مجله مهندسی آبیاری و آب ایران
پیاپی 46 (زمستان 1400)

Correct estimation of the river sediment volume is important for many water resources projects.In this study, the empirical equations of sediment transport, support vector regression (SVR), and developed k-nearest neighbor regression (KNN) were used in order to estimate suspended sediment load in the Sistan River. In this regard, in addition to the maximum temperature, minimum temperature, and dischargeand Suspended Loud In the period 1374 to 1390, it was paired on 1682, discharge, the classified discharge was used as effecting variable to suspended sediment load modeling. For each of the input combinations in support vector regression and development k-nearest neighbor regression the best structure of the regression model determined based on the performance criteria. The Result showed that the Toffaleti method is the best method between empirical equations with R2 equal to 0.705 and RMSE equal to 66558 Ton/day. Also, the support vector regression model with discharge, minimum temperature, maximum temperature and classified discharge as the set of input data is the best model in estimation of suspended sediment load with R2 equal to 0.96 and RMSE equal to 2809.3 Ton/day. The results indicate that the regression method estimate suspended sediment load much better than empirical equations in the Sistan River.

In the present study, the M5 tree algorithm and MARS multivariate comparative regression have been used as new methods for estimating the suspended sediment load in comparison with the sediment measurement curve method. The information used in this study includes water flow and sediment discharge related to four hydrometric stations of Doroud and Tireh Marvak hydrometric stations on Tireh river, as well as Marbareh Doroud and Marbareh Darreh Takht on Marbareh river in Lorestan province. For fabrication and validation of the models, the flow rate with one, two and three days delay and the flow rate of the same day with rain as input parameters and the suspended sediment load flow rate were considered as output parameters. Statistical analyzes were used to evaluate the efficiency of the models and compare their results with conventional methods. In Marbareh Doroud station, the values ​​of RMSE and R2 for the M5 model were 0.47 and 0.71, respectively, and for the MARS model were 0.46 and 0.72, respectively, while in the measurement curve method they were 0.56 and 0.64 The performance of the proposed models indicates an improvement in their accuracy and ability to estimate the suspended sediment load. The results showed that the equations presented by the M5 and MARS tree models are more accurate than the measurement curve. Based on the results, it was observed that the two methods M5 and MARS have provided close answers to each other, but finally, due to the simple and conceptual structure of the M5 model, this method is a more appropriate method for estimating the suspended load in the case range. The study was selected. In addition, the study of the relationships obtained from the two models M5 and MARS showed that among the input parameters, the flow rate of the previous day and the same day were used to estimate the suspended load and the prediction values ​​were affected more than anything. These two factors have been.

Water diversion from river for agriculture or industry based on gravity is possible according to different methods where using porous media is one of its methods. It is necessary to study the water diversion in such flows because there is sediment in water flow in the nature. Different methods such as: porous media grain size, cohesive sediment density and various water discharging were studied in this research by making experimental model. The obtained results show that discharge coefficient in D50 = 16.5 mm in discharge 20.7 lit/s with 1.5, 3, 6.5 and 8 gr/lit density are 0.038, 0.035, 0.034 and 0.033 respectively. Reducing the flow velocity in porous media is because of increasing in density which is a reason of reducing in discharge coefficient. The discharge coefficient for 3 gr/lit density in discharge of 20.7 lit/s for the D50, 11.5, 16.5 and 25 mm are 0.025, 0.035 and 0.042. This is happened because of higher porosity in D50 = 25 mm than D50 = 16.5 mm and D50= 11.5 mm. it was observed that in lower discharges, discharge coefficient changes are more than inlet discharge but it is stable by increasing the inlet discharge. By analyzing the obtained data and using dimensional analyzing and multivariate regression, relationships to estimate discharge and discharge coefficient were proposed for this intake

In any country, the management of water resources in watersheds is very important, and managers try to protect these resources by providing management packages. One of the basins that have been considered by managers in the recent years is the catchment area of Lake Urmia located in the northwestern of Iran. In this study, considering the complexity of the rainfall, temperature, evaporation, discharge of hydrometric stations, water volume of the Lake, the contribution of each factor on the rate of decreasing water volume of Urmia Lake was determined. To evaluate the changes in complexity, Wavelet-Entropy combination method was used. To calculate the value of complexity, 41 years seasonal time series were used (period of 1977-2018) for the selected hydrological units of the south and west of Urmia lake. Then, the time series were divided into three equal parts, and the complexity changes were calculated in these intervals based on the wavelet-entropy criterion (SWS). The results showed that SWS of lake water volume, rivers discharge flow and precipitation were reduced in entire time, however, the SWS of temperature and evaporation increased. Generally, it seems that the rivers discharge flow was the main cause of reducing the volume of lake water, and precipitation, temperature, and evaporation parameters were in the next ranks.

