عباس روزبهانی

One of the most important sources of water supply, especially in arid areas, is groundwater resources. The various climate and human crises have caused complexity in water resources systems, particularly groundwater. The evaluation of the technical efficiency of these systems is based on the integrated management of operational capability. The integrated approach of the DPSIR in the aquifer system can improve the efficiency of the equilibrium plan due to the critical state of groundwater resources. This approach can be applied by considering the four parts of the actuator, pressure, mode and effects to formulate proper utilization policy with consideration of compatibility with aquifer status. In this research, while proposing a unified DPSIR approach for managing aquifers, an appropriate compatibility policy was developed for optimal utilization with consideration of decision making at four operational levels. This integrated approach to the groundwater resources system for decision making can provide the right tools with minimal stress for the users and the government.

By using effective factors in the design of safe structures, it is possible to create a suitable level of protection for Nahaja fighter planes in the environment of future battles; in such a way that they are hidden and safe from detection and damage sensors and advanced weapons of the enemy. Therefore, in this research, the factors affecting the design of the safe structures of Nahaja fighter planes have been identified and explained with the approach of physical defense.

The type of applied-developmental research is a descriptive-case study method with a mixed approach. The statistical population of the study included all experts and experts of the military apparatus who are familiar with the topics of passive defense. Using purposive sampling method, 30 people were selected as the sample. Data collection tools included interviews, questionnaires, and standard documents whose validity was confirmed by content validity and their reliability by Cronbach's alpha.

Based on the data analysis, the most influential components of the independent variable are location; Related to territorial planning with an average of 4/533 and a variance of 0/315, and the lowest impact related to technical and engineering factors with an average of 4/1 and a variance of 0.83, the highest impact of independent variable components of architectural principles and techniques related to interior architecture design with an average of 47 4.4 and variance 0.38 and the lowest effect related to multi-purpose use with an average of 3.13 and variance 1.18, the highest effect of the component in the field of using electrical facilities with an average of 4.43 and variance 0.57 and the lowest effect related to using the fire alarm system with a mean of 4.33 and a variance of 0.56.

Failure to observe the factors affecting the design of safe structures of  Nahaja fighter jets with the physical defense approach, in addition to the vulnerability of these places during the threat, leads to irreparable damage.

One of the major consumers of water and energy sources is agriculture and evaluating the performance of irrigation systems to determine the efficient use of these two sources is one of the priorities of sustainable agriculture. In this regard, the present study has conducted a spatial analysis of water and energy consumption in Qazvin irrigation network. For this purpose, first, the dominant cropping pattern of the study area was extracted and then the water requirement was estimated for the products in the cropping pattern using CropWat 8.0 software. To estimate energy consumption, energy consumption in the sprinkler and drip irrigation systems, groundwater pumping, diesel fuel, labor, seeds, machinery (tractors and combines), chemical fertilizers, and pesticides for each available secondary field in the irrigation network was calculated. The results showed that the highest energy consumption in all secondary farms indirect energy consumption is related to diesel fuel with 40% of total energy consumption and in indirect energy consumption belongs to nitrogen fertilizer with 20% of total energy consumption. Also, in the energy used to pump water in irrigation systems at different heads required for pumping for crops in the dominant cropping pattern, alfalfa consumed the most energy with a value of 4811.44 Kwh / ha and corn consumed the least energy with a value of 1194.19 Kwh / ha. According to the results, the impact of diesel fuel, chemical fertilizers, and water pumping on energy consumption are high, thus controlling the consumption of these inputs would significantly reduce energy consumption.

