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Water distribution networks are one of the vital infrastructures of any country, which one of its main tasks is to deliver good quality water to consumers. These networks are always exposed to various types of threats, and since they are at the end of the water supply chain and are in direct contact with the consumer, the occurrence of quality failure in it can lead to irreparable health, life and social damages. The acceptable performance of water supply networks in terms of quality is dependent on operation and maintenance programs, and risk analysis and management can be mentioned as one of these programs. One of the main components of risk due to the occurrence of quality failure is the probability of failure. In this research, in order to calculate the probability of failure of the quality of water networks, at first, the factors affecting the occurrence of quality failure are identified and with the help of Bayesian networks, the probability of failure of the quality of each pipe is calculated. This work is done in four basic steps: preparing input data, training the Bayesian network, validating it and receiving the output results. In addition, by carrying out sensitivity analysis, four factors consist of pipe type, water pressure, water age and water velocity have been identified as the most effective factors on the occurrence of water quality failure in this area; which controlling them by managers and decision makers of water and sewage companies in the form of risk management programs, the probability of quality failure can be significantly reduced.

Paying attention to the conservation of water resources in order to prevent water crises is one of the most important duties of people in the community, including officials. In this regard, the most effective action is water demand management, for which there are different methods. One of these methods is pressure management in order to demand management, which can be used in normal operating conditions as well as in the event of water scarcity. On the other hand, in critical situations where the available water does not meet the total demand, policies such as intermittent water supply are adopted, which are associated with many problems. Therefore, an alternative method is needed to minimize the disadvantages of intermittent water supply,to meet the objectives of demand management and, at the same time is feasible, efficient, and economical. In this research, a combined simulation and optimization model is created by using EPANET2.2 and MATLAB software. With this model, the effects of adopting a water demand management approach using pressure management on the hydraulics of water distribution networks will be investigated. In this research, optimization is done in two approaches. In each case, a different objective function is defined and a genetic algorithm is used for optimization. The developed model has been analyzed on the WDN of Baharestan city located in Isfahan province. The results show that the model is able to reduce the average network pressure by 8 meters by finding the optimal location and adjusting pressure for pressure-reducing valves under normal conditions. Also, during water scarcity, it is able to distribute the available water among the demand nodes considering equity and justice principles. After imposing an 8% deficit on the network, without applying for a pressure management program, 8 demand nodes experienced a shortage between 15 and 30% and 19 experienced a deficit below 5%. However, after optimizing the pressure, only 3 demand nodes experienced a shortage between 15 and 25% and 6 nodes experienced a shortage of less than 5%.

Encouraging households to adopt residential water conservation behaviors, as an efficient strategy for sustainable water supply, has caught the attention of water demand management. However, the success of such policies depends on the voluntary acceptance of these measures by urban households. Considering the important role of psychology in explaining human behavior, the present research explored the key socio-psychological factors underlying the household adoption of WCBs and how these behaviors can be explained by expanding the theory of planned behavior via adding the habit variable to the TPB’s main model. In the current study, which focuses solely on water curtailment behaviors (behavioral conservation), 343 Isfahan citizens participated. In this regard, a cross-sectional survey was conducted using a structured questionnaire, as a research instrument, and the structural equation modeling method was also applied for data analysis. The results revealed that, by adding the habit variable to the TPB's main model, the extended model can predict 75% and 51% in the variance of intention to adopt water curtailment behaviors and water curtailment behaviors, respectively. Based on the findings, the attitude and perceived behavioral control variables had a significant positive relationship with intention, whereby attitude had the most predictive power of intention to adopt water curtailment behaviors. Moreover, the habit and intention variables were significantly and positively related to water curtailment behaviors, of which habit was the most important determinant of behavior. However, subjective norm had no significant relationship with intention, and perceived behavioral control was not significantly related to behavior. Finally, policymakers are advised to develop and implement awareness-raising and education campaigns aimed at (1) creating positive attitude toward WCBs among urban households, (2) increasing their self-efficacy and self-confidence in performing these actions, and (3) improving and/or changing their water conservation habits in order to improve WCBs among urban households.

