مجتبی اردستانی

Among natural disasters, flood is undoubtedly the most catastrophic hazard in the world. One of the basic strategies for reducing the damage caused by floods is to prepare a flood sensitivity map. Spatial prediction of the flooding probability using models created from spatial and historical data, which ultimately leads to the preparation of flood sensitivity maps is an appropriate solution for land management planners in different areas to prevent the occurrence of this phenomenon. In this research, in order to determine flood-prone areas, the hybrid model of adaptive neural and fuzzy inference and the metaexploratory optimization algorithm of imperial competition (ANFIS-ICA) and the hybrid model of adaptive neural and fuzzy inference and the metaexploratory optimization algorithm of particle swarm (ANFIS-PSO) are used.

The Zarine River watershed has an area of 4485 km2 and is located in the northwest of Kurdistan province between the longitude of 45°48ʹ30ʺand 46°48ʹ20ʺ east and the latitude of 35°42ʹ20ʺ and 36°23ʹ15ʺ north. The climate of the region is humid and the average annual rainfall is 480 mm. Locations of flood events were randomly divided into two groups: training (70%) and validation (30%). Various environmental factors (height, direction, slope, surface curvature, land use, lithology, rainfall, flow power index, distance from river and topographic wetness index) were selected as independent variables in the modeling and their digital layers were prepared. The ANFIS-ICA and ANFIS-PSO models were used in this research and their prediction results were evaluated based on the criterion (AUC) and the true skill statistic (TSS).

On the basis of these findings, in the validation stage, the model (ANFIS-PSO) with an AUC of 0.98 and a true skill statistic (TSS) of 0.89 had the highest accuracy. The results also showed that the factor of distance from the stream was identified as the most important environmental factor. In addition, ground slope and TWI were ranked second and third in importance, respectively.

Based on the results, the hybridization approach, which combines machine learning models and meta-exploratory optimization algorithms, improves the learning power as well as the predictive power of the model. The results of this research showed that the distance from the stream and the slope of the land are the most important factors affecting flooding. Based on the results and analysis, it can be concluded that machine learning models have a high capability for predicting flood potential. The flood potential maps prepared in this research can be very useful for managers and experts and can be used in planning flood prevention measures. Directing flood control facilities and measures in situations with a high flood potential will improve flood management from an economic and technical point of view.

Urban flooding is caused by the lack of capacity of the harvesting channel network and occurs when the amount of precipitation exceeds the network's capacity. One of the two main factors contributing to the aggravation of damage caused by urban floods is population growth and the expansion of urbanization, and the second factor is heavy rainfall caused by climate change, which plays an essential role in intensifying and accelerating the hydrological cycle and may change the amount and frequency of precipitation. This factor affects the probability of flooding, runoff volume, and peak flow. It is more visible in arid and semi-arid areas where rainfall usually occurs briefly but with high intensity. Urban flooding is a growing threat to urban infrastructure and public health, posing significant challenges to urban resilience and sustainability. One of the urban infrastructures that is of great importance is the runoff collection network. The increase of impervious surfaces wear and tear on the network. changes in the rainfall pattern due to climate change have increased the occurrence of urban floods and raised the importance of network redesign to minimize the system vulnerability.

In this research, the runoff harvesting network of ten districts of Tehran Municipality was redesigned and optimized. This area, with a population of 327,000 people, is located in the relatively dense fabric of the Tehran metropolis, and its area is 807 ha. Simulating the runoff collection network and checking the performance of the network by two indicators of vulnerability and reliability requires an accurate model with great details. For this purpose, in this research, SWMM version 5.1 software was used to simulate the runoff collection network. The study area was divided into 285 sub-basins to simulate the sub-channels in better detail. Then, information such as slope, area, and percentage of impervious space was introduced through ArcMap software version 10.3.1 as information under the watersheds. The sub-watershed width parameter was calculated by dividing the sub-watershed area by its most significant length using Q-GIS software and applied to the sub-basins. The LARS-WG model has also been used for the exponential micro-scale output of climate models. To simulate the network in the current or present situation, the historical precipitation information of the Mehrabad synoptic station was used, and to affect the network in future conditions, the precipitation information of the climate models of the sixth climate change report was used. Among the predictions of climate models, the most incremental changes in threshold precipitation were selected as a pessimistic scenario, and a system redesign was done to reduce vulnerability under this scenario.

This study was conducted to assess the performance of Tehran municipality's runoff collection network under current and future conditions. The SWMM hydraulic model was employed to simulate the network under various rainfall scenarios. Current conditions revealed a total runoff volume of 45.9, 51.14, and 59.7 thousand m3 for return periods of 2, 5, and 10 years, respectively. This runoff volume resulted in a vulnerability increase from 10.4 to 12.2% and a reliability reduction from 97.5 to 95.8%. To evaluate the network's performance under future climate change scenarios, the SWMM model was used with data from the IPCC sixth assessment report. Among the top five climate models, the one with the highest precipitation was selected as the pessimistic scenario. Simulation results under future conditions indicated a significant runoff volume increase, reaching 64.04 and 72.18 thousand m3 in 5- and 10-year return periods, respectively. This increase corresponded to vulnerability indices of 12.7 and 13.9% and reliability indices of 95.3 and 94.3% for the same return periods. To enhance the network's resilience, a genetic algorithm-based optimization approach was employed. Cost, reliability, and vulnerability index were considered optimization objectives with specific weighting functions. The algorithm converged to an optimal design solution in the 168th iteration, resulting in a 7.6% vulnerability reduction and a 98.1% reliability enhancement.

The vulnerability index in the return periods of 5 and 10 years is equal to 12.7 % and 13.9 %, respectively, and the reliability index is equal to 95.3 % and 94.3 %. After checking the network in its current state and future conditions, an optimal network redesign was done to improve system performance in both current and future conditions. For this purpose, the genetic algorithm was used for optimization, and the objective function consisting of cost, vulnerability index, and reliability index and the importance weights of each, were defined. Then, MATLAB software did the optimal network redesign by connecting the simulator and optimizer model. The results showed that in the 168th iteration, the algorithm reached its final answer of 0.3, which remained constant until the 300th iteration. Also, the optimal redesign has reduced network vulnerability by 7.6% and increased reliability by 98.1%. This research showed that with an optimal redesign and solving the current network problems, the system's ability to face future climate change threats could also be increased. Of course, spending the least money to achieve the best result was one of the main goals of this research. In future studies, it is recommended to use low-impact development tools along with optimal redesign to fix defects and improve the performance of the runoff collection network.

Today, fresh water sources are very important in human life. During the past years, population growth, development of industries, and agriculture have increased the need for water and subsequently increased the withdrawal from groundwater sources. This increase in withdrawal has occurred without considering the capacity of the aquifers. While logically, the exploitation of an aquifer should be limited to its dynamic storage, in most regions, the static reserves of aquifers have been used to a large extent, and it seems impossible to return these aquifers to their original state. The dynamic storage of the aquifer is actually a part of the storage volume of the aquifer, which has fluctuations, and by examining and determining these fluctuations, it is possible to estimate the permissible amount of exploitation of the aquifer. But the static storage of the aquifer, which is very important, is among the old and stable storage that has been stored for many years. The use of static aquifer storage causes events such as subsidence. The drying up and lack of water in many aqueducts, springs, and extraction wells across the country is one of the consequences of the overexploitation of groundwater resources. In the arid and semi-arid climates of Iran, factors such as climate change and water scarcity, along with overexploitation of water resources, especially groundwater resources, have caused the groundwater levels to decrease. In some areas, we are witnessing irreparable subsidence. As a result, it is necessary to manage and control the extraction of groundwater resources before the crisis occurs and reaches an irreversible level. In this regard, monitoring and controlling the condition of the aquifer using computer models is essential.