The demand for freshwater is increasing, while the limited water resources are subject to over-harvesting, pollution, and climate change, which require improving water resource management to distribute it equitably and achieve It highlights the goals of sustainable development. A low-cost option to support better water management strategies is to develop models capable of predicting available water amounts, especially amounts related to precipitation and river flow. Climatic diversity and climate changes are basic assumptions for hydro climatological predictions. One of the remarkable aspects of this issue is the correlation between large-scale atmospheric-oceanic phenomena or Teleconnection patterns with hydrological processes on a local scale, and these patterns can also affect the inflow to the dams. This study uses three machine learning models, an artificial neural network, a Bayesian neural network, and an adaptive neuro-fuzzy inference system to predict dam inflow and evaluate their efficiency. For this purpose, 12 scenarios consisting of rainfall variables, inflow to the dam, and nine climatic indicators with a delay of up to six-time steps were designed to investigate the effect of using long-term models as predictive variables of the flow one month later in Amirkabir Dam. to be placed The analysis of the results of this research showed that the use of the Nino3.4 index with one-time step delay as well as the PDO index with two-time step delays can increase the accuracy of the model compared to the scenarios in which only station variables are used. to be According to the results, the Nino 3.4 index was found to be the most effective index on the inflow to Amirkabir Dam, and the scenario in which the mentioned index along with the rainfall and flow data of one and two months before was used as input, in all three The model recorded the highest accuracy. Also, the performance of the ANFIS model for the mentioned scenario (scenario 9), with RMSE and R2 values, equal to 5.69 and 0.79 cubic meters per second, respectively, was better than the ANN and BNN models, so the value of the R2 index for the best scenario consisting of station variables (scenario 5), it increased by 0.15 and the value of RMSE index decreased by 0.78 cubic meters.

In today's borderless global economy, on the international stage, places act as new actors. Globalization of the economy and increasing the technological changes pace are two important forces in geographic location competition which is essential to have people with the following characteristics: creativity, risk-taking and awareness of environmental opportunities in the field of land economy. On the other hand, the increasing importance of tourism businesses in economic diversification and livelihood sustainability, especially in local communities, has created various economic opportunities to meet these needs. Consideration of innovative tourism activities in the context of rural entrepreneurship development is one of the most important opportunities. Therefore, the present article investigates the tourism entrepreneurship space in the Saman District of Malayer County with the aim of analyzing the spatial reconstruction capability of tourism entrepreneurship in rural areas development. The method of this study was descriptive-analytical and applied. The statistical population of the study consisted of 100 furniture and carpentry business owners. A questionnaire was used to measure the reliability of the questionnaire ، using Cronbach's alpha test for tourism entrepreneurship variable (0.98). Data analysis was performed in SPSS 20 software. Findings showed that tourism entrepreneurship (sofa and inlay) was relatively favorable in 90% of rural areas and led to the growth of tourism entrepreneurship economic activities in the region. According to the results, the villages of Dehno and Dehnoavarzaman are capable of entrepreneurship spatial reconstruction and become larger business locations. Also, the results of the means comparison test showed that there is a significant difference (p <0.01) between the perception of entrepreneurs with different educational levels in terms of factors affecting the spatial reconstruction of entrepreneurship.

Nahaja, as an equipment-oriented force, needs centers of gravity and Resistant and safe infrastructure in order to be at the highest level of combat readiness to respond to any threat.The main purpose of the research is to develop physical defense strategies in Nahaja and answer the raised research questions using a mixed method and case study. The total statistical population is 65 people, of whom twenty people were known as experts of the community. Data collection was by field method using interview with experts, questionnaire and library method, and the reliability of the questionnaire, Cronbach's alpha, was 0.889. To do so, expertise approach was run to extract the environmental factors namely strengths, weaknesses, threats and opportunities. Drawing upon the David method, following that, the environmental internal and external factors were separated, and the effective variables and cyrrent status were determined Accordingly, based on the determined IFE and EFE, the current status compared to the desired one was defined, and by forming a SWOT matrix, physical defense strategies in Nahaja were developed. Ultimately, using the QSPM matrix and consideirng the priorities, "upgarding the physical quality through the development of local capacities using intelligent and integrative technical knowledge management with the aim of reducing the physical vulnerability of Nahaja" with a value of 7.90 was rated first.

