مجله تحقیقات منابع آب ایران
سال پانزدهم شماره 1 (پیاپی 48، بهار 1398)

The reason for dissimilar behaviors of Lake Urmia (Iran) and Lake Van (Turkey) during the recent decades is one of the main challenging questions. A part of the answer can be addressed by evaluation of their land use changes as the main indicator for the role of human impacts. This issue constructs the objective of present paper. For this aim, the pixel-based and object-oriented classification approaches were evaluated for obtaining the land use maps of Lake Van basin during 1987 to 2007. The applied pixel-based methods include: Mahalanobis Distance (MD), Maximum Likelihood (ML) and Support Vector Machine (SVM); and the object-oriented method includes SVM-fuzzy. Their comparison showed better performance of the object-oriented method such that Kappa Coefficient and Overall Accuracy were 0.81 and 0.86, respectively. Then, the results were compared with a similar research work for the Lake Urmia basin which was attempted. The results revealed that that the land use of Van basin has not significantly change, while the increase of cropped lands in Van basin was only 10000 ha, it was 136000 ha in Urmia basin. The most significant change in Urmia Lake relates to orchard area by increase of 273% (3513 ha to 13120 ha), whereas it was insignificant in Van (less than 20%). Definitely, these changes can increase consumption of water and reduce inflows to Lake Urmia.

Risk assessment of structures, especially dams, has recently been one of the main topics that are considered by researchers. Risk analysis make possible to estimate uncertainties coming up from randomness of parameters in the models which are applicable in designing process. In this paper, different uncertainties along with flood and wind with various return periods segregated and simultaneously were exploited to mitigate the overtopping risk of Hajilarchay earth dam. To assess the risk in the proposed model, we used Monte-Carlo simulation (MCS) and Latin hypercube sampling (LHS) method with different iterations through system dynamics approach. The results proved the effectiveness of system dynamics approach on overtopping risk assessment for earth dams which showed the influences of different parameters on overtopping risk besides flood and wind. Furthermore, the results showed that opening the bottom outlet of Hajilarchay Dam may reduce the average overtopping risk as much as 9.20 and 4.10 percent due to just flood and due to flood and wind, respectively. In addition results showed that the average overtopping risk estimated from MCS method due to just flood and due to flood and wind were about 4.30 and 3.50 percent, respectively, more than that the results obtained by the LHS method. Also the reliability index obtained by the MCS method was higher than LHS method and MCS method has faster calculation in compare to the LHS. Finally, we can conclude that system dynamics approach along with MCS is a very effective tool to estimate the overtopping risk of earth dams.

As the most valuable natural resources, protection and management of groundwater is vital. One of the best ways to protect groundwater resources is identifying the aquifer vulnerable areas and monitoring groundwater quality spatial variations. The spatial variation of the groundwater salinity, has been evaluated in Malekan aquifer, introducing a new method, named GWQISI which has been digitally integrated of TDS, Cl-/sum Anion, Cl-/ (HCO3- + CO32-), Na+/ (Na+ + Cl-) and Ca2+/ (HCO3- + SO42-) ratios. Also, this paper presents the vulnerability mapping of the coastal aquifer system using new multi-criteria decision model as IDLRT. Five thematic layers have been created to adopt the most indicative criteria for investigating the groundwater degradation trends from saltwater intrusion. One of these layers showed the magnitude of existing status of saltwater intrusion. The other chosen layers are Recharge (R), Level of groundwater above the mean sea level (L), Distance from the shore (D) and the aquifer saturated Thickness (T). The results of sensitivity analysis, using both the map removal and single parameter methods, indicate that the Recharge (R) has the most significant impact on the vulnerability index. The groundwater vulnerability map indicates Based on the IDLRT results, about 22.15, 49.45 and 28.4 % of Malekan aquifer have very low, low and moderate vulnerability, respectively. Based on the GWQISI results, about 1.75, 4.25 and 62.4 km2 of Malekan aquifer are extermly, highly and moderately influenced by salinity, respectively. The results reveal that the northwest part is the most affected zone by salinity.