As the population and urbanization increase, policymakers consider urban water management more often; however, these policies can positively and negatively affect the urban water system. In recent years, following the increase in the water crisis in Isfahan province, pressure management has been applied to reduce access to water as a new water demand management policy in different cities of this province. The present study investigates the environmental effects of such policy in the new city of Baharestan (Isfahan province) during the 2018-2036 period, using a life cycle approach and different percentages of available water shortages. SimaPro software is used to conduct the life cycle assessment for processes such as network failure and energy consumption at the pumping station. The life cycle assessment is performed based on the conditions of the study area. The results show that significant part of the environmental effects in the water supply and distribution network is caused by network failures, which, compared to energy consumption, have many effects on most midpoint and endpoint environmental effects. So that the endpoint environmental effects of network failures are, on average, 2.2 times greater than that of pumping systems. The water distribution network and pumping system can minimize their environmental impact by implementing a pressure management policy. With pressure management, the endpoint environmental effects in both short-term and long-term scenarios are reduced by 14.7% and 20.2%, respectively.

According to the water scarcity in recent decades in Iran, long-term prediction of domestic water consumption is a beneficial approach in order to manage water demand and water supply in water distribution systems. Therefore, it is necessary to develop a model which is capable of demonstrating the complexity, uncertainties, and influences of various parameters on water consumption with high accuracy.  The increment of uncertainties in the forecasting period leads to apply probability methods such as Bayesian belief networks in addition to deterministic methods. This paper presents two Bayesian networks to predict long-term water demand in Neyshabour city. Furthermore, the efficiency of those models is compared to the Stone-Geary function; moreover, their sensitivity to the network structure and data categories is evaluated.

Separate sewer networks are designed and built to collect foul sewage from buildings and convey it to wastewater treatment plants (WWTPs). However, due to some holes and cracks on the pipes or unsealed pipe joints, a volume of ground or subsurface water that is placed in saturated or unsaturated zones intrudes sewers and WWTPs. In a condition that the wastewater level in the sewer stands higher than the groundwater level, wastewater leaks into the soil and groundwater and this phenomenon is called sewer exfiltration. Moreover, during a rain event, a part of the precipitation gets into the sewer system through the illicit connection of the yard drains and roof downspouts to the building’s lateral, and this part of the flow is called rainfall-derived inflow and infiltration (RDII). In this research, infiltration, exfiltration, and RDII were evaluated in a 16-month period to show the range of inflow and infiltration in the sewer network under the service of the South Tehran WWTP. Results show that the infiltration constitutes the major volume of the total inflow and infiltration. But the RDII leads to more operational problems due to its nature as an intense flow. After calculating the range of inflow and infiltration, results show that the average infiltration rate that entered the WWTP in the year 2014 was 0.0175 L/s/ha that is much less than the values mentioned in Criterion No. 118. Furthermore, total inflow and infiltration in five hours of the study period crossed the upper limit of the inflow and infiltration range (0.6 L/s/ha) in Criterion No. 118 that shows the high percentage of illicit connections in Tehran and a high volume of rainfall that enters the sewer network. Accordingly, the inflow and infiltration range in the Criterion No. 118 seems to be an unsound range and it needs some revisions.

Water demand management policies (WDMPs) are being proposed as a solution to water scarcity. Applying any of WDMPs can have far-reaching consequences even on the urban infrastructures like wastewater systems. However, studies on the effects of WDMPs often focused on the water sector, and there is a research gap in the wastewater section. Therefore, in this study, the impact of the application of WDMPs on sewage systems from a social point of view has been evaluated during different scenarios of demand reduction. For this purpose, the Social Life Cycle Assessment (SLCA) method, which is a subset of life cycle thinking, has been used. In this regard, Baharestan city (located in Isfahan province) is selected. The groups (stakeholders) affected by the social effects of WDMPs on wastewater systems have been identified and their characteristics have been determined. Stakeholders are social and local community, workers and consumers. Then, by compiling a questionnaire and using the opinion of experts in this field, the Analytic Hierarchy Process (AHP) method has been used for scoring. Then, taking into account the intensity of the effects of each indicator in each scenario, the social score of all scenarios is obtained. The results show that social and local community has the biggest weight than other stakeholders (wight of 0.45), and safe and healthy living condition is the most important indicator of it. Also, the scenario that has the least decline in water consumption and sewage production is socially better than others.