In the present study, the modeling and quantitative investigation of the groundwater condition of the South Mehyar-Dasht Asman aquifer in the Gavkhoni catchment area has been done by the MODFLOW 2005 model and groundwater modeling system )GMS 10.4.5( software. GMS software is one of the few with good performance and has been used in groundwater studies in many countries worldwide. This software simulate groundwater both quantitatively and qualitatively. The MODFLOW (Modular Ground Water Flow) model is used to simulates groundwater flow in aquifers with specific boundary conditions, assuming the necessary values for hydraulic conductivity and other aquifer parameters. The program allows the user to select only the modules needed to study the desired system for specific hydrogeological processes and activate or deactivate a particular part. These features have made the MODFLOW model the most efficient and accessible groundwater model today. For this purpose, the statistics and information from 15 years ending in 2013 of the Iran Water Resources Management Company and topographical information extracted from satellite data have been used to model the groundwater of the South Mehyar-Dasht Asman aquifer.

After running the model, the parameters of hydraulic conductivity, anisotropy, or HANI, RCH, SY, and parallel lines of the groundwater level were obtained. In the next stage, or the calibration stage, the model was calibrated by the parameters mentioned to minimize the difference between the observed water level and the calculated water level. In the sensitivity analysis stage, the calibrated value of the parameters is systematically changed to determine the model's sensitivity to the parameters. In this stage, it was found that the model received the most influence from the parameters of anisotropy and hydraulic conductivity. To validate the model and measure its accuracy, validation was done. The RMS error was 2.21, which is a good value, but for more certainty, the RMSE was also calculated, and its value was 23 %, which is very appropriate considering the long-term simulation period. Finally, the numbers extracted from the FlowBudget engine based on the calibrated MODFLOW model revealed that during the 12-month simulation period, a particular share of the aquifer's fixed storage was reduced on a daily average basis, resulting in an average drop of 7.5 m in the aquifer's groundwater level during this period. We see that the most significant drop is related to the eastern part of the aquifer.

In this research, the South Mehyar-Dasht Asman aquifer was simulated and modeled by the MODFLOW model and GMS software, and the groundwater level was investigated during the simulation period. The model was calibrated to reduce the difference between the observed and the calculated water level. The sensitivity analysis section also examined the influence of the model parameters. Validation was also done to increase the accuracy of the model's performance. The coefficient of determination or R-squared correlation was 0.9971, which seems to be a good number compared to other studies. The results showed that the water withdrawal is greater than the aquifer's recharge, and a specific volume of the aquifer storage is always reduced during the simulation period, which caused a drop of 7.5 m in the groundwater level. The groundwater level of the South Mehyar-Dasht Asman aquifer continuously decreases from the western part to the eastern region, and the lowest groundwater level is related to the east part of this aquifer. Declining groundwater levels, water shortage conditions, and overexploitation, increase the risk of subsidence, which is an irreversible event. To prevent this from happening, the amount of water taken from the aquifer should be proportional to its capacity, and control and management measures should be carried out on a large scale. Computer models and up-to-date methods help to maintain and manage these water resources as well as possible. Factors such as the dryness of the Zayandehroud River, excessive harvesting, and lack of water have led to the aggravation of the adverse environmental effects of the Gavkhoni International Wetland, and this has increased the importance of simulating the existing aquifers in this basin. Due to the fact that no study has been done on the simulation of the groundwater of South Mehyar aquifer-Dasht Asman and also the duration of the simulation period is 15 years, this research can be a basis for future studies and provide the possibility of comparison with other studies.

Finding the potential of groundwater resources is one of the basic principles in water resources management. The aim of this research is to determine the potential of groundwater using support vector machine learning (SVM) models as well as metaheuristic algorithms (hybrid support vector machine model and the bee metaheuristic optimization algorithm (SVM-BA) and hybrid model of the support vector machine and particle swarm optimization algorithm (SVM-PSO).

The factors of elevation, slope, aspect, topographic humidity index, distance from stream, drainage density, distance from fault, lithology, topographic position index, land roughness index, relative slope position and flow convergence index were selected in Bojnurd region. Information on the location of 359 springs was received from the regional water company. Random division algorithm was used to divide training points (70%) and validation points (30%). Based on the removal sensitivity analysis, the importance and contribution of the input variables in determining the groundwater potential were determined. The accuracy of the models was evaluated in two stages of training and validation based on the receiver operating characteristic (ROC) curve method.

The evaluation of the accuracy of the models based on the evaluation criteria of the area under curve (AUC) showed that the prediction accuracy of the hybrid model of the support vector machine and the particle swarm optimization algorithm (SVM-PSO) is 0.945 more than other models (SVM: 0.918 and SVM-BA: 0.932). Based on the results of the superior model, the high potential class and the very high potential class accounted for 7.75% and 38.66% of the area respectively. Among the factors, relative slope position with 14.5%, distance from the fault with 13.4% and lithology with 12.3% were the most important in predicting groundwater potential.

Based on the results of this research, the support vector machine model has a high performance, and two optimization algorithms, the bee metaheuristic and particle swarm optimization algorithm, strengthen the predictive power of the model. Also machine learning models can identify the relationship between the environmental factors and the water supply of the springs and determine their role by using the available data. The relative slope position factor was identified as the most important variable and the distance from the fault factor was considered as the second most important variable in the present study. The results of the research showed that the faults in the region play an important role in aquifer recharge, storage and flow of groundwater. The lithological factor was also introduced by the model as the third important variable in identifying the state of groundwater potential. In this research, by presenting the groundwater potential map, it is possible to plan and verify land use planning for the Bojnurd watershed.

The approach of water, energy and food correlation can be defined as an approach to evaluate the development and implementation of policies that emphasize the security of these things at the same time. The purpose of this research is to provide a method to analyze the relationship between water, food and energy in the crop production chain. Based on the proposed method and according to the amount of water and energy consumption, four indicators of water and energy consumption and water and energy productivity, and also based on these indicators, a combined index of water, food and energy nexus is proposed. This research has conducted on the Borkhor plain of Isfahan province and the MODFLOW model has used to simulate the watershed quantitatively and since the objective functions in this study are linear, multi-objective linear programming was chosen to solve the optimization problem. The goal of solving the optimization problem is 4 scenarios of water consumption minimization, energy consumption minimization, profit maximization, as well as water, food and energy maximization scenario. The results show that although each of the scenarios alone reflect the positive effects of reducing water and electricity consumption, but by using the scenario of combining water, food and energy, in addition to reducing water and electricity consumption, farmers' profits have also increased significantly, so that the amount of water consumption before optimization was 50 million cubic meters per year, but after optimization and applying the scenario of maximizing the correlation of water, food and energy, it decreased by 8% and reached 46 million cubic meters per year, and the amount of consumption Energy decreased by 9.7% from 13150330 kilowatt hours per year to 11867563 kilowatt hours per year and in addition, the profitability of the products before optimization was 6301966 million Rials, which after applying the scenario of correlation of water, food and energy with 21 The percentage of increase reached 8015264 million rials and on the other hand, with the continuation of the optimal scenario, the level of underground water in the state of maximizing the correlation of water, food and energy will decrease by 0.478 meters less than the existing conditions and and on the other hand, by continuing this trend in the long term, we will see a significant impact on the level of underground water.