The uncontrolled increase of population in the country, the limitation of surface water resources and the overexploitation of aquifers have caused irreparable damage to the country's natural resources in recent years. Integrated hydrological models have made it possible to analyze groundwater and surface water with high temporal and spatial resolution. The aim of this study is to understand the interactions of groundwater with surface water in the Shazand plain aquifer in Markazi province using the MODFLOW-OWHM model under the ModelMuse graphical user interface. In this study, SFR package is used to simulate river flow and its exchanges with the aquifer. The model is calibrated manually for September 2010 to September 2011. The simulation results of the model showed that Shazand plain rivers have a very small portion in feeding the aquifer and its discharge and the highest portion in feeding the aquifer in most months of the year is due to infiltration from rainfall. The highest discharge in the dry months of the year is due to wells exploitation and in the other months is due to the head dependent flux. Therefore, this study can be a strong basis for further studies to assess climate change on surface water and groundwater resources and water resources management strategies in the country.

Groundwater modeling is the foundation for quantitative analysis of groundwater resources, the successful assessment of which depends on its stable and reliable simulation. Because groundwater models are an approximation of reality, it is impossible to quite determine a system's properties through modeling or to mathematically describe the complex properties of a hydrogeological system. Therefore, inherently, all models have a degree of uncertainty, and as a result, the existence of uncertainty in the groundwater model sets managerial decisions in relation to it at risk of failure. The purpose of this study is to explain a method for quantitative recognition of groundwater uncertainty and how model uncertainty can be used as a tool to better realize the modeled system and provide the information needed to help make more informed decisions. A quantitative investigation of groundwater modeling was performed in Najafabad located in Isfahan province. Three conceptual models were created for Najafabad aquifer by different geological settings, recharging, and model boundaries. Conceptual models were developed in steady-state for 2018-2019 and calibrated using observational data. All models were validated using available water level data of 2018-2019. The models reliably simulated the water level in the aquifer. To select the best model, the model selection criteria (AIC, AICC, BIC, and KIC) was used. The results showed that model number 1 with the highest weight and the least uncertainty was introduced as the best model.

Given that global warming is a threat to human life on Earth, predicting future climate change is essential. One of the objectives of this study is to predict daily temperature and precipitation in the near future (2021-2040), using general atmosphere-ocean circulation (AOGCM) models and reduce their uncertainties. Therefore, in this study, first, among the studied models, 5 suitable models including HADGEM2-ES, MICRO IPSL-CM5A-LR, NOERESM1-M ESM2M-GFDEL were selected and downscale by LARS-WG method. Then, using two approaches of Raisanen weighting and observational mean temperature and precipitation (MOTP) were used to weight and ensemble multiple models. The results show that the maximum temperature increases in all months, with the highest temperature increase in the Riesen model in February and the lowest increase in October. In the MOTP weighting model, the highest temperature increase is in January and the lowest temperature increase is in August. The percentage of rainfall changes in June, July and August decreased significantly due to slight observational rainfall. In this study, the MOTP weighting method was chosen to predict climate variables in future periods due to having a higher R2 and the lowest RMSE as a better method in predicting climate data. Therefore, according to the results, it is expected that significant feedback in the water balance of the region will be due to the effect of increasing temperature and increased evaporation, as well as the potential for changes in atmospheric events and hydrology of the basin.

One of the factors that lead to uncertainty in the mathematical model of groundwater flow is the uncertainty due to the complexity of the conceptual model that results from the increase of model parameters. Considering complexity in groundwater modeling can aid in selecting an optimal model, and can avoidmodel uncertainty and misleading conclusions. The purpose of this study is to investigate the uncertainty of the complexity of the mathematical model of the Najafabad aquifer. In this regard, six conceptual models with five different degrees of complexity with the number of calibrated model parameters (4, 16, 20, 22, 26, and 26 parameters) with the same observational data in Najafabad aquifer located in Isfahan province in a steady-state and for the year 2018-2019 were developed and model selection criteria (AIC, AICC, BIC, and KIC) were used to evaluate the probability of models. The results showed that model#1 with four parameters, which is the simplest model, was selected as the best model and has the least uncertainty. But models 5 and 6, which are the most complex models, have the most uncertainty and the least level of confidence. Therefore, it can be said that in defining the conceptual model of an aquifer, determining the optimal number of parameters will decrease the uncertainty of the mathematical model.