Ecological and social science researchers have long faced the challenge of modeling the intrinsic complexity of socio-ecological systems. A popular approach to understand and investigate these systems is agent-based modeling, which has been used not only in ecological sciences but in many other disciplines over the years and has become a widely used tool nowadays. Despite the importance of this modeling approach, there was no standard protocol to make and present these models by 2006. Hence, several expert modelers who covered a wide range of areas in ecology suggested the ODD protocol (Overview, design concepts, and details) as a standard for describing individual-based models (e.g., agent-based models) in 2006. After that, some providers of the first version of the ODD protocol have developed an updated version of this protocol in 2010 to resolve problems and ambiguities of the original version, as an alternative for the previous version, by reviewing research that used this protocol. Then, considering the fundamental role of human decisions in agent-based modeling, a new version of this protocol named ODD+D was introduced in 2013, specifically for this modeling approach. The purpose of the ODD+D protocol was the development and modification of the ODD protocol to create a standard for describing agent-based models so that it can consider human decision-making within itself. Due to the importance of applying this protocol in the structure of agent-based modeling studies, the present research introduces the ODD protocol, reviews its evolution over recent years, and addresses the detailed description of different versions.

Simulating and understanding of abnormal conditions is one of the most important applications of hydraulic models of water distribution networks. Hence, existence of calibrated models is essential to network behavior realization. This process requires field data collection to improve model's performance by comparing predicted and actual data. Sampling from network has different constraints. Therefore the sampling design process is performed in order to optimize it, which includes different aspects of sampling, such as location, number and frequency. This paper focuses on pressure sampling nodes for hydraulic model calibration. To implement sampling design, first by sensitivity analysis, uncertainty of each nodal pressure is divided between model inputs.

In this paper, a global sensitivity analysis method, Sobol, is used which divides the variance of model into model inputs and their interactions. Then, two criteria for selecting sampling points are defined. The first criterion maximizes the entropy and magnitude of sensitivity values of each parameter for the set of sampling design points. The second criterion, by replacing number of points with sampling costs, follows minimization of sampling costs. To solve the integer multi-objective optimization problem, the multi-objective integer genetic algorithm called MI-NSGA-II is employed.

Investigating different scenarios demonstrates effect of parameter type on the position of selected points. In the meantime, similarity between the results of combinatorial and individual scenarios decreases from cases including roughness to cases involving demand. This indicates effective role of roughness in selecting points in combinatorial scenarios. Also, analysis of combinatorial scenarios suggests that parameter interactions are effective in selecting points.

The results showed that the developed approach offers good performance in selecting sampling points with different scenarios. The MI-NSGA-II algorithm has a good ability to find the solutions of the integer multi-objective optimization problem. The use of pressure driven simulation method is effective on the results of sensitivity analysis and sampling design.

Contamination of drinking water is known as a major threat of water security around the world. As contamination enters a water distribution network, it spreads rapidly into the network and poses health and safety risks to the community. Using a set of sensors to report the concentration of chlorine or any other chemical, useful observations can be made to detect, identify and manage pollution. Based on these observations, location, concentration and start time of contamination can be determined and decision makers can be informed. In this paper, a simulation-optimization approach is used to solve the problem of contamination source characterization in which the EPANET software is used as a simulator and the Genetic Algorithm is used as an optimizer. The model developed in this paper is implemented on EPANET example 3. Modeling of water distribution networks uses information as input data which can cause error in model simulation. Pipe roughness and chlorine deterioration rate are among these inputs. The model has been implemented to find the location, start time and concentration of inlet pollution and the effect of pipe roughness and chlorine deterioration rate on the model responses have been investigated. The pollution entry scenario is applied to the network and the model presented is accurate in finding the location and time of the contamination. As the variables increase, the model accurately estimates the location and time of entry of the contamination but does not have complete accuracy in estimating the concentration of contamination, which is calculated with standard deviation of σ = 4.8% -8.1%.