In this study, experimental research was conducted to determine the effect of  arrangement and canopy density and other common non-dimensional hydraulic parameters on drag coefficient of rigid vegatations, during long waves. The beach and vegetation model was fitted at a knife edge flume.  A dynamic loads were measured by Load Cell device (Type Single base with a capacity of 50 kg) and 3D velocities were measured by Acoustic Doppler Velocimeter  equipment.  The experiments were performed in two triangular and rectangular layouts, which include densities of 12 to 273( stem/m 2). The results showed that the vegatations Drag  coefficient was indirectly related to the flow velocity. As the flow velocity of rigid vegatations decreases, the Drag coefficient increases. It was also found that rigid vegatations have a significant  influence on energy absorption and energy dissipation. On average, with an increase of 15%, the area occupied by the coverage is increased by 12% to the values of the Drag coefficient. In the most dense case, 273 stems per unit area with increasing relative wave height, due to the fact that the wave is involved in colliding with the beach and breaking the wave with more coverage, the traction force is increased and 18% is added to the Drag coefficient. In the most dense case, with a decrease of 8% in the Reynolds value, the Drag coefficient increased by 33%, and in the lowest density, the increase in the Drag coefficient increased to 44%.

Due to the severe shortage of fresh water in arid and semi-arid regions, farmers are forced to use deficit-irrigation techniques along with salt water. In order to minimize salinity and water stresses impacts on the yield and yield components of spinach plant, separately and mutually, a pot experiment was performed from November 2, 2018 to January 18, 2019. The experiment was performed as factorial in the form of a completely randomized design with four replications including three irrigation levels (consisting complete irrigation 100% water requirement =W1, W2=75% W1, and W3=50% W1) and three salinity factors (drinking water S1=0.75, S2=4, S3=8 dS/m) in Kashmar's arid climate. The results showed that separate salinity and deficit irrigation stress had a significant effect on the plant traits including the wet weight of aerial part, leaf surface, plant height, stem height, root length, the dry weight of aerial part and the dry weight of the root, but the mutual effect of salinity and deficit irrigation on the mentioned traits was not significant. As salinity and deficit irrigation increased, the morphological properties of the plant decreased; for example, the maximum wet weight of the plant's aerial part was 147.15 grams in the plant related to W1S1 treatment and its minimum was 38.36 grams in the plant related to W3S3 treatment. The results of comparing the average of plant growth traits showed that there was no significant difference between the treatment of 100% water requirement with salinities of 0.75 and 4 dS/m, but in the salinity treatment control (0.75 dS/m) there was a significant difference between various levels of deficit irrigation. In regard to the above results, it can be said that spinach plant is more sensitive to water stress than salinity stress and applying water stress to the plant during the growing season should be avoided

Recently, calibration based methods are developed for leak detection in water distribution networks (WDN). These methods are collected the pressures and flows data of a real network and try to regulate the demands in hydraulic network model to match the model results with observations. Therefore, in addition of hydraulic analysis, an optimization algorithm is needed. In this study, a new population based optimization method is presented. In this method, the network first is zoned to some regions. First generation are guessed for appearance loss and leakage in each zone and answers fitness are calculated. Moreover, a new factor named minor fitness, developing in this research, is computed for each zone in all answers. A small minor fitness in a zone, predicts the correct value of leakage. With combination of the results of best answers, in each generation, a range is calculated for the next generation selection. This range become narrower in consecutive generations and the correct answer is found. The proposed method is investigated on a real network with hypothetical leakages. The results obtained in model are evaluated with the assumed value, as well as, WaterGEMS model results.  The results show the capability of the proposed optimization method in detection of the both location and the value of leakage. Comparing this method with Darwin calibrator show more accuracy, convergence and speed of the proposed method. The fitness in the present study method and WaterGEMS calibration are 0.654 and 0.817, respectively.