One of the most important challenges of hydrological studies is the projection of precipitation variability in a basin in future periods. Atmospheric Ocean General Circulation Models (AOGCMs) can project this variability but in large-scale regions. Various versions of these models have been released, one of which is the CMIP5 series with about 40 dynamic models. In this study, the CCSM4 climate model has been used. The data output of this model is in 1 × 1 (Latitude× longitude) degree. To downscale the precipitation data of this model, the hybrid of two dynamic (WRF1) and statistical methods has been proposed. The study area is the Poldokhtar subbasin in the ​​Karkheh basin and rainfall data between 1996-2005 have been used. First, the precipitation data were downscaled by the WRF model from the range of 1 × 1 degree to 9 × 9 km, and then these data were converted to the range of 3 × 3 km separately by two methods a) hybrid and b) WRF. The results showed that the dynamic downscaling by the WRF model in the range of 9 × 9 km quite shows the precipitation fluctuations during the statistical period. In the 3 × 3 km range, the hybrid method performed better than the WRF method. Finally the results showed that downscaling of precipitation in this basin using both methods is associated with underestimation and should be accompanied by an bias correction method. As a result, by reducing the time and cost of dynamical downscaling of climate models, the findings of this paper can be of great help in making decisions about water resources management in the wet and dry years of the coming decades of a basin.

Improving the performance of water distribution systems in the agricultural sector is essential to increase arable crops production by considering surface water volume and energy consumption. Therefore, the main objective of the current research is to evaluate performance of practical alternatives in modernization projects in order to improve the performance of surface water distribution systems and to quantitatively evaluate their performance based on the water-food-energy nexus. The current operational management of the Rudasht Irrigation Network located in Isfahan, was simulated under normal and water shortage scenarios. Then the impact of two modernization methods including an improved manual operation and an automatic control system by using the Model Predictive Control (MPC) on the improvement of surface water distribution was investigated. In order to investigate the operational methods, eight indicators of surface water delivery, energy consumption, surface water productivity, food productivity, energy productivity, surface water economic productivity, energy economic productivity and food economic productivity were used. In the current status (Manual Method) under normal and water shortage scenarios, the values of water-food-energy nexus index were estimated 0.41 and 0.07, respectively. By improving the operational method to improved manual operation method, under normal and water shortage scenarios, the values of water-food-energy nexus index were estimated 0.46 and 0.09, respectively. The results of MPC method showed that this method has the best performance with 0.94 and 0.38 in normal and water shortage scenarios, respectively. The proposed evaluation approach can be used as an appropriate evaluation method to evaluate and prioritize modernization options of agricultural water distribution systems.

Urban treated wastewater or urban effluents as one unconventional water resource can be a continuous and controllable source for various uses. Simultaneously, the effluent from the wastewater treatment plant can carry chemical and biochemical contaminants and consequently expose the affected area to hazards and risks. The concept of risk analysis has helped researchers and project managers to assess the risks of treated wastewater applications in various uses to take appropriate action to reduce or manage irreversible effects on the environment and human health in advance. In this study, risk structures are created for use of treated wastewater in agriculture, landscape irrigation, artificial recharge for aquifer balance, and industry by considering environmental, social, economic, and technical criteria. Further, the effluent quality of 27 treatment plants has been evaluated. To calculate the risks, different hazards of treated wastewater applications are listed and hierarchically affect main and overall risk criteria to calculate the risks. The average overall risks of treated wastewater use in agriculture, landscape irrigation, artificial recharge, and industry are evaluated to be 29.7, 24.0, 24.3, and 26.0 percent, respectively. It is also worth mentioning that although the environmental risk of using treated wastewater in most treatment plants is low, but its social risk is high, which can be attributed to a lack of confidence in the quality of wastewater and low awareness of communities.

