations of rain gauges development، it is impossible to measure the exact distribution of rainfall over an area، so it is needed to select the optimal number and locations of the rain gauges in a region. There are several factors that affect the optimal number and location of stations، thus، development of an optimization model for development of rain gauges network is necessary. In this study an optimization model is proposed for determining location of the rain gauges considering the transformation entropy and the regional rainfall estimation error. In this model، the points with the minimum transformation entropy and the maximum rainfall estimation error are considered as candidates for development of new stations. The results of two considered criteria are combined to determine the location of the new stations. Geogrpahic information system (GIS) is used to better represent the results of rainfall spatial analysis and explain results of the proposed optimization model. A sub basin of Karkhe basin in South West of Iran has been considered as the case study of this study. Results show that using new rain gauges which are determined to be 17 using the proposed approach could improve accuracy of spatial analysis of rainfall siginficiantly.

The education of engineers, who are aware of today’s challenges and future opportunities, plays an important role in economical and social development of different societies. The current engineering education system tries to increase professional engineering knowledge in related fields and does not consider the side effects of engineering activities which commonly impact the environment. This thinking structure, called the Newtonian paradigm is vertical thinking based on linear and sequential phenomena. In the Newtonian paradigm, the engineering education program is developed on the basis of maximum usage of available environmental opportunities and control of natural events. In time, the undesirable effects of this engineering paradigm on the environment become visible and also some signs of un-sustainability in engineering systems appear to make some problems in the long time performance of these systems. These impacts force the engineering education system to develop engineering knowledge and pay more attention to the environment. The holistic paradigm has been developed in response to these requirements. The holistic paradigm is based on parallel and non-linear phenomena. In this paradigm in addition to increasing professional knowledge, engineers are made familiar with the interactions between engineering activities and the environment. This way the maximum profit will be obtained from available opportunities and also the engineering activity impacts are minimized. In this paper the paradigm shift trend and its future vision in engineering education and its effects on the development of engineering systems as well as environment are discussed.

Hydraulic pressure is one of the most significant parameters in optimizing water distribution networks. Its simulation and estimation are essential tools in water distribution network management due to the significant effects it has on certain parameters of these networks. As a result of water losses to leakage, not all the inflow to urban water networks is consumed. Water leakage results in losses of supply, pressure, and capital investment. It also has adverse effects on water transfer capability, water treatment, and other elements in the distribution process. Furthermore, water quality problems could result from pollution at leak points. It is, therefore, necessary to estimate the amount of leakage at each point as a function of pressure.In this paper, artificial neural network as a powerful and flexible mathematical tool is used to model pressure estimation based on reservoir head, node elevation, water consumption, and the amount of leakage at a given point. Part of Tehran metropolitan water distribution system is modeled and the EPANET2.0 software is used to estimate the pressure variations in the network. Two different artificial neural network models, namely, a multi-layered ANN and a fuzzy logic neural network (ANFIS) are used for this purpose. The results are analyzed and compared with those from EPANET.