In recent years, the changes in the intensity and frequency of precipitation and the occurrence of severe floods and droughts have prompted decision-makers to consider the effects of climate change in their plans. Due to the existence of impervious areas in urban environments, a more significant part of precipitation is convertedto runoff, and the changes in precipitation patterns resulting from climate change can affect the performance of drainage systems. On the other hand, with the change in precipitation pattern, the amount of pollutants washed from the surface is changed, and in this way, the quality of runoff is also affected. Nowadays, coupled atmosphere-ocean general circulation models (AOGCMs) are considered the most advanced and reliable tools for simulating climate change. Recently, a coupled model intercomparison project Phase 6 (CMIP6) hasbeen introduced as the latest version of AOGCMs, which can simulate future periods with high accuracy. The sixth assessment report evaluates the changes in climate variables by combining Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP) scenarios. According to this report, in addition to covering different climates, future scenarios should also consider the socio-economic aspects of development. The CMIP6 models have higher spatial resolution than the models of previous reports. A review of the research background in the assessment of climate change effects on precipitation and runoff shows that most of the studies have been conducted using the models and scenarios of the fifth and earlier reports, and only a few of them have included the scenarios of the sixth report in their evaluations. In this regard, our research evaluated climate change effects on urban runoff based on the CMIP6 models’ predictions.

District 10 of Tehran municipality is selected as the case study. This region is located in the south of Tehran and has an area of about 800 ha. Due to its high population density, lack of enough green space, and a high percentage of impervious areas, runoff management is a priority for this region. Moreover, the presence of agricultural land highlights the need for runoff quality management in the study area. The MehrAbad synoptic station is the nearest to the case study, and its observation data during the base period is gathered for evaluating the changes in hydrological variables under climate change. For implementing the methodology, different CMIP6 models were first assessed, and those with high performance in precipitation prediction in the historical period were selected. Their projections under SSP1-2.6 and SSP5-8.5 for the future (2021-2050) were downscaled using the LARS-WG model. Then, the statistical method was employed for disaggregating the LARS-WG’s daily output into 6-hour design precipitation. In the following, maximum and minimum values of precipitation were determined as optimistic and pessimistic scenarios, respectively, and the stormwater management model (SWMM) was implemented for simulating the runoff under these scenarios. The SWMM subdivides the watershed into sub-watersheds and utilizes three primary processes for runoff quality and quantity simulation. First, generated runoff is calculated by determining the hydrological characteristics of the sub-watersheds in the hydrologic process. Then, the canals route runoff to the outlet using a hydraulic process. In the quality process, the runoff quality is simulated using build-up and wash-off equations. In our research, the study area was subdivided into 84 sub-watersheds. Changes in runoff volume, peak flow, and total suspended solid (TSS) concentration at the watershed outlet were evaluated under climate change. Correspondingly, for assessing the performance of the drainage system, the changes in the flooded volume of the system were quantified.

According to the results, in all models under SSP5-8.5, monthly precipitation will increase in January, February, and March and decrease in August and September. Also, under SSP1-2.6, the precipitation trend is predicted to fall in September. The highest increase in precipitation compared to the base period is related to August under SSP1-2.6. In addition, with a decrease of 37.4 %, the highest reduction in precipitation is associated with February. The most evaluated prediction uncertainty is related to August under SSP1-2.6. This month, precipitation changes range from +226.31 to -18.34 % compared to the base period. Also, predictions on an annual scale do not show a specific trend. The changes in annual precipitation vary from a -9.8 % decrease to a 5.4 % increase compared to the base period. Then, by analyzing the 6-hour rain, the predicted values of HADGEM3-GC31-LL and CMCC-ESM2 were identified as the highest and lowest values, respectively. The 6 h rain with 5 and 10-year return periods under the pessimist scenario will increase by 31.4 and 26.8 % and decrease by 2.5 and 11.3 % under the optimistic scenario, respectively. The results of performing SWMM under a pessimistic scenario showed that in the return periods of 5 and 10 years, runoff volume would increase by 25.2 and 20.7 %, and TSS concentration will decrease by 21.4 and 18.2 %, respectively. Besides, in this scenario, the flooded volume of the basin increases to 42.12 %. Performing SWMM under an optimistic scenario revealed that with the reduction of precipitation compared to the base period, in the return period of 5 and 10-years, the runoff volume will decrease by 2.2 and 8.3 %, and the TSS concentration will increase by 2.5 and 10 %, respectively.

Performing SWMM under an optimistic scenario shows that with the decrease of 6-hour design precipitation, the quantitative parameters (runoff volume and peak flow) decrease, and TSS concentration increases at the watershed outlet. Furthermore, under the pessimistic scenario, quantitative parameters increase, and TSS concentration decreases with the increase in precipitation. More examination revealed that despite the decline in precipitation, the number of flooded nodes remained constant under optimistic scenarios indicating the drainage system’s vulnerability even under base-case rain and a little less. Moreover, the increase in flooded volume and the number of flooded nodes under the pessimistic scenario make it necessary to utilize management strategies to improve the runoff collection systems’ performance under climate change. In this regard, low-impact development (LID) practices can be used as a climate change adaptive approach in future works.

Estuaries are very important aquatic systems due to importing/exporting large amounts of organic and inorganic materials from natural and anthropogenic sources to seas.

In the present study, suspended particulate matters (SPMs) were collected from Navrud River in to laboratory and sequential extraction procedure was conducted to determine element concentration. Adsorption and desorption of heavy metals (Cu, Zn, Pb, Ni, and Mn) was determined under the effect of various parameters (Salinity, DOC, pH and Nitrate).

Based on the results of adsorption and desorption testing, when SPMs enter estuarine mixing zone at different salinities, Cu, Ni and Zn adsorbed to SPMs by 6.41, 3.03 and 2.09, respectively. Mn and Pb desorbed from SPMs by 97 and 2.09 ppm. Base on cluster analysis, Nitrate and pH dominate the adsorption and desorption of Mn and Pb during experimental blending. Also, salinity and dissolved organic carbon control adsorption and desorption of Ni and there was a high correlation between this element and salinity and DOC.

Water resource managers will make better decisions with more accurate information, the actual amounts of heavy metals transported by rivers to the sea are different from those taken for absorption and desorption. Therefore, the absorption and desorption of heavy metals in the estuary is of great importance due to the possibility of different salinities.

Considering the effects of pollutants of industrial origin, such as heavy toxic metals-containing wastewater, on rivers and surface waters and the importance of their removal, in this study, the preparation, characterization and evaluation of zinc oxide nanophotocatalyst based on magnetic organic-metallic frameworks (ZnO@IL-mSiO2@Cr-MIL-101), abbreviated as ZISM nanophotocatalysts, was evaluated in removing of lead (Pb2+) and arsenic (As3+) metals from aqueous samples.

This experimental study was performed using a ZnO-based nano-photocatalyst and a reactor consisting of an ultraviolet (UV) source and a reaction chamber for water samples contaminated with lead (Pb2+) and arsenic (As3+). To determine the removal efficiency of contaminants by ZISM nano-photocatalyst, the effect of various parameters including contaminant concentration, amount of nano-photocatalyst, pH and reaction time were investigated.

The results showed that with increasing the amount of ZISM nano-photocatalyst and pH, the removal of lead and arsenic increased. The maximum removal of Pb2+ and As3+ was obtained 99.8 and 98.3, in initial concentration of 5 mg/L, nano-photocatalyst dose of 250 mg/L, pH =8 mg/L and reaction time of 60 min.

According to the results, the ZISM nano-photocatalyst emerged as an efficient and recyclable nano-photocatalyst, which was a potential and environmentally friendly process for the removal of toxic heavy metals as hazardous water pollutants. This photocatalyst showed good recyclability in 5 consecutive periods.

Since allocating water to satisfy environmental water share can cause a conflict among governmental organizations supplying water, withdrawing water, and protecting the ecosystem, recognizing and analyzing such situations is paramount significance and can avoid encountering serious conflicts. In this research, we analyzed the actions of involved organizations which are either using or supplying water from Ilam’s dam to find the equilibria and the possible outcomes of the conflict.

We used Graph Model for Conflict Resolution to study the actions and strategies of rival organizations managing water allocation and involving in water conflict. The involved organizations are determined based on uses of Ilam’s dam. To define the strategies, all the measures and decisions of these organizations have been studied since 2005. In addition, the effect of drought years on the players’ actions is taken into account. Finally, we compared the status-quo with the results of the base line strategy of the model.