One of the ways out of the water crisis is to use polluted and non-conventional water. In this regard, a study was conducted in 2017 and 2018 in the Agricultural and Natural Resources College, the University of Tehran in the form of a completely randomized factorial design with four treatments, three replications, and a total of 12 experimental plots in the lysimeter environment. Experimental treatments included surface irrigation with contaminated water by heavy metals (SRC), surface irrigation with conventional water or control treatment (SRF), subirrigation with contaminated water by heavy metals (SBC), and subirrigation with conventional water (SBF). The texture of the soil inside the lysimeters was sandy loam, its pH was 7.4, and the heavy metals used were copper, zinc, and lead. The results showed that the highest copper concentration in SBC treatment was observed at a depth of 75 cm, which was 43% less than the maximum amount in SRC treatment, and 25 cm depth, which was significant at the level of 5%. Also, there was a difference between the maximum amount of soil zinc on SRC and SBC treatment of more than 4.2 mg/kg, and in subirrigation, 32% less zinc was absorbed into the soil, which was significant at the level of 5%. The average amount of copper uptake by the plant in SRC treatment was 4.97 mg/kg, which was 80% and 70% increase in copper uptake, respectively, compared to control and SBC treatment, and this difference was significant at the level of 1%. In general, top-down motion (SRC) is higher than bottom-up motion (SBC), indicating the use of heavy metal contaminated water in subirrigation.

Irrigation scheduling  is an important step in optimizing agricultural water use management  and has been recommended in the previousstudies. Since smart models play an important role in irrigation planning on the  water use management of on farms, it has this aimed study that is investigated the effects of such models on sugar beet water consumption at Zarghan-Fars Agricultural Research Station from 2018 to 2019. Here was conducted with three treatments and three replications in a randomized complete block design, in which treatments were included three approach of scheduling irrigation such as: intelligent system (T1), database of crop water requriments is that obtained from calimetological station (T2), and farmers traditional management (T3).Their replicates were covered 6 lines of Arta variant sugerbeet with 8 meter length that irrigated via the Tipe irrigation system. The results reveal that the amount water for irrigation in T1 and T2 treatments were about 27% and 15% less than traditional irrigation management, respectively, whereas the average daily water use in T1 treatment was about 7was that varied from 2 to 10 mm/day during different stages of growth, such that was lowest water use compared to the other treatments.The accumulation annually water use in treatments of 8946, 10194 and 12130 (m3/ha) respectively for T1, T2 and T3 showed a 27% of the saving water in the intelligent system comparing with the control treatment, in which it was included two parts such as 10% due to decreasing the irrigation time and about 17% due to improving the discharge setting in the experimental plots.The results of research has been shown that the duration of irrigation and the input of distribution network would controled by using the intelligent system for estimating and planning irrigation.The tracked measurements of amount water use and soil moisture for each irrigation caused the improving the distribution  system management resulting in decreasing one hour of irrigation time in T1 compared to the other treatments.  In T1, T2 and T3 treatments, Crop water productivity (CWP) based on the root yield were 3.46, 2.25 and 2.7 kg per cubic meter, and based on sugar content were 0.69.0.44 and 0.38 kg sugar per cubic meter.

It is necessary to study the efficiency of water use as an effective factor to determine water consumption efficiency and improving it. On the other hand, measuring this parameter is time-consuming and expense. Therefore, developed models that have capability to provide accurate simulations at real is vital. In this study, hydrodynamic, Zero initial and SRFR (Balance method) models were used by border irrigation during 2014-2015 for simulating applied water efficiency in wheat cultivation. Calibration results in the first year showed that the complete hydrodynamic and zero initial models had similar performance with 12 and 13% error, respectively, which was compared with the SRFR model in the second year. The results also indicated that that the SIRMOD-HD model with an average R2 of 0.89, the Root Mean Square Error (RMSE) of 1.86% and the Normalized Root Mean Square Error (NRMSE) of 5% is suitable for simulating application efficiency conditions and has better performance than The SRFR model.