In recent years due to water resources scarcity and increase in water extraction costs, more attention has been given to water consumption; specifically, urban water consumption as a more sensitive and high priority demand with high costs of supplying. Accordingly the water and wastewater authorities are directed to modern water management methods including water demand management policies and water conservation. These practices and policies not only have widespread positive and negative effects in different aspects, but also by affecting the different components of the system, can make more severe and immense effects. Amongst the most important aspects related to such policies are the social aspect and the main stakeholders of the urban water management, i.e. households. Thus, the purpose of this paper is to address these different aspects by reviewing the requirements and obligations of the integrated framework in assessment of water demand management policies. To this end, firstly the importance and necessity of assessing the water demand management policies has been discussed. Then, different approaches for integrated environmental assessment and management have been introduced by demonstrating the main implications. Also, some illustrative examples are presented. Finally, the agent-based model is introduces as the integrated approach for investigating the micro-level social interaction and assessment of macro-level aggregated impacts.

Ensuring water security in the face of population growth and resource scarcity has posed a serious challenge for policymakers in urban areas and led them to water demand management (WDM) approaches. Water conservation as a key factor in WDM is an effective solution to the sustainable urban water supply that includes two categories: water curtailment behaviors and water-efficiency behaviors. Given that the voluntary acceptance of water conservation behaviors by individuals, understanding the psychological determinant processes of these behaviors is an important aspect in designing effective policies and interventions in this area. Therefore, the purpose of this study was to investigate factors affecting water conservation intentions and behaviors among Tehran citizens using the theory of planned behavior (TPB). The data collected using both online and offline surveys (N=820) in Tehran by a structured questionnaire, which its validity was confirmed by experts, and its reliability was confirmed by Cronbach's alpha coefficient. Data analyze conducted through the structural equation modeling. Based on the results, the TPB can explain 83% and 40% of the variance in water curtailment intentions and behaviors, respectively, and 57% and 37% of the variance in water-efficiency intentions and behaviors, respectively. The results also suggested attitude and perceived behavioral control affect the intention regarding both behaviors, but subjective norm does not affect the intention for both behaviors. In addition, the results revealed that both behaviors influenced by intentions and perceived behavioral control. Finally, based on the results, implications for improving residential water conservation and suggestions for future research are provided.

Water demand management policies have widespread positive and negative effects on various aspects and can affect the severity and extent of these effects by affecting various components of system. Also, the application of these policies to social systems, which are composed of adaptable factors with complex behaviors (indirect effects) and interact with each other on micro-scale, causes emerging phenomena at system-level (macro-scale). In addition to the complicates of inner nature of socio-ecological systems and urban water supply-demand cycle, the complicates of urban infrastructure behaviors also present another challenge in this area. Therefore, urban water system is known as a complex adaptive system that requires integrated evaluation and modeling of system complexities in different dimensions. So, this article reviews the two main concepts regarding evaluation and modeling of environmental policies, including urban water management policies, namely (1)modeling of complex adaptive systems and (2)integrated evaluation and modeling and the types of common approaches of them. By reviewing these concepts and previous researches in the field of urban water management, the interactive cycle and modeling process in this field is extracted. This paper begins with an introduction to the importance of urban water management, especially demand management, and continues with an overview of the basic requirements and concepts in the structure of assessment and modeling of environmental policies. The proposed framework is then presented based on past researches. At the end, agent-based modeling as a powerful tool in evaluation and modeling of urban water management has been investigated using the two approaches above.