Utilization of groundwater resources in arid areas is an important factor in the development and landscape of the region. This has led to the use of different approaches to assess and determine the volume of groundwater resources. In this study, Bayesian network, which is a probabilistic network based on recorded data, was used to reduce uncertainties. The use of two single states of piezometers and a combination of piezometers in the estimation of aquifer hydrographs using Bayesian network was evaluated using HUGIN v8.3 software. In order to implement two simulation approaches with Bayesian network, single state simulation for each observation well and integrated mode simulation for five observation wells at the aquifer level were performed. The results of two simulation models for two years predicting the future trend of the aquifer indicate a high level of statistical indicators between observational data and simulation. The final results in the single method indicate an average explanation coefficient of 0.85 with an average error square of 0.42 and in the integrated method with an average explanation coefficient of 0.8 with an average error square of 0.25. The results also showed that the use of Bayesian method to predict groundwater level and aquifer volume is highly accurate and the use of a single approach to predict groundwater level in each observation well and integrated method in predicting aquifer hydrograph has good accuracy.

Unsustainable development and rapid urbanization have led to changes in the hydrological characteristics of watersheds, and the risk of flooding has been increased consequently. One of the solutions used for quantitative and qualitative control of urban runoff is green infrastructure and low impact development (LID) based approaches that have attracted the attention of many researchers. In this study, SWMM was used to simulate the rainfall-runoff process in region 1, district 11, Tehran. Six scenarios, including different combinations of several LID types such as Green Roof, Rain Barrel, Bioretention Cell, Porous Pavement, Vegetated Swale, and Dry Pond were developed. Then the SUSTAIN model was utilized to assess each scenario's performance. Optimal solutions were then obtained using non-dominated sorting genetic algorithm-II (NSGA-II), and a cost-effectiveness Pareto frontier curve was performed for all scenarios. Results showed that the selected solutions of scenarios one to six reduced the runoff volume by 53%, 4%, 66%, 72%, 31%, 34%, respectively. Scenario 4, with a combination of rain barrels, porous pavements, and vegetated swales with a runoff volume reduction of 72% and an implementation cost of $ 12.2 million, showed the best performance, comparing the other scenarios' corresponding optimal solutions. Scenario 6 also came in next with a 34% effectiveness and a cost of $ 7.1 million. The combined use of SUSTAIN and SWMM, in addition to the technical evaluation, helped to attain optimized, cost-effective solutions for developed scenarios as well. The results of this study can also help relevant organizations and decision-makers to design, evaluate performance, and implement costs of different LID scenarios.

The water crisis is one of the most important conflicts of the day, and Iran is also in the field of water resources from countries with tension. Following the drop in groundwater levels in aquifers, most of the country's plains have experienced water crisis and water scarcity and their groundwater aquifers have been limited. Among the water stresses, Hashtgerd Plain, which has been selected as the study area. In order to exit the plain from the aforementioned situation, water management should be undertaken with basic management measures, which requires the provision of water resources predictive tools through these measures, one of which is the Bayesian network; In this study, to create a water-borne water prediction model, the predicted variable, groundwater surface parameter in the following month and predictive variables, temperature, precipitation, evaporation, aquifer feeding, The discharge level of the aquifer and the groundwater level were considered in the current month. To reduce information uncertainty, two predictive approaches were used with categorized data (discrete data) and prediction with explicit data (continuous data), and by examining the precision of the pre- The aquifer nose by the two approaches referred to provides explicit precision approach to observational hydrographs. As a result, this approach has been selected as a superior approach for predicting groundwater level due to the application of management scenarios in which the values ​​of the coefficient of explanation 0.94 and the RMSE is 0.207. The approach used in this study can be used in other water resources stresses.