Equilibria results suggest that in states 27 and 32 the Jihad Agriculture Organization and the Water and Wastewater Companyare interested in withdrawing more water to achieve their goals. As a result, the Department of Environment will complain against them to protect ecosystem and provide the required environmental water share. In this case, the Regional Water Authority and the Governorship can play a dominant role in accomplishing to the stable outcomes. Furthermore, it is shown that the status-quo is not stable.

Analyzing this conflict indicates that all players have enough power to change the game's output. Therefore, their goals and measures can effectively change the equilibria and the future of the conflict

Each year, millions cubic meters of water are lost from water reservoirs (especially dam reservoirs) due to evaporation. Spreading artificial monolayers on water reservoir is one of the ways to reduce evaporation. Monolayers are one molecule thick films formed at a phase boundary like air/water interface. According to laboratory studies, long chain fatty alcohols such as Cetyl and Stearyl alcohol, are one of the most effective materials for reducing evaporation from water bodies, specially dam reservoirs. Most of the materials used as monolayers are readily broken down by bacteria, moreover these materials could also be evaporated, so redistributing them in specific periods is necessary to keep up their function. Most of Previous studies are experimental (both laboratory and in-field) which resulted a wide range for evaporation reduction (0\% - over 50\%) based on different cases, locations and monolayer materials. The aim of this study is to evaluate the amount of evaporation reduction causes by using this method to reduce evaporation. Energy balance relations were used to calculate the evaporation rate. Minab dam reservoir, was selected as a case study and Cetyl alcohol was chosen as a monolayer material. The evaporation rate was calculated for the 5-year study period (1390-1394) in base condition and in two scenarios, first for full time usage of monolayers and second for only summer usage scenario. Application of monolayers increases the apparent surface boundary layer thickness, thereby, increasing resistance to evaporation. Excess aerodynamic resistance caused by the usage of monolayers was computed according to previous studies as a linear function of wind speed (means the monolayer resistance decreases linearly when wind speed increases) and entered into evaporation rate calculations directly. Results show that average evaporation reductions are 8.1\% and 2.7\% espectively when monolayers were used full-time and when they were used only in summer. This amount of reduction leads to save up to 3.54 million cubic meter annually. A primary cost estimation was also done and resulted about 1 USD per cubic meter of not evaporated water for full-time usage scenario and about 0.8 USD per cubic meter of not evaporated water for the summer usage scenario.

Monitoring of organic carbon in water resources is a critical quality index in environmental management, water quality monitoring and drinking water projects. In this study, the performance and applicability of artificial neural network and multiple nonlinear regression modeling were investigated and optimized for the prediction of dissolved organic carbon. Optimization was performed using backward elimination method with the highest probable correlation coefficient and minimum number of input parameters. Model verification showed a good agreement between the predicted organic carbon and actual observations. Results showed the acceptable performance of neural network model with the mean absolute error percentage of 7.6% and correlation coefficient of 0.91. Further investigations unveiled that although the multiple regression model, with mean absolute error percentage of 8.4% and correlation coefficient of 0.89, seems to be less appealing but its fast run-time and better performance in critical conditions makes it a better choice for the prediction of organic carbon in aqueous solotions with high range of qualitative changes.

One of the most effective techniques to reduce evaporation rate is to use suspended shade covers to create shadow on the water bodies. Black polyethylene is a material that can be used for covering as porous fabric like sheets. In this study, energy balance analysis was used to evaluate the effects of using this type of covers in dam reservoirs on evaporation rate. Minab dam was selected as case study and energy modeling was conducted with respect to different scenarios. Results show that the use of black porous polyethylene can reduce evaporation by an average of 77% and 83% in the case of using single-layer and double-layer, respectively. This amount of evaporation reduction could be lead to reduce 11, 22 and 33 million cubic meters for 30%, 60% and 90% covering scenarios, respectively, for Minab dam reservoir.

The importance of considering the environment in the oil industry and related industries is undeniable in order to develop sustainable industry.
This study is scientific-research which is conducted to analyze and develop innovative strategies by HSE approach and environmental planning, using a case study of the Pars Special Economic Zone (Assaluyeh). Key factors influencing the development of HSE program have been explained in the first step of this research and the next step has been identified strategic factors in every field. Each of these factors, the relative importance and strategic value of implementing matrix model evaluation according to internal and external factors, using the Delphi technique and were evaluated by a questionnaire with closed questions. Thus, the strategic and internal-external organization factors have been ranked and the most important opportunities, threats, strengths and weakness points of the organization, with the aim of development of environmental protection based on HSE, have been introduced. Finally, evaluating the total function of strategic factors conclude that the strategic position of Pars Special Economic Zone (Assaluyeh), is able to overcome the opportunities to threats.
Hence, it’s possible to apply “opportunities-threats, strategies” in order to recompense weak points of the organization.