Proper functioning of a sewage collection network whole depends heavily on its management plan. Prioritizing component inspection of these networks is also an important part of management plan and paying attention to it can greatly improve their performance. In the present study, after determining the factors affecting the structural deterioration process of sewers, the impact of each of these factors on their decision-making and inspection prioritization process is investigated. After defining the indices and determining how each index is scored, each of the indices is classified in the range of 1 (very good) to 5 (very bad). Subsequently, a deterioration model based on polynomial logistic regression was developed to estimate the structural status of components using defined structural indices and videometric data. In addition, hydraulic and environmental assessment indices of sewers were introduced, which classified the condition of sewers in the range of 1 (very good) to 5 (very bad). Finally structural, hydraulic and environmental indices are combined according to different scenarios proposed to prioritize for inspection activities. In the present study, a part of Tehran wastewater collection network was investigated. On average in all defined scenarios, the pipes are in excellent, good, average, bad and very bad condition with 0.2, 6.4, 44.1, 45.9 and 3.3% of the total length of pipes, respectively. According to the results of the sensitivity analysis on the index coefficients, the structural index was identified as the most effective index in the prioritization program and its precise determination should be considered.

In this research, intermittent water supply is optimized using pressure driven hydraulic analysis and particle swarm optimization algorithm with the aim of maximizing the uniformity of water distribution in the network and reliability. In the following, by calculating the resiliency as an efficiency criterion, system performance is evaluated. Obtain ed results from pressure driven hydraulic analysis and demand driven hydraulic analysis are compared. In this regard, the particle swarm optimization algorithm and the EPANET hydraulic analysis model are linked. Pressure driven hydraulic analysis is performed by applying some modifications on the hydraulic calculation process. The proposed model is evaluated on a sample network in several water shortage scenarios. According to the obtained results, the objective function (uniformity of water distribution) has higher values for the scenarios with lower water shortage, so that the maximum value is relevant to the scenario without water shortage. The values of the objective function for scenarios with pressure driven hydraulic analysis are 20% more than its values for scenarios with demand driven hydraulic analysis. By comparing the values obtained for system efficiency criteria it can be observed that the network resiliency and nodal resiliency for most of the scenarios with demand driven hydraulic analysis are more than their values for scenarios with pressure driven hydraulic analysis. This is because of the independency of nodal discharge from nodal pressure in demand driven hydraulic analysis that leads to unreal values for nodal discharges and therefore, hydraulic failure accrues rarely. The maximum value achieved for resiliency is around 99% which is relevant to efficiency threshold of 70% in nodal form. Uniformity and equity of water distribution between demand nodes and as a result satisfaction of stakeholders can be maximized by using optimization models. Employing pressure driven hydraulic analysis models makes it possible to simulate the behavior of water distribution networks realistically.

Effective strategies for optimal management of water distribution networks (WDNs) along with financial resources are clearly identifying design and performance parameters affecting the emergence of non-revenue water and reducing the impact of parameters. In this study, using references and experiences of experts in the field of WDN, the factors that are involved in the development of non-revenue water components were identified. Then, to collect the required information on the status of the parameters, officials’ and experts’ opinion were asked through questionnaires. Bayesian Networks (BNs) were used as a modeling tool so as to not only consider uncertainties associated to the lack of sufficient data and detailed information on non-revenue water components but also consider the probabilistic relationships between parameters. Finally, in order to analyze BN models results, a sensitivity index was proposed to prioritize parameters based on their impact. To investigate the usefulness of the proposed model, the area covered by District 4 of Tehran Water and Wastewater Company was selected as a case study. The results indicated that the probability that apparent losses, real losses and non-revenue water are high is 37.48 %, 35.04% and 32.2%, respectively.