In recent years, climate change and rising global water demand as a result of population growth has caused water scarcity. In this regard, calculation of agricultural water productivity in order to optimize the management of water resources and reduce the water consumption is essential. One of the promising methods for this purpose is remote sensing. In this research, a functional and fully satellite-based model that called WATPRO was used for direct calculation of agricultural water productivity and its evaluation in the Jiroft plain located in Kerman province. For this aim, Landsat8 satellite imagery were acquired during the growing season of wheat on 2016-2017 years and after necessary image preprocessing, the WATPRO model was implemented. The deployment peak, cultivation and harvesting time for six divided field were determined by using the time series of Normalized Deference Vegetation Index (NDVI) extracted from satellite imagery, then wheat water productivity was calculated and the results were evaluated with ground control points. The results shows that the highest and lowest water productivity for wheat in this area is 0.4 and 0.8 kg m-3, respectively and the average of water productivity in the study area was estimated around 0.5 kg m-3. Also the correlation coefficient of 76.5% was found between average NDVI and water productivity in this area. Assessing the accuracy of the WATPRO model with the measured water productivity at field show that this model perform well for estimation and mapping water productivity with an RMSE and correlation coefficient of 0.16 kgm-3 and 85% respectively.

In this research, a deterministic algorithm based on the Genetic Optimization (GA) method was used to optimal water allocation from surface and underground resources between different uses in the operation of Yamchi reservoir dam in Ardabil province. The objective function in the optimized model was to maximize the profit of water allocated to the agricultural sector according to the selected cropping pattern, so that the supply of drinking and environmental requirements was considered as a constraint in the optimal model. The rainfall and inflow to the reservoir are discretized due to their non-deterministic property, and then for different values of the initial volume of the reservoir at the beginning of the operation period and any logical combination of rainfall and inflow to the reservoir (under the three scenario: minimum, normal and maximum), the optimal model was implemented. The results showed that in the minimal and normal scenario with increasing initial volume of the reservoir, the profit was increased, but in maximum scenario, the initial volume of the reservoir had no effect on the profit. The smaller the initial volume of the reservoir had the lower the relative yield of the products, which is most evident in the minimum scenario. Also, the amount of water allocated from groundwater resources to agricultural sector varies from 3.1 to 7.9 MCM, which corresponds to the potential for extracting water through utilization wells.

Water pollution has received particular attention in recent years. One of its reasons can be water scarcity or drought. One of the methods which significantly helps to manage this crisis is reuse of the effluent of wastewater treatment plants. In big cities, wastewater is usually collected by an integrated wastewater collection system and then treated in a centralized wastewater treatment plant. This approach has a lot of limitations regarding wastewater collection costs, risks of unanticipated events and treated effluent reuse. Furthermore, in less populated cities, using centralized wastewater treatment plants might be costly when concerning infrastructural and operational costs. In this situation, it is recommended in the literature to use decentralized wastewater treatment plants (DWWTPs). Therefore, it is crucial to highlight and locate communities with more potential to use this facility. This study aims to locate the communities which have the most potential to construct DWWTPs and dedicate them a fuzzy-AHP index. Based on the findings of this study, the prioritized societies with high potential to build DWWTP in Qom Province are Sarm, Vanarch, Jandab, Varjan, and Kahak. Finally, the communities under the study were compared regarding wastewater collection system costs by using WPM model. The results indicated that DWWTP was multiple of times more economical than the centralized method.