Piano-Key weirs are a new type of overflow that are designed to increase the drainage capacity of dams and canals. If the keys forming this overflow model are placed on an arc of a circle, it is called curved piano-key weir. In this research, the performance of three models of Intelligent Support Vector Regression (SVR), Support Vector Regression- Firefly (SVR-FA) and Support Vector Regression- Grasshopper (SVR-GOA) to predict curved piano-key weir flow rate were evaluated. Determination Coefficient (R2), Mean Squared Error (MAE), Root Mean Squared Error (RMSE), and Scattering Index (SI) are four statistical indicators that are used to determine the accuracy of intelligent models. The result of these evaluation criteria during the test period is that the SVR-GOA model with values ​​of 0.99275, 0.01220, 0.00026 and 0.00046 compared to the SVR-FA model with values ​​of  0.95666, 0.03844, 0.00200 and 0.00342 and SVR with values ​​of 0.94249, 0.04013, 0.06027 and 0.00410 for R2, MAE, RMSE and SI indicators, are more accurate in predicting curved piano-key weir flow rate

Concrete gravity dams secure their stability by the weight of the concrete used in their structure. Therefore, minimizing their weight (the volume of concrete consumed in their body) can reduce the costs significantly. This study aims to evaluate the performance of three metaheuristic optimization algorithms: harmony search, particle swarm optimization, and artificial bee colony, to find the optimal cross-section size of the gravity dam. In this way, the Koyna dam located in India is considered a case study. The programming is applied in Matlab software. Each algorithm under the constraints of this problem (the sliding, overturning, and vertical tension on the body of the dam) is run 6 times. Finally, the lowest value was chosen as the optimal result. The results revealed that however all the algorithms have the optimal outputs than their real one but the optimum one is for the harmony search algorithm. To investigate the role of available uncertainties of dam cross-section, Monte Carlo simulation is engaged. The achieved results based on reliability show more safety of dam design.

The accurate design of the geometry and the sealing layers of the earth dam to obtain the optimum structure are important from a practical and economic point of view. Due to the complexity of the analytical methods, the numerical method is the best practical solution for measuring the mechanical behavior of the dam including seepage and slope stability. In this study, reliability analysis of seepage and slope stability of Eyvashan dam has been performed using Multivariate Adaptive Regression Splines (MARS). The Eyvashan earth dam was modeled in Seep/w and Slope/w Software's and the model was validated by observational data of instruments. Then, forecasting of seepage and slope stability was investigated by MARS method. For this purpose, 214 data series from Seep/w numerical analysis and 300 data series from Slope/w numerical analysis were used to establish the MARS model. The model was evaluated and validated by these data. The MARS model showed high performance in modeling process with determination coefficients of 0.98 and 0.97 and the root mean square error of 0.0132 and 0.0160 for seepage discharge and safety of factor of slope stability, respectively. Also, in this study, the effective parameters in seepage and slope stability such as permeability of materials, internal friction angle of soil, specific weight of materials and upstream water level were sensitized to determine the best combination of modeling input's structure. The parameters of the upstream water level 29.5% and the permeability of the core 12.5% had the greatest effect on the seepage and internal friction angle of shell with 69.7% had the greatest effect on the factor of safety. Also, suitable combinations of input parameters were presented and a comprehensive relationship was obtained to accurately estimate the seepage discharge and factor of safety in different modes of layer arrangement and their characteristics

In recent studies in Iran, arsenic anomalies have shown in excess of the WHO standard (10 ppb) in water resources that the use this water has irreparable effects on human health. Therefore, it is necessary to offer a solution for reducing the arsenic anomalies. In recent years, nanoparticles have been used to reduce the arsenic concentration in water resources at syntheses samples. However, the performance of these nanoparticles to reduce the arsenic concentration in groundwater resources, which generally have different complexes, has not been investigated. In this study, iron oxide nanoparticles have been used to reduce the arsenic anomalies from groundwater resources. Previous studies on iron oxide nanoparticles have been to isolate arsenic added in the laboratory, but the main challenge of this study is the separation of arsenic from groundwater sample. The results of investigation the effective various parameters such as pH, temperature, filtration time and the adsorbent amount on the separation of arsenic from groundwater showed that the highest separation is the temperature conditions above ambient temperature, low pH, time 5 to 15 minutes and the adsorbent amount 0.3 g. Finally, Sugeno fuzzy model was used to simulate and model the process of removing arsenic pollutants from groundwater sources. The fuzzy model results showed this model is very efficient for approximate prediction of arsenic adsorption by iron oxide nanoparticles with NRMSE = 0.03 and R2 = 0.8.