Water distribution networks (WDNs) are complicated infrastructures which their construction, operation and maintenance have considerable costs. Since most of the variables effective on the design and operation of WDNs cannot be computed and achieved accurately and definitely, uncertainty subject should be considered as an inseparable issue in the calculation of these networks. In this study, using the fuzzy logic concept and genetic optimization algorithm, the impact of uncertainties of input variables (nodal demands and pipe roughness coefficients) on the results of hydraulic analysis of two sample networks have been examined. In this regard, first, the fuzzy membership functions of input variables have been determined and by considering the simultaneous impacts of these variables' uncertainties, the output variables of hydraulic analysis have been calculated more accurately. Afterwards, variables of pressure, velocity and energy loss have been considered as representers for evaluating the hydraulic performance of network elements (nodal demand and pipes). In order to calculate the hydraulic performance indices of these elements, after analyzing the network based on the pressure driven simulation method, penalty curves defined according to the available standards, have been employed and the obtained results have been compared to the results of the demand driven simulation method. In addition, a new relation for combining the performance indices of network elements and obtaining an index for evaluating the total pipe performance and calculating the total hydraulic performance index of network has been introduced. According to the obtained results, slight uncertainties in the input variables of hydraulic analysis lead to high uncertainties in the outputs of the hydraulic analysis of WDNs. Meanwhile, velocity in pipes more than nodal pressures are affected by the uncertainties of input variables of hydraulic analysis. Also, implementing the pressure driven simulation method in performance evaluation of WDNs in their operation period leads to more reasonable and real results. For instance the total performance of network was 0.56 for 9-loop network and was 0.26 and 0.59 for 2-loop network, respectively, based on demand and pressure driven simulation methods.

Having a reliable rehabilitation plan with sufficient operational data is crucially important for the operation and maintenance of a water distribution systems. This research was conducted to develop a prioritization model for planning the rehabilitation of pipes in water networks when minimum structural data is available. To accomplish the main objective of the study, WDSR-Min model with Fuzzy TOPSIS technique capability was used to prioritize the pipes rehabilitation. The proposed model was used for the prioritization of pipes rehabilitation in a two-loop water distribution system. The prioritization of pipes rehabilitation were evaluated under two methods by using: 1) the pre-defined template of the WDSR-Min model, and 2) the template consistent with the conditions of the study area. The results showed that the rehabilitation plan obtained from WDSR-Min was aligned with the real needs for rehabilitation in the water network pipes. Furthermore, it was found that to prioritize the pipes rehabilitation it was preferred to localize the model criteria for the conditions of the study area, while to determine the pipes rehabilitation strategies the use of the pre-defined template of the WDSR-Min model was preferred. Using the proposed model in this work makes it possible to determine the prioritization/strategies of pipes rehabilitation using the minimum structural data of water distribution networks and independent of operational data.