Drought monitoring is one of the main pillars of drought management. Therefore, investigators are always looking for a way to improve the drought monitoring accuracy. The main purpose of this paper is to investigate the efficiency of GRACE satellite observations in drought monitoring in the Markazi basin of Iran between 2002 and 2016. With the launch of this satellite, it has been possible to monitor total water storage anomalies (TWSA) for the entire world with high precision. Due to the significance of human activities impact on Total Water Storage Anomaly (TWSA), obtained from GRACE in the above mentioned basin, the common GRACE-based drought indices, such as Drought Severity Index (DSI), has not been efficient in this basin. Therefore, in this paper the newly Modified Drought Severity Index (MDSI) is introduced based on de-trended TWSA time series. Also, both Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were used, as the criteria to assess the performance of DSI and MDSI. The results showed that the correlation coefficient between DSI and SPI12/SPEI12 were equal to 0.42/0.26, while these values for MDSI were equal to 0.69 and 0.56, respectively. Calculated MDSI time series revealed that during the studied period, the most severe and longest drought occurred in the years 2008-09. During this period the basin faced with a deficit of 238 km3. On the basis of maximum and average rate of deficit changes in the basin, at least 21 and on average 91 months is needed for recovery of this deficit.

This paper examines the role of shared water resources in establishing territorial cooperation. To do so, the Abarkooh basin which lies on the border between the Yazd and Fars provinces has been singled out as our case study. Across this basin, the upstream and downstream villages all exploit a common groundwater reserve. Until the late 1970s, the exploitation of the common groundwater took place based on a systematic relationship between the basin’s upstream and downstream, which was associated with geographical distribution of vital resources and livelihood differentiation. However, the traditional cooperation has turned into competition and social tension, which contribute to the destruction of their shared water resource. This study has deployed the research method of grounded theory in order to answer the questions: how the shared water resource can serve as the groundwork for systematic interaction and cooperation, and under what conditions such systematic interaction may turn into a competitive confrontation. According to our field studies, the geoghraphical difference between the basin upstream and downstream led to the different possibilities accessed by the human communities in both areas. The same different possibilities gave rise to the creation and development of different economic systems under a condition to which we refer as livelihood differentiation. Livelihood differentiation in turn paved the way for the cooperative exploitation of the shared water resources. However, over the past decades, the exogenous socio-economic programs along with the climate change impaired the livelihood differentiation so that the traditional cooperation was replaced by competition.

One of the long-term goals of strategic management at the country is to balance between water supply and demand at the lowest cost. Water supply and demand management is one of the tools to achieve the efficient allocation of water resources. Dynamic water pricing is a very effective tool for managing demand. Since environmental conditions (economic, cultural, social, and political) are sometimes contradictory and complex, water pricing is a complex issue. In the current issue of dynamic water pricing with the aim of balancing supply and demand in villages by using the dynamics of the simulation system, and using validation tests, simulation accuracy was evaluated in a case study. In different scenarios during the ten years from 2020 to 2029, the future status of water resources and balance between supply and demand were examined. The use of dynamic pricing and revenue from it, culture building and infrastructure reform was the prevailing scenario. According to this scenario, adding additional resources or rationing in the village of Akramabad will not be required until 2029.

In this study, a new framework is developed for determining an optimized crop pattern and water pricing for agricultural use. to do this, two different approaches have been taken. In the first approach, determination of the crop pattern and price of water is carried out using an optimization model with the objective of maximizing the benefit of the regional water company, which is in charge of selling water to agricultural sectors, based on a leader-follower concept. In the second approach, the optimized crop pattern and water price are determined using an optimization model with the objective of maximizing the Nash product of benefits of agricultural sectors. In both approaches, the problems solved considering a local water market between agricultural sectors. The developed approaches are applied to a case study of five neighboring farms in the Mahyar Plain, Isfahan. Based on the results of the first approach considering a local water market, the optimal price of selling one cubic meters of water by the regional water company to the farmers would be 2490 Rials and the price of selling water in the market would be 5250 Rials. The values of average annual benefit of the regional water company and farmers are higher than those gained for the case of not having a local water market. In the second approach, selling one cubic meters of water at 2500 Rials by the regional water company and 6300 Rials in the local market give the highest average annual benefit for both water company and farmers.