Water quality trading (WQT) is an economically incentive-based strategy that focuses on finding the optimal discharge permit market for surface water quality management. The amounts of traded discharge permits determine the interactions of emission sources in the market. Pollutantsthat are able to provide extra permits can satisfy the demands of other participants for credits. Finding appropriate permit sellers and buyers depends on their marginal costs, enthusiasm for participating in the market and the impacts on the quality of checkpoint for waste load allocation (WLA). It was recommended that the feasibility and cost-effectiveness of WQT should be analyzed in advance for practice. This needsto estimate the projected loads, environmental standard limits, the incremental and total abatement costs, and finally to optimize WLA. In addition, the assignment of total maximum daily loads (TMDLs) is required. This can be carried out through the simulation methods. However, TMDLs and WLAs with focus on limiting total nitrogen (TN) may be different to the phosphorous or biochemical oxidation demand (BOD). Therefore, the outcomes of WQT may be dependent on different factors such as the spatial location of pollutants, discharge loads, river self remediation, and economical and environmental conditions. All emphasizes on this fact that WLA using WQT requires analytical studies in different cases. This research primarily aims atfinding the optimal WLA in the downstream of Sefidrud in which the trading discharge permits (TDP) based on TN may qualify the pollutantsfor market interactions. It intends to assess the feasibility of WQT policy and compares the analytical results to the case of Gharesoo River. Finally, the effectiveness of integrating wastewater reclamation with TDP is introduced as a solution and compared with the results of Gharesoo River.
The study area is limited to the downstream catchment of Sefidrud in which it starts at the spillway of Sangar Reservoir at headwater. This ends up to the Caspian Sea after 55 km length. Here, the main pollutantsare identified as domestic, agricultural and industrial sources. This area receives the effluents of 10 point sources and rice farm lands. The flow rates and the projected TN load (kg/day) discharged to the surface water are estimated using the export coefficients, typical concentrations of TN and the statistical reports of their discharges as for the Gharesoo River. These were simulated by Qual2kw and the terminus point is the checkpoint. TMDLs are calculated by limiting TN to 4.5 mg/L at checkpoint. The impacts of discharge load reduction incurred by emission sources are also determined through the sensitivity analysis and normalized as previous studies.
This research addressesthe feasibility of nitrogen discharge permit market in Sefidrud and compares its effectiveness to the Gharesoo River. For this purpose, in the first scenario, the outcomes of conventional TDP policy are calculated and in the second scenario, its integration of wastewater reclamation market is examined.
The simulation results reveal that the concentrations of total and organic nitrogen can be reduced from 10 and 6.6 mg/L at checkpoint to 4.5 and 1.4 mg/L, respectively. This is conducted using the TMDL policy. This improvement may totally cost 70 billion Rials in a year in the catchment. In this regard, if the wastewater treatment operators appropriately use the secondary units, it can be expected that the classification of river based on water quality index promotes one degree.
In order to study the feasibility of conventional TDP, the WLA is determined using the typical procedure outlined by previous studies. Allocation ofabatement duties to the pollutantswith lower marginal costs as permit sellers may decrease the annual TN abatement costs about 1340 million Rials. It only saves 2% in comparison with TMDL approach and may not receive significant outcomes. In contrary, the results of TDP in Gharesoo River approved its economical efficiency. Here, total savings may exceed 35%. This is discussed as a matter of difference in the total nitrogen discharged between the domestics and agricultural users. The ratios of nitrogen loads in domestic effluent to the agricultural drainage are, respectively, 0.58 and 0.71 for Sefidrud and Gharesoo Rivers. This ratio is introduced as an index to compare the feasibility of nitrogen discharge permit market. Since the point sources are typically assigned as permit sellers to supply credits for non-point sources, this index may imply that whether the trading has sufficient permits. Studying these two cases for nitrogen permit market indicatedthat in lower ratios, the market may find more limits to supply credits. In this regard, it is concluded that the success of market does not rely on the expansion of catchments. It mainly depends on the existence of centralized point-sources and the agricultural land uses. It is also confirmed that the balance between permit demand and supply is the key of a successful trade.
In the second scenario, this study introduces an integration of TDP and wastewater reclamation market. This intends to find an economical solution to increase the credits for trading. If the reclaimed water is used for irrigation of crop lands, about 15 credits may be added to the conventional trading. In addition, the necessity of nitrogen removal would be reduced. This is due to the fact that the agricultural users require the nutrient contents of reclaimed water and simultaneously domestic wastewater treatment plants prefer not to remove nitrogen to sell their effluents with higher values. Consequently, marginal nitrogen abatement costs are dramatically reduced. In this regard, total cost savings would be increased to 57% and 63% in Sefidrud and Gharesoo catchments, respectively. It shows that the integration of markets not only provides more flexibility to the system but also makes markets promising as an economical solution.
In the first scenario, the primary price of permits can only be determined on 150 thousands Rials. Some stakeholders and dischargers may lose their economical incentives for participation in TDP. As a result, they would leave the market and make the predicted interactions fail. In order to increase the robustness of conventional market, it is recommended that point-sources should use discount factor about 15 to 25% for credits. In this condition, the equity in benefits may increase and make market more stable. However, the shadows of unstable and breakable market turn this strategy into a challenging solution. Therefore, in the second scenario, the integration market is introduced. Regarding the analytical results, it is understood that market would be changed into a more flexible strategy that no longer is dependent on the permit price for stability. In contrary to the first scenario, the point sources are not obliged to use the discount factor. However, they would freely reduce the permit price to increase the economical incentives of the permit buyer (non-point source). It is claimed that in this scenario, the permits can be sold about 99% cheaper than the first scenario and simultaneously all sellers may use the maximum benefits obtained. These results have similarly been achieved in Gharesoo River as well.
Finally, it can be discussed that using the integrated reclaimed water and discharge permit market depends on the capabilities of wastewater treatment plants to supply permits enough in regard. In other words, a highly populated city is required in the study area to provide the secondary treated wastewater and its related permits for the integrated market. Therefore, some recent studies have introduced approaches in which they may find further flexibility and economical savings in the market. For example, using artificial aeration is recommended for small areas with permanent streams in which the dissolved oxygen and BOD concentration are the major quality problems of water. Here, the integrated market is able to fill the blanks for nitrogen control and reduce more abatement costs. The second approach is to identify the amounts of tradable permits through index like dissolved oxygen where multiple pollutants such as BOD and nitrogen have to be controlled simultaneously. For example, the dischargers who are not able to provide nitrogen limits should abate more BOD in their effluents to address DO limits instead. In TDP program, this approach can increase the flexibility for pollution abatement but has high uncertainty and complexity. This is recommended to be used only in small areas with limited non-point sources. Meanwhile, the integrated market can be associated with this approach and increase its outcomes. Third approach points to the fact that in trading between point-non point sources, the seasonal demands and supplies should be considered. Therefore, in large watersheds with high non point sources, using seasonal WLA may reduce the overall abatement costs and increase the equity. However, this depends on that wastewater treatment plants should be practically able to obey various WLA policies through different seasons. Consequently, designing operationally flexible tertiary treatment units is a key factor for successful seasonally integrated discharge permit and reclaimed water market. Therefore, it can be outlined that the integrated market can be combined with different technical or management based approaches but needsto be studied in advance. The selection of optimal alternative and also permit pricing mat require an analysis based on game theory approach.

This study concluded that water quality trading strategy is not necessarily an efficient and promising practice to manage all surface waters. It depends on how much stakeholders attain economical benefits to participate in this voluntary strategy;otherwise, it would be failed. In this case, for nitrogen discharge permit market, it is recommended that the reclaimed water is used for irrigation withhigh content of nutrients. Therefore, the obligations tohigh nitrogen abatement and its managementcosts would be decreased. This makes the conventional market change into a more flexible strategy that is almost independent onprimary permit price. As a consequence, the market shape turns into a free interaction with the lowest monitoring requirements. However, it requires further studies to analyze the details of interactions with respect to the variations of permit demands in time. In addition, the combination of different qualitative parameters such as BOD, TN and DO may change the economical outcomes.

The increase of greenhouse gasses, the so called reason of climate change, may cause global average temperature to be surged up and consequently, patterns of regional precipitation, evaporation, landuse, soil moisture and river flow rates will be altered. Based on climate change, the earth’s temperature continues to rise, it is possible to expect a significant impact on water resources. As temperatures increase, some parameters like evaporation increases, sometimes resulting in rain and droughts. Rainfall and runoff variability are important phenomenon and at times severely impacts on the water resources planning and management. It is the most studied hydro-climate variables because of its significance for sustainable water resources management, water supply, environment, agricultural activities and ecological management. In this research, prediction of outflow of Gharesu River basin, a river in the west of Iran, in current and future has been done. Gharesou River basin is one of subbasins of Karkheh basin with area of 5354 km2 and is contain of three major streams. Using climate models and under different emission scenarios, future hydrologic criteria and outflow of basin have been simulated and predicted. This study have tried to discover the effects of climate effects on hydrologic variables, rainfall and runoff variability of a river basin using a methodology combining climate models, rainfall-runoff model, GIS and predictors.
In this study, the impact of climate change on the stream flow of Gharesou River for the future period of the years 2046 to 2065 is analyzed, utilizing two climatic models, HADCM3 and MPEH5, under three emission scenarios- A1B, A2, and B1. Moreover, MapShed, a rainfall- runoff model that requires GIS layers of surface water, topography, soil type, regional climatological stations, accompanying with precipitation and maximum and minimum data produced by LARS-WG model, was used to simulate the stream flow in a given upcoming time. LARS-WG model produced future hydrological data based upon present precipitation. Major predicted data are maximum and minimum temperature and sunny hours of a day. Then, the MapShed model was calibrated and validated based on the observed stream flow, provided from the Kermanshah regional water authority, of the years 1990 to 1995 and 1996 to 1998, respectively. In order to predict the future condition, the upcoming parameters of the rainfall and the temperature were predicted by downscaling the HADCM3 and MPEH5 models’ output by means of Lars-WG statistical downscaling model. For accomplishing this goal, the past climatic parameters of the period of 1960 to 1995 are used. The output of these climatic models (for the period of 2046 to 2065) associated with GIS layers of the basin’s land use, topography, surface runoff and soil context were introduced to MapShed, a GIS-based watershed simulation model, to produce the future flow of the river basin. The goodness of fit criteria, for flow rate produced by MapShed model, including RMSE, R2 and minimum cumulative errors (CE) indicate the decent performance in calibration and validation processes for the periods of 1990 to 1995 and 1996 to 1998, respectively. In all model-scenarios except for MPEH5-A2, the future, like ling-term observation period, peak flow happens in March. Under MPEH5-A2 scenario, the peak flow was transferred to April. Additionally, model MPEH5, under the A1B scenario and in all months, predicts flow rate less than that of observation period, while this model forecasts flow rates more than the period in observation period for all months of years. Moreover, most of the model-scenarios indicate a decline of flow rate in months of February, March, April, September and October and an increase in months of June, July, August and January.
The results show that the 20-year average of future flow in the Gharesou River under four model-scenarios of MPEH5-A1B, HADCM3-B1, HADCM3-A1B, and MPEH5-B1 will increase and under two model-scenarios of MPEH5-A2 and HADCM3-A2 will decline, in comparison with the long-term mean of the observed annual flow. It is worth mentioning that most of the scenarios predict the increase of flow rate, with respect to observation period, in the late spring and during summer and the decline of flow rate in the early spring. Like observed period, in the most of scenarios, peak discharges of outflow of basin has been estimated in March, and just in MPEH5 scenario, peak discharge has been happen in April.