  Probabilistic prediction model is obtained by development of spot prediction model. Unlike definite prediction, probabilistic prediction provides an amplitude of probable amounts for water demand. It is clear that there is more trust to amplitude values in decision making process. Probabilistic prediction of water demand is calculated through the distribution of uncertainty in independent variables by water demand model and production of a probabilistic distribution function for water demand in the point of interest in future. Looking for the probabilistic distribution allocation, Monte Carlo simulation process is used to develop probabilistic prediction of water demand according to the spot model by using Stone-Geary utility function. For each repeat in Mont Carlo simulation, a value of allocated distributions to each descriptive variable is used randomly. In this research both methods of determination of probable density functions consist of analyzing the past information and other experiences are used. Normal and uniform distribution functions were used because of their easiness in determination of parameters whenever their real distribution is not clear or it cannot be determined easily. To apply uncertainty on independent variables used in prediction of domestic water demand consist of per capita real income, the real price of water, stock prices of goods and services, the average maximum temperature and the number of literates, the best distribution of their monthly values, resulted from probabilistic distribution function, were used as the entrance of water demand function and the outputs obtained as the monthly water demand. For validation of water demand prediction model, the predicted values of water demand was compared with its real values in a few periods. In this research the LARS-WG micro scale statistical exponential model was used to predict the annually maximum temperature.
Neyshabur city, located in Razavi Khorsan province, was selected as a case study and the statistical society of domestic water branches was investigated. The required information was obtained from its subsidiaries annually function report and statistics of meteorological organization.
Independent variables which were used for water demand estimation are per capita real income, the real price of water, stock prices of goods and services, the average maximum temperature and the number of literates. The best distribution was selected by applying distribution functions on the value of variables, considering results of the Anderson test, selecting the minimum Anderson multiplier and attending to the others studies and experiences.
The final model for long term water demand according to the Ston-Geary utility function is as equation 1:(1) t=1,…, 120 
MP: is the average price of water (Rial)
I: is the per capita income of consumer (Rial)
PO: is the stock price of goods & services in Razavi khorasan province
Perc: is the amount of per capita consumption (m3)
E: is the number of literates
MT: is the average maximum temperature
U: is the disturbing element
Discussion of results and Calculated elasticity of price, income, intersecting, maximum temperature and number of literates by considering their average values in investigated time periods for Neyshabur city are presented in Table 1. Table 1. Calculated elasticity of water demand for Neyshabur city
Price Income Intersecting Maximum temperature Number of literates
-0.117 0.195 -0.078 0.054 0.402 Table 1 shows if the price of water increases one unit, it will result to decrease of just 0.117 unit in water demand that indicates the possibility of using pricing policies for decreasing water consumption. Relatively low income elasticity (0.195) shows the small share of water in the family income. Negative intersecting elasticity indicates that water is a complementary good. Temperature elasticity is positive (0.054) that notes the tendency of using water by temperature rise. In this research the elasticity for number of literates obtained equal to 0.402. So one percent increase in the number of literates will result to 0.402 percent increase in water demand.
To assess the accuracy of the model the per capita water demand was predicted by using independently observed variables for the period of 1997 to 2008 and the results were compared with observed information that showed a good match. Also results of RMSE and MSE tests for assessing the accuracy of the models was 0.22 and 0.12 respectively that emphasizes on acceptable accuracy of the model.
After finalizing the model the per capita water demand of Neyshabur was predicted by the spot method and summary of results are showed in Table 2. Table 2. Summary of the per capita water demand prediction by spot method.
Unit Year Percentage
changes Average of yearly changes
2008 2011 2016 2021 2026 2031
M3 51.18 53.35 60.06 66.03 71.93 79.31 48.6% 2% Finally the per capita water demand was predicted for Neyshabur through the probabilistic model and summary of the result is presented in Figure 1.   Fig.1. Comparison of the observed values and 90% confidence interval of the annual per capita water demand forecast. As it can be seen in Figure 1 the annual amount of predicted mathematical expectation for the per capita water demand in year 2031 is calculated equal to 80.36 m3 which shows 50% increase in comparison with year 2011. The average annual increase in water demand is about 2% which is consistent with the results of the spot prediction model. For year 2011 the defined confidence interval for water demand has obtained between 48.34 and 58.36 m3 averagely. While for year 2031 this range has grown and broadened to 67.66 and 98.64 m3. Furthermore, probability function shows 90% confidence interval for all probable predictions with considering uncertainty of independent and explanatory variables.

In this research, Fault Tree Analysis (FTA) with fuzzy and crisp approaches were used to assess the risk associated with the performance of water treatment plants. The fuzzy logic was used to consider the uncertainties in expert opinions and the nature of threats. This modelling approach was implemented as a case study in Jalaliyeh water treatment plant in Tehran. One undesirable event in such structure was improper water quantity and quality. The results of this case study showed that probability of treatment plant failure under fuzzy and non-fuzzy methods are 19% and 10%, respectively. The risk treatment plant failure was found to be within the low to medium range. For risk assessment, multiple components were found to influence the failure of treatment plants. Our evalutation showed that the following items were ranked as highest to lowest to influence the treatment plant failure: inappropriate tank design, power equipment failure, failure of transmission line, and inadequate repair and maintenance of the pumps.

Considering the importance of sufficient pressure in supplying demand in water distribution networks, it is necessary to study the factors affecting pressure variation, that the roughness of pipes directly affects the pressure of nodes. Therefore, the study of factors affecting the change in roughness coefficient (Hasen-Williams) in water distribution networks is important. Pipes diameter, age and corrosion are among factors affecting the change in the roughness coefficient of pipes that are evaluated in this paper. The roughness coefficients were plotted against each of the above mentioned factors, and the approximate relations of the roughness coefficient was obtained by fitting to the obtained graphs. Finally, by combining the relations obtained, a general relation is obtained for the roughness coefficient. Also, in this paper, the cast iron pipes, for which laboratory data is available, were used to obtain a mathematical relationship.Then again, instead of using the roughness coefficient of new pipes in analysis and design, the roughness coefficient for the end of the design period was used, taking into account the effective factors mentioned.To evaluate the results of the proposed method, a two-loop network was investigated in two common and real situations. The results showed that if the roughness coefficient of new pipes at the end of design period is used for designing, there will be a save of about 50% in cost of pipes, but then the network pressure at the end of design period will be reduced by more than 25%. Therefore, in order to ensure that there is sufficient pressure and demand satisfaction throughout the design period, it is necessary to accept an increase in the cost of network implementation at the beginning of the project.