After discover of flocculation process in estuaries, there was a significant change in calculation of dissolved metals load entering sea and other saline water environments through rivers. In other words, due to mixing of fresh and saline water in an estuarine zone, a significant amount of heavy metals flocculate and settle in the estuarine zone. In the present research, the flocculation process of heavy metals in Shfarud River is investigated during estuarine mixing with Caspian Sea water. Results indicated that that Cd, Cr, Co and Ni lose their initial load by 86, 74, 62 and 52 percent, respectively. Furthermore, an updated method, which is considered as one achievement, was used to simulate the estuary in this research. Actually, it is showed that flocculation process could be a reversible process. In other words, due to continuous chemical and physical change of estuary environment, flocs of metals might return to dissolve phase.

Among the meteorological components, because of having considerable changes in time and space, precipitation is one of the complicated issue in hydrological process. By increasing of satellite-based technologies over the past decades, that’s easy to access to high resolution precipitation products in most parts of the world. This research addressed the accuracy of European Center for Medium Range Weather Forecasts (ECMWF) reanalysis datasets for estimation of daily and monthly precipitation over the SefidRood catchment. Moreover, in order to better evaluating the performance of ECMWF dataset, the PERSIAN and TRMM datasets are used. Findings on daily time scale, show that the correlation coefficient between ground observation and ECMWF, PERSIAN and TRMM products is about 0.8, 0.47 and 0.32 and this completely prove the superiority of ECMWF for estimation of rainfall at daily time scale. At monthly time scale, both of ECMWF and PERSIAN products correlate very well with gauges measurements (CC statistic is more than 0.9), but TRMM owing to have CC equal to 0.57 correlates moderately with observations. According to the categorical verification statistics, ECMWF yields better results for detection of precipitation events on the basis of Probability of Detection (POD), Critical Success Index (CSI) and False Alarm Ratio (FAR) in SefidRood catchment, compared with other satellite data sets. Therefore, in ungauged catchments or hydrological modeling that require an accurate precipitation datasets, using ECMWF dataset is suggested.

Due to the lack of proper spatio-temporal coverage of precipitation measuring stations in the country, there is a need for gridded data with proper spatial and temporal resolution. For this reason, global rainfall centers were used in water resources studies. In recent years, the number of these gridded datasets has been increasing and many of these datasets have been used in water resources studies. In this research, rainfall datasets have been evaluated in both pixel scale and mean basin with observation data in the Karoon basin. The datasets used in this study are PERSIANN, PERSIANN-CDR, APHRODITE, TRMM-3B42 RT, CHIRPS V2.0, ERRA-INTERIM. Evaluations were made on a daily scale and for the period of 2003-2013. According to the results of statistical indices such as coefficient of determination and NRMSE, the APHRODITE and ERRA-INTERIM datasets have shown better performance than others. Also, according to the contingency table indicators, the APHRODITE and ERRA-INTERIM datasets have good performance. The results showed that despite the fact that the APHRODITE and ERRA-INTERIM datasets have the proper accuracy in all evaluations, they have poor performance in detecting non-occurrence of rainfall. According to the evaluations, the APHRODITE dataset can be used as an alternative to observational data and among satellite datasets, Among the satellite datasets, TRMM has better performance, and with calibration and bias correction using observational data, this satellite can be used in water resources studies for the target area.

Hirmand River is the main drainage system in the southern part of Afghanistan and has a significant impact on the socio-economic life of Sistan region. The assessment of water potential of Hirmand River is essential for long term period, which requires the use of rainfall-runoff model. The present study focuses on simulating the daily discharge of the upper Helmand basin of Afghanistan using the conceptual model FLEX in combination with multi-objective optimization, which has not been considered in previous studies. At first, the discharge was evaluated integrally by lumped model considering one objection function. Then it was simulated using semi-distributed model by adding the logarithm of the flow to the objection function. The results of this study indicates that the model is efficient in the semi-distributed mode by using two objection functions for calibration of parameters. The coefficients of NS, NS-log in the calibration and validation period were estimated to be 0.86, 0.92, 0.76 and 0.81, respectively. Pareto front analysis gave the best optimum set for each parameter used in model simulation. The model gives satisfactory results based on monthly calibration and can be used to investigate the drought and climate change research of studied basin.