Intelligent model optimization is a key factor in the improvement of water treatment. In the current study, we applied artificial neural networks modelling for the optimization of the coagulation and flocculation processes to achieve sufficient water quality control over the total organic carbon parameter. The ANN network consisted of a multilayer feed-forward structure with a back propagation learning algorithm with the output layer of ferric chloride and cationic polymer dosages. The results were simultaneously compared with the nonlinear multiple regression model. The model validation phase was performed using 94 unknown samples for which the prediction result was in good agreement with the observed values. Analysis of the results showed a determination coefficient of 0.85 for the cationic polymer and 0.97 for the ferric chloride models, respectively. He mean absolute percentage error and root mean square errors were calculated, consequently, as 5.8% and 0.96 for the polymer and 3.1% and 1.97 for the ferric chloride models, respectively. According to the results, artificial neural networks proved to be very promising for the optimization of water treatment processes.

The purpose of this study is to focus on the challenges that the nitrogen discharge permits market face with in Sefidrud River. In addition، it intends to find the optimal waste load allocation (WLA) in regard. Thus، the river is simulated by Qual2kw in which the total maximum daily loads (TMDLs) and the impacts of dischargers at the quality of checkpoint are calculated. Eventually، the optimization of WLA is assigned using the total abatement cost functions. Results verify that this market is limited because of few permits supplied by point sources. Here، 150 permits are totally traded that can only save 2% in total abatement costs comparing to the conventional TMDL policy. The economically incentive based optimal solution is only in hand if some dischargers use 15 to 25% of primary price as discount. However، in case of Gharesoo، the total cost savings increase to 35%. It can be concluded that the outcomes of discharge permit market relies on the total permit supplies and demands and their feasibility requires case studies in advance.

When there is no determined value for water (as a public asset) by its trustees and beneficiaries and its allocation method is more dependent on the requirements of water consumers than comparing water affairs benefits with its real value, decision making on which interested group, when and to what extent can use water is a game. This study is aimed to determine sustainable policies for water allocation to interested groups such that high quality sufficient water is available to survive water bodies and economic purposes of interested groups are satisfied by sustainability agreement with the environment. For this, the environment is recognized as an independent water user in optimization model and as an independent player in the game theory. Thereby, Zayandehrud basin has been studied as a case study.

In this study was first dealt with optimizing the allocation of water output from the reservoir to consumptions including drinking, agriculture, industry and environment by means of genetic algorithm. To get the most desirable possible state of water provision for consumptions, 4 approaches have been considered, as described briefly below. The first includes providing biological current for the river which is in an equilibrium using Tenant (Montana) method and available data (providing 2.06 (MCM) for each month in the cold season and 6.18 (MCM) for each month in the warm season). The second has been formulated by providing minimum water requirement for lagoon survival and considering protection and provision of minimum survival requirements for this valuable water ecosystem in the area. Continuity of natural life in the swamp depends completely on water depth. The lowest possible depth for vital activities is in about depth of 15cm. This depth can be achieved by importing 75 MCM per year water to the swamp. Benthos is hardly survived in this depth. The third includes providing desirable quality for the lagoon based on TDS such that the water requirements for TDS dilution have been assumed as a biological requirement. In the fourth, provision of minimum water requirement for the lagoon is considered and with regard to the studies on Gavkhoony swamp, desirable performance occurs with provision of 140MCM per year water. This amount provides depth of 30cm for the swamp. Then, having estimated benefits of each beneficiary, their interactions in the basin have economically investigated by cooperative games. The percentages of requirement provision for beneficiaries and annual water allocations have presented in Table 1 for different approaches. The benefits of each beneficiary and the results of cooperative game have been provided in Figure 1. Tabel - Gross profit of water user in each approach Discussion and

With regard to data from the studied area, in spite of various managerial plans to increase water provision for the basin, it no longer satisfies the requirements of water consumers. Specially, it is the case in the environmental sector where because of ignorance and devoting water allocation priorities in the recent years, it has been deficient in its life and is completely dependent on seasonal currents and rainfalls. According to the designed approaches in the environmental sector of this study, more than 85% of its requirements can be eliminated in allocations. With water provision approach for environment sector, 3-8% of agricultural and 8% of industrial requirements are deficient. From environmental requirement provision point of view which has been distinctively defined in every approach, the model has shown the best performance in the first approach such that 100% of environmental requirements are satisfied. Of course, considering that this approach has accounted minimum requirements for the environment, minimum deficiencies in agricultural and industrial allocations have been observed. Maximum water requirement has been considered in the fourth approach in which optimization model can allocate 87% of environmental requirements. The fourth approach, from water allocation to the environment view point, is the best approach because of water allocation to the environment with regard to water content as well as positioning the lagoon in a desirable state for survival. It can be concluded from economic analyses of model approaches that the industry has the same benefit in all approaches despite 8% change in water allocation respect to unfair allocation and low or high environmental utility in different approaches has no influence on economic performance of the industry. The second approach has the most benefit in agricultural sector and it has the best performance in environmental sector because of the most desirable state for the river and lagoon survival. Economic analysis shows that agricultural sector has more benefit in second approach than other states. From model allocations, it can be said monthly allocation and distribution model has impressive effect in agricultural sector. With constant optimization procedure in allocations, agricultural sector incurs severe pressures but considering allocated water and benefits in the agricultural sector, first, second and fourth approaches have little differences because of monthly water distribution procedure in firth and third approaches. From game theory, benefits from player cooperation in agricultural and environmental sector have been more than no cooperation. The industry earns the same benefit from both states, except for third approach. Proportional Nucleolus game has maximum benefit in agricultural sector, except in the first approach. Weak Nucleolus has shown better performance in benefit calculation in the environmental sector, except for fourth approach. Therefore, there is no specified procedure for games but because of more benefit from cooperation in agricultural and environmental sectors than no cooperation both sectors will get more benefits from cooperation beside water requirement provision. Best benefit allocation has respectively occurred in fourth, second, third and first approaches. Finally, it is clear that considering the environment as a beneficiary of basins and planning for water resource management makes always more benefit the system, although less water allocation to consumers makes less benefit. Because of no profit in environment sector and no protest except in critical conditions, there is ignorance in this sector while water ecosystems are most valuable resources that their economic value estimation is complicated and far from reality but with these economic methods it is seen that the aggregate benefit and profit is in the environment protection and survival.