Various reliability indices have been defined by researchers for the water distribution networks. Due to the complexity and heterogeneous nature of distribution networks, results of indicies can vary substantially and municipalities have hard time to select the most practical indicies for their networks. This study was undertaken to develop a new method for identifying the best reliability index by considering various factors including the appropriate sensitivity to changes in network parameters, the appropriate shift in extreme conditions, the capability in covering critical condition, hydraulic condition, and water quality reliability. To accomplish the objective of the study, several water distribution networks were evaluated under multiple scenarios and the optimum reliability indices were verified with an example real water distribution network in Ahar. Controlling parameters included in scenario analysis for network reliability indices include: minimum, maximum and optimal pressure, residual chlorine in nodes, velocity in pipes, nodal pressure reliability, pipe velocity reliability, and nodal residual chlorine reliability . To evaluate the performance of defined index, a two-loop test (critical) were compared with the conventional single-lop test (normal). The performance assessment of indices obtained from this study showed that the index values ranged between 0.11 and 1.0, which indicate the normality and the appropriate sensitivity of the indices. Also, by increasing the residual chlorine of the reservoir, the network reliability index changed from 0.54 to 0.75 and then as the residual chlorine decreases in the distributon network the reliability index decreased back to 0.54. This appropriate shift in reliability index while changing residual chlorine in the network, cearly shows the the effectiveness of new method in determining the reliability indicies under extreme conditions. Also, the new method did not respond to the failure of some network components, as were evident with insignificant change in the indices values under critical conditions. From the results of this study generally can be concluded that the newly defined relability indices is an efficient way for evaluating the performance of water distribution networks.

Rivers are water resources which are exposed to different amounts of pollutants. Therefore having awareness of qualitative variation of rivers is necessary. Using water quality indices is one of the methods for analysis of water quality. In this study, kind and weight of the variables included in the valid national and international water quality indices are examined statistically. Then, the performance index curves of the variables are produced based on the various standards and guidelines. In the next stage, using the Delphi method 9 variables are selected as the effective variables for water resources in Iran and their weights are determined based on the analytical hierarchy process. Curves with high correlation coefficient are fitted to the quality values proposed by the specialists and geometric average function is employed for combination of sub indices and calculating the final value of the quality index. The value of the proposed quality index is calculated for the Karoun river and is compared with the other quality indices. According to the obtained results, interpretation of water quality in the Karoun river based on the presented new quality index differs from the other quality indices.

Investigation and research, which are essential for economic growth, are integral parts of industrial activities and also the basic needs of dynamic industries. In an efficient research, the process of study is always important and the industry faces challenges and obstacles such as opportunity lose and energy that was spent through it. Therefore, the optimization of the process and the way of research and also the agility of the related stages are necessity of a successful research. In this study, it is tried to investigate the process of research in universities of the country (case study: University of Tehran) and identify barriers of investigation and research in the field of water and wastewater. The purpose of this paper is to study the main and structural issues of the inefficiencies of research in advancing the goals of the industry. Some of these factors are lack of an effective research system, lack of dynamic linkages between industry and universities, lack of definition of scientific problems for universities, lack of effective knowledge management system and scientific exchanges, inadequate research credit, inadequate structure of education system and inappropriateness with the need of industry, the structure of government agencies, and so on. After reviewing and recognizing the disadvantages structure of the academic research system, appropriate solutions are found to eliminate defects and use the results of the research. It is attempted to make the proposed solutions, in spite of generalization, consistent and relevant to the research of active areas in the field of the environment, especially water and sewage.