The purpose of this research was determine factors affecting the sensitivity of eastern regions of Lake Urmia basin to water crisis (68 regions). Required data were collected by using survey and documentary data and after a series of steps, sensitivity was calculated to obtain the average of that at each of the studied regions. Based on results, three classes of sensitivity were recognized: Low, moderate, and high. In the other words, 51.47% of the basin regions have a high sensitivity to the lake crisis and 23.52% are less sensitive to this crisis and the other regions have a moderate sensitivity to the Lake Urmia water crisis. Also, the results of one-way ANOVA analysis showed, studied regions have difference in the terms of variables such as: unemployment rate, farmer’s literacy level, less distance from the lake than other region and the number of illegal wells. The results of this study have implications for to national and regional Urmia Lake Restoration Program. The limited resources should focus on drought sensitive regions for increasing adaptive capacity and sustainable development building in the study regions.

Extensive available hydrological characteristics (precipitation, temperature, streamflow data and physiographic attributes of catchments) can be used to extract hydrological similar catchments. In this research cluster analysis as a new and effective method, was used for grouping catchments into several groups or clusters. In order to understanding the hydrologic similarity, 28 characteristics (descriptors) of location, physiographic, climatic and land use of 15 catchments with heterogeneous characteristics located in the western part of the Hamoun-Jazmourian river basin were used. Selecting of characteristics were done based on the hydrological response specification which provided insight into the hydrologic performance of the catchments. In RStudio software, using PCA algorithm, the components and main characteristics were extracted, then the number of optimum clusters with the Davies-Bouldin criterion was determined and the clustering of the catchments into homogenous classes was performed using k-means algorithm. The results showed that the latitude of gravity center, area, length of main river, height of hydrometric gauge, slope and percentage of poor rangelands are as the main attributes from 28 attributes, also, the Davies-Bouldin criterion was 2.46 for the number of clusters equal to 3, which indicates the number of clusters in the k-means algorithm. After clustering the catchments, it was determined that most of the catchments in the same clusters are located in the vicinity of each other. The results of this study enable us to interpret the hydrologic behavior in the study area for purposes such as streamflow regionalization in ungauged catchments of this region and regional flood frequency analysis.

Among different types of natural disasters in the world, floods, especially flash floods, are known as the most devastating hazard which cause serious damages and human deaths in residential areas. Importance of estimating the maximum possible number of fatalities due to flash floods in urban watersehds, in order to consider appropriate management plans to reduce the number of fatalities, is undeniable. Implementing some global equations in Kan watershed, located in the north of Tehran, led to this conclusion that their accuracy for estimating the number of human fatalities is not enough and developing a regional relationship is essential. In this study, using hydraulic parameters such as depth and velocity, a regional and comprehensive equation was developed to estimate loss of life due to flash flood in residential areas. Comparing the outcomes of the developed regional equation with the previously presented global equations showed that the proposed equation provides more accurate estimation of the number of fatalities in the study area. Finally, it can be concluded that in spite of existence of general relationships to estimate flash floods fatalities, developing a regional equation will be more accurate and practical for the watersheds with high flood fatality potential.

The economic effects of large dams that were constructed during recent two decades in Iran are explored in this paper and their effects on agriculture and welfare of their own district and downstream districts are analyzed. Ordinary least squares (OLS) method is used to investigate these effects and for more accurate results, we control for geographical variables and rainfall. The results of this study show that dam construction leads to higher agricultural yield, production value and irrigated area in dam’s own district; but it doesn’t affect yield, production and irrigated area in downstream districts. Also dam construction results in planting more water-intensive crops in their own district and less water-intensive crops in downstream districts. In addition, per capita expenditures in rural regions of downstream districts decrease in response to dam construction in upstream districts, but urban regions of the downstream district and also urban and rural regions of their own district are not influenced by dam construction.