In this study we investigated the water quality of Khersan 2 dam, Iran, using   multivariate statistical methods. For this purpose, The monthly data of the rivers water quality parameters including electrical conductivity (EC), PH, Hco3, Ca, Mg, K, Na, Cl, CaCo3 and TDS was collected., the Principal Component Analysis (PCA) method is used to identify the main quality parameters that play more important role in changing the water quality of the Khersan 2 dam reservoir. Results of PCA analysis indicated that all the selected chemical and physical parameters of Khersan 2 dam were of high importance. Based on the studies, three factors were identified as important factors that have the greatest role in determination the variance of the data. The first factor, which has about half the impact on water quality with a percentage 55.28% of the total variance, includes Cl, Na, Mg, Ca, EC and TDS, which is completely related to the water quality and the nature of the area. The second factor consists of HCo3 and CaCo3, and the third factor is K and PH. The second and third factors are 15.14% and 10.25% of the total variance, respectively. The second and third factors are affected by the dissolution of Asmari limestone in the study area. In addition, the comparison of the chemical analysis results of the Khersan 2 dam reservoir water with the national standards and the World Health Organization has been carried out.

Water surface temperature or surface temperature in open waters and seas is known as one of the indicators for measuring oceanographic and meteorological features. In this study, to analyze the spatio-temporal Sea Surface Temperature (SST) of the Caspian Sea, the AVHRR data (0.25 Degree) were selected for the period from 1989 to 2019. Evaluation of the trend of temperature changes in the Caspian. sea water level was prepared by calculating the average monthly, seasonal and annual temperatures from daily data.The results of data analysis of SST show that 2003 with an average annual temperature of 14.7 degrees Celsius as the coldest year and 2010 with an average annual temperature of 16.56 degrees Celsius as the warmest year. Average monthly, seasonal and annual temperatures were obtained from the daily data. The results indicated that the southern parts, especially the southeastern Caspian Sea, are the warmest regions and the middle Caspian sea has a lower temperature than the other regions, although in some seasons and months, the effect of latitude prevails and the northern parts show the lowest temperatures. The annual time series of SST in the Caspian Sea have a completely increasing trend. However, from a spatial point of view, it should be said that the northern parts of the Caspian Sea have the lowest temperature and the temperatures increase with decreasing latitude to the south. The overall average surface temperature over the 30 years is about 15.6 degrees Celsius. The result also indicated that SST of the Caspian Sea it is completely increasing in terms of annuals, and in terms of seasonality and the temperatures show an increasing trend. And it shows the exact state of the image, that is, the temperature increases with increasing latitude.

Awareness of water resources quality is one of the most important requirements in planning and developing water resources and protecting it. Rivers are of particular importance as the main source of drinking, agriculture and industry needs. In this study, in order to investigate the long-term effects of temperature and precipitation from the output of the four climatic models of the fifth report (AR5) IPCC under RCP4.5, RCP6 scenarios for the base period was extracted and compared with the observational climatic data. Daily values of precipitation climatic parameters and temperature of superior models for future periods 2020-2052 and 2085-2053 were produced by LARSWG6 Downscaling method in the study area. In order to predict runoff, artificial neural network model was used in Neurosolution software. After calibration of the model in the base period of 1983-2015, the prediction was made for future periods and then in order to predict the water quality parameters of the river, the support vector regression model was used in the Python programming environment. The results showed that the amount of precipitation in CanESM2 and MIROC-ESM-CHEM models increased and decreased in the rest. Temperature increases in all models and climatic scenarios with the highest value of 3.32 °C in the next second period in the GFDL-CM3 model. The average reduction of models and climatic scenarios resulting from Neurosolution model output in the second period was 9.29% compared to the first period. Changes in the amount of discharge affected the quality parameters of the river, so the values of parameters, TDS, EC, CL, Mg Ca and the sum of anions were predicted according to the number of appropriate observational data.

Water, as a major limiting factor in production, plays an important role in determining the type of agricultural activities in Iran. The occurrence of droughts in recent decades have also threatened these activities. Today, one of the most effective responses and strategies for agricultural drought risk management is to identify vulnerable areas and determine the optimal pattern of low-water cultivation. Therefore, the aim of this study is spatial analysis of agricultural drought vulnerability and introduce a pattern of low-water cultivation and compatible with arid areas in Pishkuh watershed in Yazd province. In this research, first the dominant garden species in the study area were identified and after calculating their water requirements, a map of the agricultural drought vulnerability in the study area was prepared. The results showed that the southern to southwestern of study area, including the villages of Sanich, Darreh Shir, Darreh Sir, etc., have the highest vulnerability to drought compared to other areas. Therefore, it is recommended to be cultivated garden species with the least water requirement such as almond and Grapes with water needs of 753 and 798 mm during the growing period, respectively. Also Results showed that the central, eastern, and northwestern of study area, including Islamieh, Navab, Nasrabad villages and etc., have a moderate and relatively low vulnerability. In addition, it is recommended to plant the species with moderate-water needs such as pomegranate and apricot. Therefore, changing and modifying the cultivation pattern, such as reducing the planting areas with high water requirements, developing species with low water needs, and increasing water efficiency, is one of the most necessary activities for managing agricultural drought risk.