The occurrence of continuous water shortage as a natural hazard has dramatically impacted the country's performance of surface water delivery systems. In this research, drought risk analysis in surface water delivery systems in Roodasht irrigation network has been investigated. For this purpose, the streamflow Drought Index (SDI) has been used to assess the region's probability of drought. The consequence of drought was calculated by combining water distribution performance evaluation indicators, efficiency, adequacy, and justice with a simple additive weighting method (SAW) in five weight scenarios based on different management perspectives. Finally, by combining the probability and consequence of drought, the risk of this phenomenon in the agricultural water distribution system was calculated and analyzed. According to the SDI index, the results showed drought occurred in the monthly period with magnitude of -2.42 to 2.47, and in the annual period with magnitude of -2.54 to 1.65. The range of monthly drought risk values of the system in five weighted scenarios is as follows: evaluation perspective with emphasis on the opinion of the network administrator (0.668 to 0.804), With the emphasis on the beneficiary's opinion (0.636 to 0.803), the simultaneous emphasis of manager and beneficiary (0.647 to 0.802), emphasis on regional water opinion and provincial managers (0.684 to 0.804), and with emphasis on environmental considerations within the irrigation network (0.692 to 0.804). The obtained results of employing the risk analysis framework in both annual and monthly periods make the authorities present appropriate alternatives considering the magnitude and timing of the system's failure risk.

Nowadays, one of the solutions to meet the growing water needs and achieve regional balance is inter-basin water transfer projects. This study examines eight scenarios in order to evaluate eight scenarios of inter-basin water transfer from great Karun watersheds to the central plateau of Iran with the aim of supplying drinking water. Prioritization and evaluation of these scenarios were performed using four important and effective criteria (social and political risk, environmental and water resources risk, technical risk and economic risk) in inter-basin water transfer according to UNESCO criteria. Then, with the help of these criteria, ten effective basic events in inter-basin water transfer projects. Then, using the Fault Tree Analysis (FTA) and Fuzzy Fault Tree Analysis (FFTA) models, the failure probability of top event "failure of water transfer projects" for all eight scenarios were calculated. The results showed that water transfer from Behesht-Abad basin through Pumping and short tunnel from Behesht-Abad base flow for Isfahan province and khersaan basin - khersaan dam to Yazd and Kerman provinces with crisp and fuzzy failure probability of 0.65 and 0.61 as the eighth scenario, is the superior scenario. Due to the high probability of failure and in order to identify the factors affecting the occurrence of this failure, the basic events were ranked based on their effect in the failure of the top event using two indicators of BI and FIM. The results indicate the greater importance of socio-political and Environment criteria in the failure of inter-basin water transfer projects.

Declining the quality and quantity of water resources in recent years has threatened food security, health and the development of communities, especially in arid and semi-arid areas. The purpose of this study is to investigate the quantitative and qualitative conditions of surface and groundwater resources in the drinking and irrigation sections of Zayandeh Rood basin that faces political and social sensitivities in addition to the dangers of the arid regions of the Central Plateau of Iran. In this paper, using the integrated groundwater footprint (iGF) and for the first time integrated surface water footprint (iSF) indices as well as applying the Schoeller and Wilcox standards for checking quality of drinking and agricultural water, respectively, water resources status has been evaluated in 2006 and 2016. The average of integrated groundwater management index in Zayandehrud basin for drinking and irrigation purposes in 2006 is equal to 8.9 and 1.3, respectively and these values have decreased to 7.3 and 1.1 in 2016. Furthermore, in 2006 the average of integrated index of surface water footprint for whole basin in drinking and irrigation water were obtained 3.8 and 2.4, respectively and these values have improved to 3.3 and 2 in 2016. However, the results of these two years show a relative improvement in water resources in the Zayandeh Rood Basin, but they are far from acceptable conditions, especially in the drinking water sector, which requires serious attention of decision makers for developing of dynamic plans for sustainable development of this basin.