The proper estimation of evapotranspiration in designing, managing irrigation and drainage systems is very important. One of the methods of estimation of evapotranspiration, which is widely used in solving these problems and its prediction, are Neuro-Fuzzy Methods (ANFIS), Artificial Neural Networks (ANNs) and decision making tree M5. The purpose of this study was to evaluate the efficiency of the mentioned methods in estimating the reference evapotranspiration in the Shiraz meteorological station. For this purpose, the 5 yearly climatic data of the station were selected as inputs of the models. To implement artificial neural network model, Nero fuzzy model and decision tree M5 were used respectively from Qnet2000, MATLAB and WEKA software. In order to evaluate the results of these models, the mean squared error (RMSE), coefficient of determination (R2) and the criterion of the mean power of relative error (MAE) were used. The results of Artificial Neural Network model and ANFIS model with the help of statistical indices R2, RMSE and MAE were 0.0999, 0.099, 0.0500 and 0.0999, 0.051, and0.01119, respectively the accuracy of both models in simulation is high. Also, the correlation coefficient (R2), RMSE and MAE of decision tree model were calculated to be 0.7064, 0.0935 and 0.0414 respectively, which indicates the proper performance of the M5 tree model in predicting the reference evapotranspiration rate.

Evapotranspiration is one of the key components of the hydrological cycle and its quantification is essential to understand the processes such as vegetation phenological changes, environmental hazards such as floods and droughts, and, in general, the ecosystem water balance. The use of remote sensing methods based on surface energy balance has been increased to estimate evapotranspiration. The purpose of this study was to estimate the evapotranspiration of corn based on integration of Landsat 8 and MODIS satellite images using the SEBAL algorithm in in Mahidasht, Kermanshah province. Linear with Zero Intercept (LinZi) method was used to integrate satellite images. Also, actual evapotranspiration of corn in 15 farms in the study area was estimated based on ground data. The results of the SEBAL algorithm were compared with ground-based evapotranspiration using MAE, BIAS and RMSE indices. The results indicated that the combination of satellite images has led to an improvement in the accuracy of estimated evapotranspiration compared to Landsat 8 images. The mean absolute error of estimated evapotranspiration during the growth period was determined as 0.44 and 0.42 mm.day -1 respectively based on Landsat 8 and combined images. In general, the results of this study showed that the estimation of evapotranspiration using the SEBAL algorithm and based on the integration of satellite images with different spatial and temporal resolutions could have acceptable results.

Precipitation is a major component of the hydrological cycle, which has significant changes in location and time. The lack of suitable data for this parameter causes a problem in hydrological forecasts. Since satellite data provides a new solution for estimating rainfall with spatial and temporal variation, this study evaluate the accuracy of some of these data types, including high-resolution spatial data consist of ERA-Interim, CHIRPS and PERSIANN-CDR at the upstream of the Maroon Dam on daily, monthly and annual timescales. In order to evaluate gridded precipitation data and observational data from 2003 to 2014, it was considered. The results show that estimation of the annual rainfall data of the gridded precipitation models is underestimated and estimates the average annual precipitation less than the mean annual observational precipitation. In the estimation of monthly precipitation with regard to the Nash-Sutcliff coefficient at Dehno, Idenak and Margoon stations, the ERA-Interim model and at the Ghale-Raeesi station CHIRPS model indicate the best performance compared to other models. In the daily rainfall estimation, like the monthly rainfall, the best estimate at the Idenak station is the ERA-Interim model, which has a NSE of 0.63 and the best estimate of precipitation in all stations is by ERA-Interim. ERA-Interim has the best performance from the 3 gridded models in the correct detection of rainy days. The best performance of this model is in determining the correct rain days with POD = 0.53 at Idenak station.