The concept of virtual water has considerable potential to help improving water management, especially in the agricultural sector. Therefore, virtual water analysis of basic products of the agricultural sector can help us in policy-making and planning in the optimal use of water resources. In this study, the amount of virtual water and its related indicators were determined using the basic approach and then, based on the amount of production and demand of the province for agricultural products, the amount of agricultural exchanges and the trade balance of virtual water in Hamadan province in 2018 were estimated. The results showed that the trade flow of the studied products has a volume equal to 924.7 million m3 of virtual water exports outside the province and 33.4 million m3 of virtual water imports into the province. Based on this, the trade balance of virtual water was estimated at 891.3 million m3. These results show that Hamedan province produces and exports water-intensive products within the province. The positive and significant trade balance warns of the need to change the cultivation pattern in the province due to the lack of water resources. According to the results of the study, it is suggested that the area under cultivation of crops such as corn, beans and alfalfa with high virtual water content be reduced and crops such as fodder corn and sugar beet, which require less virtual water, be replaced.

The accurate prediction of soil water movement and root uptake are very important to provide optimal root zone moisture conditions for increasing plant yield. In this study, soil water movement and sugar beet root uptake were simultaneously simulated, using HYDRUS 3D software, and the effect of extraction methods of input parameters on the accuracy of simulation were evaluated. For this purpose, sugar beet was cultivated in three lysimeters with identical soil texture. Irrigation was performed twice a week (8 on Sunday and 16 on Wednesday). Volumetric water content and drainage water volume from lysimeters were measured before and after each irrigation, respectively. The volume of drainage water from the lysimeters at different times, was selected as objective function. Using measurement, calculation or simulation, the hydrus 3D software input parameters including initial moisture (with two methods), saturated moisture (with three methods), residual moisture (with two methods) and saturated hydraulic conductivity (with two methods), extracted and simulation were completed. The results showed that if the residual moisture derived from measurement (by pressure plate method), saturated moisture derived from RETC software, initial moisture derived from measurement (measured by weighing method) and hydraulic conductivity derived from Rosetta software, were used in the simulation, the simulation accuracy will be highest. The values of relative error, root mean square error, mean absolute error, geometric mean error ratio and coefficient of determination are 17.58%, 0.759 liters, 0.866, 0.777 and 0.885, respectively. Values of GMER parameter, also, showed that in most simulations the model is underestimated.

The purpose of this study was to evaluate the environmental risks of Alborz Dam on Babolrood River in Babol city, using MCDM methods. First, the environment of the study area was identified, then a list of identified environmental risks was prepared in the construction and exploitation phase, and in the form of a questionnaire was provided to environmental experts familiar with the Alborz dam basin. Environmental risks were rated by experts according to the Likert scoring range based on the three indicators of occurrence intensity, probability of occurrence and risk significance, then environmental risks ranking was performed using OWA method. The most important risks of Alborz dam were obtained during the construction phase: when the decision maker is risk aversion, respectively: Destruction of forest within the dam with a score of 0.048, Displacement of reservoir residents with a score of 0.047, and, When the decision maker is risky, respectively: Destruction of forest within the dam with a score of 0.051, Displacement of reservoir residents with a score of 0.050. Also, The most important risks of Alborz Dam were obtained during the operation phase: When the decision maker is risk averse, respectively: Thermal stratification of dam reservoir with a score of 0.053, Reduction of self-purification of Babelrood River with a score of 0.051, and, When the decision maker is risky, respectively: Thermal stratification of dam reservoir with a score of 0.057, Landslide with a score of 0.056.