Contaminated groundwater by gasoline spill is a worldwide environmental problem. Gasoline contains methyl tert-butyl ether (MTBE) and benzene, which are the chemicals of concerns (COCs) among the gasoline components. MTBE is highly water soluble and has a low Henry’s law constant and low soil adsorption co-efficient. Therefore, MTBE can easily move through the soil and then accumulate, distribute or migrate in groundwater. Accidental releases of petroleum products from pipelines and from aboveground and underground storage tanks are the most common causes of groundwater contamination in most countries. Due to issues of taste and odor, health concerns, carcinogenic effects of benzene and MTBE, many attempts have been made to remediate contaminated groundwater. Due to the limitations of conventional groundwater cleanup technologies (e.g., pump & treat, air stripping and permeable reactive barriers (PRB)), in-situ chemical oxidation (ISCO) has become one of the attractive remedial alternatives for petroleum-hydrocarbon contaminated groundwater in recent years. In addition to oxidation-reduction potential (ORP) of oxidants, hydrogeological and geological characters and dispersion diagram of contaminants and other effective factors in aquifer must be identified and considered before designing ISCO system. Based on natural conditions of the case study area including approximately fine grained aquifer, low permeability, low concentration of dissolved autochthonous iron and high levels of scavengers like ions and other organic matters, we need a potent and stable process simultaneously to access an efficient distribution and link between chemical agents and target contaminants. Thus, in this study Fenton chemical oxidation (H2O2/Fe) using stabilized nano zero-valent iron particles (S-NZVI) was used. Among different sources of iron as catalyst in ISCO, S-NZVI was opted. This study focuses on in-situ remediation of contaminated groundwater by Fenton’s oxidation using stabilized-NZVI particles to gain more efficiency and ROI in special conditions of southern Tehran Aquifer. The main objectives of this study were to 1. assess the feasibility and effectiveness of applying the S-NZVI in ISCO injection system as a catalyst on the control of petroleum-hydrocarbon plume; 2. determine the optimum components of the ISCO materials including H2O2, S-NZVI, and in some cases required pH; 3. determine the level of some hazardous by-products including tert-butyl alcohol (TBA) and acetone in simulated conditions; 4. assess the influences of physico-chemical conditions of groundwater on remediation efficiency. The tests were implemented on a bench-scale pilot with a one-dimensional soil column and similar chemical and physical conditions of the region. To simulate the qualitative conditions of the contaminated groundwater, MTBE, and BTEX were used as the chemical of concerns (COCs) but only MTBE and benzene were assessed as target contaminants. Uncontaminated and non-uniform sand, silt, and clay (50% fine grained sand and 50% low-Plasticity silt and clay) (Soil Unified Classification: “SM”) were mixed as simulated porous media. To achieve the average porosity of n=0.38 and the average hydraulic conductivity (k) equal to 0.001cm/s, a standard was defined for compacting of the soil mixture in the column. Water head of all reservoirs was equal and varied between 140 and 135cm during reaction time and the length of the soil column was 32cm (i=Δh/Δl≈4.3). Before starting each experiment, soil column was flushed with a 1mM HCl solution at approximately 10 Pore Volume (PV) and then was washed with de-ionized water at 4-5 PV. After this preparation process, predominant dissolved anions and cations in effluent water decreased to below 10 mg/L. Three clean reservoirs considered to inject polluted water, H2O2 solution and S-NZVI suspension into the column. Then salts, MTBE, BTEX, sulfuric acid and caustic soda were added to de-ionized water to obtain the required values for each reservoir. To avoid agglomeration, deposition and oxidation of S-NZVI particles by dissolved oxygen (DO) in its reservoir and to keep a homogenous suspension, before and during the injection, N2 gas was sparged to the suspension for mixing and removing DO. To reduce volatilization of MTBE and BTEX from water, the reservoir was isolated against air with a flexible cap and was cooled too. At the end of each test, a 4mL sample was taken from the last sampling point on the column by a syringe and stored in a sealed glass container with no headspace. It was then kept in the refrigerator for maximum 3 days until analysis time. Discussion and At first, for investigation of system efficiency and finding optimum concentrations of the agents at simulated conditions including neutral pH range, temperatures between 15°C and 20°C and certain COCs and ion levels, different concentrations of agents were injected into the column. The concentrations of MTBE and benzene in the influent and effluent were measured to calculate remediation efficiency. Blank experiments illustrated that approximately 20% of MTBE and 30% of benzene can be absorbed in fine grained particles of soil during the initial passage of contaminated water before the reaction starts. Therefore, a preparation time of 1.5hr was considered to saturate the soil in order to eliminate COCs absorbing capacity of the soil. Degradation of MTBE and benzene can be increased with the increasing of H2O2 and S-NZVI concentrations. However, this procedure will continue till a certain level of each one (Fig. 1). It was concluded that for remediation of simulated groundwater polluted with approximately 2mg/L MTBE and 1mg/L BTEX, optimum concentrations of H2O2 and S-NZVI were 1500 mg/L and 300 mg/L, respectively. This leads to elimination of 78% of MTBE and 87% of benzene in the pilot with mili molar ratios. and Then, to assess the degradation of COCs and hazardous by-products of the reaction (acetone and TBA) during run time, samples were taken from all sampling points on the length of the column. The by-products were generated first and then were degraded as an organic matter by hydroxide free radicalsin oxidation process. At least, 90 minutes after the beginning of the reaction, by-product concentrations were obtained less than 0.1 ppm on average. Thus, it can be claimed that the remediation has no problem in this respect. The tests demonstrated that degradation rates of MTBE and benzene are less than values previously reported by other researchers. It is due to differences between complete mixed conditions of batches in other researches and conditions of this study including using porous media (laminar flow), the type of iron, and high levels of scavengers like ions which reduce the availability of radicals to contaminants. S-NZVI unlike NZVI, ZVI, and ferrous salts, supply Fe2+ ions continuously to react with H2O2 during passing through the column. Thus, hydroxyl radicals are generated continuously (not immediately) and degrade COCs. This process causes more distribution of agents in subsurface media and increases the ROI. In the next part of the study, to investigate the effects of pH on remediation efficiency, the optimum concentrations (H2O2=1500mg/L and S-NZVI=300mg/L) were injected and all experiments performed at 16-17°C to simulate ion conditions. The tests demonstrated that the efficiency is more in lower pH so that 90% reduction in MTBE and 96% reduction in benzene occurred at pH=3.2. Thus, alkaline conditions result in drastic reduction of remediation efficiency or waste some of consumed iron. In the other hand, high pH conditions increase iron intake and low pH condition can help iron to be solved in water. In the next part, to assess the effects of ion concentrations on remediation efficiency, the optimum concentrations were injected and all experiments were performed at 10-15°C, pH=6.5-7, and different ion conditions. Five categories of TDS were selected for injection. Results illustrated that at very low levels of ions, the removal efficiency will be approximately 92% for MTBE and 96% for benzene. Thus, existence of ions up to real concentrations of the area causes 15% and 9% reduction in removal efficiency of MTBE and benzene, respectively. On the other hand, they increase consumption of reaction agents. Ions including HCO3-, CO32-, SO42-, Mg2+ and Ca2+have more effect and ions including Cl-, NO2-, NO3-, Na+ and K+ have lower effect on efficiency reduction. Ions can consume iron particles and cause formation of an insoluble layer on the surface of particles. Using S-NZVI instead of bare NZVI or ZVI, partially, helps the particles to be more stable against the unwanted reactions during passing the media. This study showed that using S-NZVI instead of micro-ZVI powder can reduce consumption of iron as catalyst and increase the ratio of H2O2/Fe0. S-NZVI unlike NZVI, ZVI and ferrous salts, supply Fe2+ ions continuously to react with H2O2 during passing through the column. Thus, hydroxyl radicals are generated continuously (not immediately) and degrade COCs. This factor helps the agents to distribute more in the subsurface media and increases the ROI. Results illustrated that in theory MTBE and benzene could be removed in this system significantly. But in practice, full-scale pilot tests must be done after a design process to determine the method sufficiency.