In this paper, a multi-objective simulation-optimization model for reservoir selective withdrawal considering different releases scenario and model Fusion method is developed, NSGA-II model, CE-QUAL-W2 model and validated model Fusion method are developed to determine the quality of reservoir releases from outlets. To generate possible reservoir releases as well as automatic running of calibrated CE-QUAL-W2 model for different possible scenarios, two codes are developed in MATLAB® software, separately. The main objectives function of this study are minimizing difference between reservoir water releases and different demands of stakeholders, maximizing Iran Water Quality Index of outlet water and the reservoir storage. Based on this methodology, the input-output data sets of simulation model are saved and utilized for training and validating the MLP, GRNN and RBF Meta models. The Ordered Weighted Average is used for fused the meta-models and for determining the model weighted is used Orness method. Then, the validated Meta model is linked to NSGA-II model to determine the objectives. For obtaining an appropriate solution considering different involved stakeholders on the pareto front, Nash theory and different social choice rules method are used. At the end, the fallback bargaining theory is used to choose the best reservoir selective withdrawal solution.

During the past decades, Tehran has suffered from subsidence crisis. Prolonged droughts and excessive exploitation of groundwater for agricultural and industrial purposes have reduced the level of aquifers and reduced the density of the subsurface soil layers. This study focuses on monitoring the displacement of the ground in west of Tehran which is affected by subsidence of Shahriyar and Tehran plains. A time series of 30 Sentinel-1 images were processed by radar interferometry technic based on the persistent scatterers in two years. Average annual displacement map was prepared for the region of study. The result of study indicates 15 centimeters of displacement in southern part of the study area where it ends to Shahriyar and Tehran plains. However, displacement is not limited to plain and non-urban areas. It has also scattered through industrial and urban areas. In industrial and residential areas, cumulative displacement of 9 to 13 centimeter was recorded in two years especially in Fath Highway which experiences more than 4 centimeters of displacement each year. Relative evaluation of results was made based on the data gathered from underpass 35. Considering the small difference in the estimates obtained from orbits 28 and 35, these areas had little Horizontal displacement. Displacement vector was high in vertical movement. Vertical displacement was computed for ascending and descending orbits in the second study region and verified by data from a GPS station.

Groundwater as a source of drinking water is very important in coastal aquifers. Groundwater vulnerability maps can be used to protect the quality of groundwater resources. Therefore, in this study, GALDIT model was applied to assess and determine vulnerable areas to seawater intrusion in Gharesoo-Gorgan Rood coastal aquifer. The GALDIT model is a type of the rating models and needs to be calibrated in each study area. The novelty of this study is to use the Fuzzy Logic model to modify the GALDIT model. In addition, the weights of this model were modified by Analytical Hierarchy Process (AHP). Then, the pearson’s correlation coefficient was used to validate the results. Correlation coefficient between Fuzzy-AHP and GALDIT-AHP models with TDS concentration was 0.63 and 0.51, respectively. As a result, the optimal model for the study area is the Fuzzy-AHP model. The results of the vulnerability map indicate that the northwest and west of aquifer areas are highly vulnerable to the seawater intrusion. The Fuzzy Logic model can be used as an effective way to modify the GALDIT model and ensure its results.

In this research, we obtained mean values of -2.9‰ to -6.6 ‰ for δ18O and -14.4 ‰ to -31.6‰ for δ2H for precipitations of Pol-e-Zahab area. The Pol-e-Zahab meteoric water line (δ2H = 6.6*δ18O + 12.1) represents high deuterium excess (12.1‰) and elevated values of d-excess of rainwaters from SarpoleZahab, Qasr-e Shirin and Kerend weather stations (between 8.7‰ and 20.9‰) confirms the impact of Mediterranean atmospheric water vapor. In Pole Zahab study area, the isotopic composition of the ground water resources has less variation than that of rainwaters. The mean values of the isotopic composition for the groundwater (alluvial and karst) ranges between -3.5 ‰ and -8.6 ‰ for δ18O and between -2.29 ‰ and -6.36 ‰ for δ2H. In general, karst water isotopic composition (δ18O and δ2H) in the study area has less seasonal variations, which indicates the existance of sufficient time for mixing of infiltrated water with water in saturated zone and in turn indicate high groundwater residence time in formation. The least isotopic seasonal variations were observed in largest karstic springs of the region, including Srabgrm, Ghaleshahin, Gharebolagh and Ryjab springs. Consequently, the water of these springs have the greatest residence time in formation and in turn high relative age of water. Around Marab karstic spring, development of karst channels and faster flowing of groundwater resulted in less residence time and low relative age of water.