Intensification of water crisis in Iran, due to climate and environmental factors, inappropriate management of water resources management over the past three decades, the excesive use of surface water and underground water has seriously threatened the country's water resources availability. In the present study, the status of the water crisis in Iran provinces was first examined using Water Steress Index (WSI) and Falkenmarkwater stress indicators. In the next step, by assessing the sixth development plan of the Islamic Republic of Iran and the legal provisions that directly and indirectly relate to water governance, the Water governance condition was analyzed using the network analysis method.The results of this study indicate that, according to the WSI index, in most of the country's provinces, in terms of water resources consumption, they are in medium to high levels. Also, according to the Falkenmarkindex, most of the country's provinces located in critical condition from the point of view of water crisis to absolute deficits.On the other hand, the results indicate that the water governance system in the country continues to be hierarchical, with a top-down approach focused on the power of government. Definitely, in the sixth program of development of the existence of Non-governmental organizations (NGOs) and paying attention to organizations with public participation is a positive and promising point in the issue of water governance. But more attention should be paid to NGOs in the water resources management, and define more legal duties and obligations for these institutions.

The Lake Urmia has been experiencing intensive environmental degradation characterized by the enormous reduction of the lake area and water table. This has been mainly related to land use/cover changes, agricultural activities expansion and intensification. As land use changes is of the most important factors having effects on this system alterations, transitions between different land use classes and their effects on ecosystem services and goods have been considered using ecosystem services assessment matrix on the basis of experts advising approach. The results indicate that the lake area has been decreased from 4946.3 in 1987 to 2147.87 km2 in 2016 (50%) which is due to two times agricultural lands area expansion and 1538.43 km2 increase in comparison with the year 1987. Bare land and urban areas expansion is also considerable in the mentioned time period. In such conditions, although increasing ecosystem services supply such as two times agricultural products increase and water supply to 1.5 times in 1987-2016, the supply of other ecosystem services remained constant or have declined. According to the spatial hotspots studied in the lake basin, ecosystem regulating and cultural services as well as biodiversity mainly decreased at the shorelines of the lake, while provisioning services increased along the major rivers and close to cities. In this regard, understanding and studying the causes of this phenomena in a natural ecosystem would assist valuable landscapes conservation via spatial planning tools especially in sensitive and fragile ecosystems.

Water supply is one of the basic and unavoidable needs in the natural cycle and human activities. The increasing development of the southern shores of the Caspian Sea on the one hand and the production of some strategic products with high water requirements such as rice, has led to attention to the issue of water supply, especially in agriculture, drinking and industry. Due to the limited fresh water resources available, desalination of Caspian Sea water is considered as a potential solution to replace water in this region. This study was conducted to investigate the possibility of utilizing desalination technology and identifying suitable locations for the construction of desalination plants in the Caspian Sea by multi-criteria AHP analysis method and considering the capacity and environmental potential of the southern coast of this sea in Mazandaran province. The results of this study, which was carried out with the approach of assessing the environmental effects of desalination in the Caspian Sea, have shown that 30% of the coast of Mazandaran is suitable, 34% unsuitable and 20% relatively suitable for the construction of desalination units. This study emphasizes the issue of desalination sewage management in the location and design criteria of units on the southern shores of the Caspian Sea and considers the use of modern saline sewage management methods to increase the capacity and environmental capacity for desalination of Caspian Sea water

It is very important to study and simulate the transfer of environmental pollutants, especially leachate from waste accumulation in landfills. The aim of this study was to trace and simulate the path and depth of leachate transfer at downstream of Landfill using special electrical resistivity tomography. For this purpose, at the leachate accumulation site from the landfill of Hamadan city, two special resistance tomographic profiles in the northwest and southwest parts with a length of 52 m were taken at 2 meters electrode distances with a Wenner array. The results showed that the study area is of alluvial, sandstone and calcareous formations. Also, it was found that during the profile, the pattern of diffusion and infiltration of leachate from landfill was not similar, so that in profile 1, the leachate penetrated to the end at a distance of 30 to 40 meters to a depth of 3 meters, and in other parts of the profile, no deep penetration was observed. However, in the total length of profile 2, the penetration depth has reached to 2.5 meters and in the middle part up to 5 meters and more, which indicates the nonuniformity of leachate penetration along the profile. Therefore, it was found that the use of special electrical resistivity tomography method in two-dimensional imaging of landfill leachate diffusion will be more accurate and realistic than point studies. It is suggested that in feasibility studies to determine the landfill, the use of vertical electrical sounding methods and special electrical resistivity tomography should be prioritized due to low cost in the study of the depth and area of contamination and on the other hand, the effect these pollutants should be analyzed on the quality of downstream groundwater resources.