Since the majority of water resources is used for agricultural purposes, irrigation and drainage networks become important. Moreover, these networks are threatened by various natural and unnatural hazards that each one can affect the performance of the network. This research seeks to develop a risk analysis model of agricultural water distribution systems with the help of hybrid Bayesian networks. The proposed hybrid Bayesian model evaluates the risk of agricultural water distribution system and its components with the following inputs: inflow of water distribution system and its fluctuation, and the demand of water. The hazards which threat the system are identified and the model nodes are determined according to these risks and the system components. This model was investigated on the distribution of Roodasht irrigation network located in Isfahan, which is under the threat of improper performance of the ditch-riders and operational losses. The average risk value of the distribution system was 14.8% and the risk of components was calculated in the range of 0.01-49.2%. The hybrid Bayesian network model shows a good accuracy and performance in training and test sets with root mean square error of 0.07% and 0.08%, and coefficient of determination of 0.65 and 0.63, respectively. The proposed model helps operators and decision-makers to be aware of the causes and potential failures of the system’s components. This can lead to better planning for the allocation of irrigation water based on the anticipated risks in the occurrence of various hazards.

a significant portion of water is wasted during the conveyance and distribution process due to seepage and operational losses. To deal with the limitation of water resources, it is necessary to provide methods for reducing losses from canals. Therefore, the current study aimed to represent a method for estimating the minimum seepage and operational losses in earthen canals in order to improve water efficiency in agricultural water distribution systems using ant colony optimization algorithm.

In this research, the innovation and aim are to optimize seepage and operational losses in water distribution system using the ant colony optimization and the results of the algorithm are used to manage water resources, especially in agricultural water distribution systems. To achieve this goal, initially, basic information was collected from the Moghan plain canal and for the purpose of hydraulic flow simulation in the canal a simplified mathematical integrator-delay model was used. Then, in order to minimize seepage losses, a formula extracted from research history was applied. In addition, the seepage formula was calibrated and validated based on the measured seepage amount at each segment over the 23 km of the canal. Also, to optimize the purpose of this study, two single objectives, which they were minimizing seepage and water shortage delivered to each offtake in the main canal distribution process, respectively, were defined and adjusted in ant colony optimization algorithm model. Then, by linking the hydraulic simulator model, the estimation seepage formula and the Ant colony optimization model, it was possible to optimize the mentioned objective functions.

According to the results, optimizing the first objective function, in order to minimize seepage losses caused the reduction of total seepage amount during the 23 Km of selected research area, from 0.199 Cubic meter per second (seepage in the present condition of the studied canal) to 0.187 Cubic meter per second. Therefore, the reduction in seepage losses for the first objective function was 6 percent. However, the application of the first objective function has led to an increase in the amount of operational losses from 39.91%, which is the amount of current operational losses in the canal, to 45.55%. In other words, the operational losses from the first objective function compared to the current operational losses, increased by 5.64%. Accordingly, the total reduction of losses in the first objective function compared to the current losses in the canal was 0.39 percent. By applying the second objective function, the results show a reduction in operational losses from 39.91% to 27.91%, which indicates a 12% reduction in operational losses compared to the current situation of this type of losses. Also, seepage losses have increased from 0.199 cubic meter per second to 0.2168 cubic meter per second, which indicates an 8.9% increase in seepage losses compared to the current situation. Overall, the total losses reduction in the second objective function compared to the current situation is equal to 3.1 percent.

single objective functions of seepage and operational losses reduction results showed that optimization with the purpose of reducing seepage losses did not lead to a significant reduction in total losses in irrigation canals. On the other hand, in order to reduce operational losses, Ant colony optimization algorithm model by choosing optimum water depths could reduce the amount of operational losses to a considerable amount. According to the results, it can be generally acknowledged that modernization, renovation and rehabilitation projects of irrigation networks with the target of reducing losses and improving water use efficiency, if more focused on improving the operating process, more reduction of losses would result in agricultural water distribution system.