Snow cover in mountainous basins is known as an important and reliable fresh water resource. Due to the physical conditions of the mountainous environments, it is believed that snow can measurement is still challenge based on traditional methods and techniques. In order to deal with this issue, remote sensing satellite images can be considered as efficient method for identifying snow covers and computing their depth and volume. Within the current research, the Landsat 8 satellite images were employed to detect snow cover surface for the Yamchi basin using NDSI indices and object based image analysis methods. The ground control points were applied to compute the accuracy of results while the overall accuracy was computed to be about 90%. In order to measure the snow cover depth and compute water discharge, the Sentinel A1 and D-InSAR satellite imagery were employed. In context of detection snow cover using Landsat 8 images, the satellite images for September indicated no snow cover for the study which accordingly employed as basic data for comparing against winter season satellite images and accordingly computing the snow cover and depth using the interferometry approaches. The results were verified by ground data.The correlation coefficients were computed to be about 85%. With confidence in the accuracy of the maps, the snow volume was also obtained through surface and snow depth maps. Accordingly, the correlation between snow depth of ground control points the obtained snows depth from differential radar interference were employed to compute water discharge of the study area.

The optimization of the Muskingum method coefficients is important for increasing the accuracy of the method. One of the main problems of this method is the estimation of the outflow rate at the time of flood initiation, which is usually equal to the inflow rate at the same time. In this study, due to the uncertainty of the equilibrium of the outflow rate at the time of flood initiation with the inflow rate at the same time, using the Particle Swarm Optimization (PSO) algorithm, in addition to calculating the coefficients of the linear Muskingum method (X, K), the outflow value in The flood initiation time is optimized in proportion to the amount of inflow at the same time, and then calculated using the calculated coefficients and the entered outflow rate is utilized using a flow that is considered as flood observations to calculate the flood outflow Other related items can be used at the same hydrometric stations. The accuracy of this method has been increased using the proposed solution in this research.

Near the most of real-world decision-making issues, especially in the water resource management area, are multi-objective issues that are taken based on different and conflicting goals. Due to the wide range of application of these issues, different models have been proposed to solve them, NSGA-II and MOPSO are the most important of these multi-objective optimization models. The purpose of this study is to compare the performance of NSGA-II and MOPSO algorithms in solving multi-objective optimal operation of a hydropower reservoir. Due to the fact that the hydropower reservoirs are involved in providing the peak load of the network electricity, a neural network to predict daily energy prices in peak hours was developed initially, then the results were used to optimize the multi-objective operation of Karun 5 Dam reservoir, includes two goals of maximizing annual income and maximizing minimum daily energy production. Although the run time of the NSGA-II method is about twice as high as the MOPSO, the precision of its results is 20% better for both purposes than MOPSO.

Water scarcity is now one of the most critical challenges in most countries around the world, especially in Iran. One of the key ways to control and manage this issue is the investigation of the water demand. Qom city has always been encountered with a threat due to its location in the dry area of the country and in the absence of proper management in the near future, there will be serious dangers in this field. The purpose of this thesis is investigation of water demand dynamics from method of system dynamics in Qom city. Dynamic of various variables such as population, water demand, surface water resources, ground water, water supply in this model has been used by Vensim software. The maximum relative difference (%) of this model for estimation of water demand was found to be 7%. The change of birth rate from 4% to 2% resulted in 29% reduction of water demand level in 1405 compared with current trend. . Base on this result, the policy of population control had the most important effect on water demand. The price effect on water demand is negligible, so that, 20% increase of price leaded to 2.04% reduction in level of water demand in 1405 compared with current trend.