One of the issues considered in the statistical analysis of water quality variables is investigating the correlation between them. Canonical Correlation Analysis method expresses the relation between two sets of parameters by finding some linear combination of the first set of variables that have the most correlation with the linear combination of the second one. In this study, to supply a significant amount of water needed for Khorasan Razavi, Khorasan Shomali and Golestan provinces, the relation between physical and chemical variables was evaluated to provide an appropriate management plan. Five physical and six chemical variables were measured at 38 stations. Results showed that there is an effective correlation between the physical and chemical parameters and from five canonical varieties, only the first two categories are statistically valid according to P-value number. In general, results confirmed by the cluster analysis method indicated the effectiveness of linear combinations for EC and TDS. Chemical parameters are mostly caused by human activities and physical parameters caused by both human and natural sources. It can be concluded that the sources of both categories of parameters are human activities. Thus, It could be recommended to focus more on human activities in future water quality management plans and also control the physical parameters.

The importance of inter-basin water transfer project is its ability to balance the non-uniform temporal and spatial distribution of water resources and demands، especially in arid and semi-arid regions. A water transfer project can be executed if many economics and environment criteria are satisfied. In this research، a methodology is proposed for inter-basin water allocation using the virtual water concept. Thus، a model based on the virtual water estimates the benefit of the inter-basin water transfer. SWAT simulation model was applied in order to estimate the virtual water potential of the receiving basin. The water related revenues of the basins that receive transferred water and the initial basins and related virtual water are estimated. The results show efficiency and benefits based on value of water and production. The effectiveness of this methodology is examined by applying it to a large scale case study of inter-basin water transfer from the Solegan to the Rafsanjan Basin in southeastern part of Iran.

Due to shortage of fresh water resources, the quality of impounded water behind the dams become more important than how it was previously as a source of fresh water resource. Thermal regime and dissolved oxygen concentration are factors that affect the quality of water reservoirs. Many lakes show vertical stratification of their water masses, at least for some extended time periods. The atmosphere imposes a temperature signal on the lake surface. As a result, thermal stratification can be established during the warm season as a lake is sufficiently deep. On the contrary, during the cold period, surface coolingfo rces vertical circulation of water masses and removal of gradients in water properties. However, the gradients of dissolved substances like dissolved oxygen may be sustained for periods much longer than one annual cycle. In order to understand the annual cycle of temperature and dissolved oxygen in Shahid Rajaee Reservoir, Ce-Qual-W2 model was used. Study area Shahid Rajaee Reservoir Dam located over the Tajan River almost 40 km south of Sari, Mazandaran, Iran. Construction purposes of this dam is including water supply and regulation of for agricultural activities in Tajan lowland, potable water supply for the population within the plan area, industrial water supply, power generation, flood control, and prevention of the damage by flooding. The dam type is double curvature concrete arch dam and its height is about 133.5 m. reservoir volume is about 165 MCM and was constructed from 1987 until 1997. Shahid Rajaee reservoir dam is simulated using a two-dimensional, laterally averaged, hydrodynamic and water-quality model, CE-QUAL-W2. Hydrodynamics, temperature, and dissolved oxygen are simulated and then calibrated with observed data to verify accuracy. The input data used in this model are the best available and are assumed to be accurate representations of meteorology, flow, and water quality parameters. Meteorological data for the model include air and dew point temperature, wind speed, wind direction, and cloud cover observations and daily mean flow rates. These data are collected for a period from 2001 to 2011. Data for water quality parameters are taken from Mazandaran Water Company for the years from 2010 to 2011. When data are not available, statistical relationships was applied to supplement the water quality data. The hydrodynamic model built and calibrated for the years from 2001 to 2011. Then the model was used to simulate the thermal regime and dissolved oxygen concentrations for the period with two assumptions. The first assumption is continuation of current situation and the second is a 50% increase in water requirements. The bathymetric grid was generated using topographic maps in scale 1:100000. The water body was divided into 95 segments, and 45 layers. The segments have 50 meters length and all layers are 2 meters thick. The accuracy of the bathymetry data was checked using storage-capacity curves. The curves show reservoir storage at different reservoir elevations. The com parison of the model volume to the actual storage capacity is made to verify the accuracy of the model grid. Calibration data include temperature and DO concentrations measured at several monitoring sites taken at depth intervals of 1 to 15 meters from the water surface to the reservoir bottom. The results indicate the thermal stratification in summer and vertical mixing in winter. This regime is predicted for the years from 2010 to 2014 in Fig. 1. Based on These results Shahid Rajaee Reservoir is in branch of warm Monomictic lake. Warm Monomictic lakes are lakes that never freeze, and are thermally stratified throughout much of the year. The density difference between the warm surface water (the epilimnion) and the colder bottom water (the hypolimnion) prevents these lakes from mixing in summer. During winter the surface water cool to a temperature equal to the bottom water. Lacking significant thermal stratification, these lakes mix thoroughly each winter from top to bottom. Dissolved oxygen modelling results showed that its concentration at reservoir bottom is zero when thermal stratification dominates. Dissolved oxygen concentration will be homogeneous at winter when thermal vertical mixing dominates. Winter Anaerobic conditions in the bottom of the reservoir are fading and the reservoir is homogeneous in the vertical direction. Change in dissolved oxygen concentration is also predicted for the years from 2010 to 2014 in Fig. 2. The 50% increase in water requirement caused a decrease in water levels and water retention time in the reservoir. Besides this issue, 50% increase in duration of water requirement occurred in summer and the presence of anaerobic conditions decreased in the bottom of the reservoir.

Industrial activities are among the major factors leading to environmental disturbances.One of such activities is that of Mobarakeh Steel Complex.The major aim of this study wasto investigate the concentration and distribution of Cr and mo in soil, water and air aroundthe factory. In this study, systematic sampling and geochemical analyses were used. After granulumetry, the samples were analysed with ICP and AAS methods and the mapsrepresenting the dispersion of Mo, Cr were drawn using the "Surfer "Software. From theobtaind results, the effects of pollutants on the surrounding areas were determined. Thiswas compared with global standards. Finally some controlling methods to preventdistribution of environmental pollutants in the area were presented.

Industrial and agricultural activities are major factors for distribution of As in Mobarakeh region. The aim of this study is an evaluation of the extent and amount of Arsenic pollution in the soils of south – west Mobarakeh region. In this study, systematic sampling and geochemical analyzes were used. After granular metery the samples were analyzed using the ICP method. The amounts of As in soil weredistinguished and a distribution map was drawn with the Surfer software. Because of the effect of Fe and P in the distribution of As, their amounts in the soil were analyzed and the distribution maps were drawn and compared with the Arsenic map. Considering the global standards and comparing them with natural limits, Changes in the range of As were normal(0/1 -40 PPM).

Comprehensive information and knowledge about the quality of water resources plays a very important role in preservation plans for water resource management. One of the engineering methods used to assess river water quality conditions without mathematical and statistical complexity is water quality indices. In this method, different water quality parameters are analyzed and interpreted in a river water quality assessment study. It is one of the most important parts of river quality monitoring plans in which the qualitative indices are converted to a single and dimensionless number. Water quality classification is undertaken on the basis of the value of the indices comparing with a predefined rated scale. In this study, a monitoring plan is achieved for the 18 stations located along with Gheshalgh River in Kurdistan province in Iran. Water quality assessment has been conducted using two NSF quality indices of general water use and the British Columbia index for drinking and agricultural consumption. Based on the results obtained from these indices, water of this river has the worst quality due to agricultural use downstream of the wastewater treatment plant of Sanandaj city. Its condition is degraded up to the discharge point of Morghe Par slaughterhouse due to the assimilation capacity of the river. In this location water quality is acceptable for drinking purposes and most of the stations have appropriate conditions except for Dare Kuleh and the downstream stationwhich are on the border. Results indicate that the degree of influence of urban pollutant sources such as entry of urban wastewater and also of a landfill leachate brook is high, especially in the Gheshlagh bridge area up to the tributaries.