Urban treated wastewater is a useful resource for allocation to various non-potable reuses because its quantity and quality can be controlled and managed by humans, but it has its limitations. Improper use of these resources without treatment can lead to environmental and health risks and, as a result, can cause social dissatisfaction and sometimes economic problems. This paper examines the risks of limitations associated with the use of treated wastewater. Qualitative information of 26 wastewater treatment plants in the country was collected to create a proper database for risk assessment of using treated wastewater for agricultural and industrial application by taking into account the major factors such as environmental, socio-cultural, economic, and technical. For risks calculation, multiple risks associated with the use of treated wastewater were identified by reviewing various available publications and categorizing them according to the above four risk factors. Hierarchical networks were prepared to calculate the main and the overall risk. Bayesian networks were used to model risk-based structures. Bayesian relationships are causal and helpful in expressing the links of the nodes in a probabilistic way. Research results show that the risk of using treated urban wastewater in agricultural sector is generally higher than its application in industrial use, and hence it will make it more suitable and more acceptable for industrial use under current treatment. Bayesian risk-based agricultural and industrial structures were suitably modeled according to R2, RMSE, and MAPE indicators. The average values of the above indicators for the calibration of Bayesian model using treated wastewater in agricultural and industrial risked-based structure were 0.993, 0.202 and 0.637; 0.988, 0.980 and 2.731, respectively. From this study it can be concluded that Bayesian networks have a modeling capability in assessing the risk associated with the use of treated wastewater in agricultural and industrial sectors. The method presented in this paper can be used by the wastewater treatment plant managers and end users when assessing the potential risk of using treated effluent for agricultural and industrial applications.

the present study aimed at studying the relationship between job stress and personality traits and also if the effect of job stress on personality traits was moderated by social support.

The populations consisted of offshore personnel working in Iranian Offshore Oil Company (IOOC) in Kharg Island. 234 participants using convenience sampling answered three questionnaires (job stress, very brief NEO-form, and perceived social support of family-scale). Four main hypotheses using structural equation analysis were examined.

The findings showed a predictive effect between the personality traits and job stress except for openness to experience such that job stress had an increasing effect on neuroticism and a decreasing effect on extraversion, agreeability, and conscientiousness. Social support, on the other hand, as a moderator decreased the effects of job stress on personality traits except for openness to experience, extraversion, and agreeability such that it decreased neuroticism and increased conscientiousness.

the results generally revealed the predictive effects of job stress on personality traits and showed that social support, as a buffer, can reduce the effects of job stress on personality traits. The results were discussed based on the existing models on personality changes.

It is important to predict debris flood for reducing its damages. The aim of this study is the prediction of sediment concentration of debris floods and ordinary floods using bayesian network (BN) and artificial neural network (ANN) models in Ammameh, Navrood and Casilian basins which were located in Tehran, Gilan and Mazandaran provinces, respectively. Accordingly, average basin elevation (EL), average basin slope (S), watershed area (A), current day rainfall (R), antecedent rainfall (AR) of three-days ago and discharge of one-day ago were selected as input variables. Then, 32 scenarios were tested to determine the most effective factors on the sediment concentration of flood. For the scenario derived from all selected factors, indices R2 and MAPE in the test stage were obtained 0.97 and 8.55%, respectively. Assessment of the effect of different factors shows that the most effective factors on the BN model’s prediction accuracy are EL, R, PQ, A and AR one-day ago. Indices R2 and MAPE for this scenario were obtained 0.916 and 11.01%, respectively. It was selected as the best scenario because the least number of predictors and the highest accuracy. The most effective factors identified in this study can be used to predict debris flood in similar basins.

The main purpose of the study is the operational simulation of main irrigation canal and evaluation of water delivery and distribution locally, regionally and overall using adequacy, efficiency, and equity indicators and “Desirability of water delivery and distribution” indicator. To achieve this goal, the hydrodynamic model of Roodasht irrigation network’s main canal was developed. The results of the calibration and validation of the hydrodynamic model showed that the two processes were satisfactory. All available scenarios including normal, water shortages and fluctuations were considered for water delivery and distribution in different conditions. In the local assessment, the adequacy varied from 7 to 85%, and the efficiency in all scenarios was 100%. The adequacy, efficiency, and equity indicators in the regional evaluation varied from 6 to 89, 91 to 100, and 13 to 46%, respectively. The overall evaluation of the canal showed that the most desirable situation is related to a harsh fluctuation increasing with the adequacy, equity and efficiency indicators equal to 82, 23 and 91%, respectively. Calculation of the “Desirability of water delivery and distribution” indicator showed poor performance in all operational scenarios except harsh fluctuation scenario with 82% of which, the canal performance was estimated in fair level.