IRAN-WATER RESOURCES RESEARCH
Year:2019 | Volume:15 | Issue:1 |Papers Count:31

One key question in restoration of Urmia Lake is to investigate the difference between the behaviors of Urmia Lake (Iran) and Van Lake (Turkey). Land use change is one of the most important factors which can show the role of human activities in Urmia Lake desalination. The main objectives of present papers are: (a) comparison of pixel-based and object-oriented classification approaches (includes Mahalanobis Distance (MD), Maximum Likelihood (ML) and Support Vector Machine (SVM) and SVM object-oriented methods) for determination of land use changes in Van basin during 1978-2007 and (b) comparison the process of land use changes in both Urmia and Van basins. The results showed that the accuracy of object-oriented classification method (Kappa Coefficient: 0. 81 and Overall Accuracy: 86) is higher than the other pixel-based methods. The results showed that the land use of Van basin has not been significantly changed, while its change in Urmia basin was dramatic. Based on results, the cropped lands in Urmia basins increased by 136000 ha, while this increase in Van basin was only 10000 ha. The most significant change in Urmia Lake is related to orchard area by 273% increase in comparison with that in 1987. This change in Van basin is inconsiderable.

Risk assessment of structures, especially dams, has recently been one of the main topics considered by researchers. Risk analysis makes it 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 in assessing the overtopping risk for earth dams which showed the influences of different parameters besides flood and wind on overtopping risk. 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 when incorporating the effects of just flood and flood and wind, respectively. In addition results showed that the average overtopping risk owing to just flood and to flood and wind estimated from MCS method were respectively about 4. 30 and 3. 50 percent more than corresponding results obtained by the LHS method. Also the reliability index obtained by the MCS method was higher than LHS method and MCS method has less calculation time compared to the LHS. Finally, we could conclude that system dynamics approach along with MCS is a very effective tool to estimate the overtopping risk in 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 digitally integrated TDS, Cl-/sum Anion, Cl-/ (HCO3-+ CO3 2-), Na+/ (Na+ + Cl-) and Ca2+/ (HCO3-+ SO4 2-) ratios. Also, this paper presents the vulnerability mapping of the coastal aquifer system using new multi-criteria decision model of IDLRT. Five thematic layers have been created to adopt the most indicative criteria for investigating the groundwater degradation trends from saltwater intrusion. These layers included the magnitude of existing status of saltwater intrusion, 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, indicated that the Recharge (R) has the most significant impact on the vulnerability index. The groundwater vulnerability map based on the IDLRT results, indicated that about 22. 15, 49. 45 and 28. 4 percent of Malekan aquifer has 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 revealed that the northwest part is the most affected zone by salinity.

In recent years, climate change and rising of global water demand as a result of population growth has caused water scarcity. In this regard, calculation of agricultural water productivity is essential in order to optimize the management of water resources and reduce the water consumption. One of the promising tools for this purpose is remote sensing. In this research, a functional and fully satellite-based model 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, Landsat 8 satellite imagery was acquired during the growing season of wheat on 2016-2017 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. Wheat water productivity was then calculated and the results were evaluated with ground control points. The results showed 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 about 0. 5 kg-m-3. Also the correlation coefficient of 76. 5% was found for correlation between average NDVI and water productivity in this area. Assessing the accuracy of the WATPRO model with the measured water productivity at field showed that this model perform well for estimation and mapping of water productivity with an RMSE and correlation coefficient of 0. 16 kg-m-3 and 85%, respectively.

In this research, a deterministic algorithm based on the Genetic Optimization (GA) method was used for optimal water allocation to different uses from surface and underground resources 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, and the supply of drinking and environmental requirements were 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 the 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 the lower the relative yield of the products, which was 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. Among its reasons can be the water scarcity or drought. One of the methods which significantly help 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 lots 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 such facility. This study aimed to locate the communities which have the most potential for construction of 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 constructing DWWTPs are multiple of times more economical than the centralized approach.

Drought monitoring is one of the main pillars of drought management. Therefore, investigators are always seeking ways to improve the drought monitoring accuracy. The main purpose of this study was 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 GRACEbased 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 respectively equal to 0. 42 and 0. 26, while these values for MDSI were equal to 0. 69 and 0. 56. Calculated MDSI time series revealed that during the studied period, the most severe and longest drought occurred in 2008-09. During this period the basin faced a water 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 of Yazd and Fars provinces has been singled out as the case study. Across this basin, all the upstream and downstream villages exploit a common groundwater reserve. Until late 1970s, the exploitation of the common groundwater took place based on a systematic relationship between the basin’ s upstream and downstream communities, 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 the 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 opportunities accessed by the human communities in each area. These different opportunities 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 nation-wide strategic management at the country is the 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 and in this regard 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 study, the issue of dynamic water pricing is investigated with the aim of balancing supply and demand in villages using the dynamics of the simulation system. The simulation accuracy is examined using validation tests for a case study. In different scenarios in ten years from 2020 to 2029, the future status of water resources and balance between supply and demand are examined. The use of dynamic pricing and revenue from it, culture building and infrastructure reform was the prevailing scenario. Based on this scenario, no additional resources or rationing would be required until 2029 in the village of Akramabad.

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.

Once the flocculation process was discovered in estuaries, there was a significant modification in calculation of dissolved metal load from rivers entering sea and other saline water environments. It was learnt that 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 Shafarud River is investigated in estuarine mixing with the 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, considered as an achievement to this research, was used to simulate the estuarine metal load. It showed for the first time that flocculation process could be a reversible process. In other words, due to continuous chemical and physical changes of the estuary environment, flocs of metals might return to dissolved phase.

Among the meteorological components precipitation is one of the complicated issues in hydrological process, due to its considerable changes over time and space. By increasing application of satellite-based technologies over the past decades, it is now easy to access 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 also used. Findings on the daily time scale showed that the correlation coefficient between ground observation and ECMWF, PERSIAN and TRMM products was respectively about 0. 8, 0. 47 and 0. 32 and this proved the superiority of ECMWF for estimation of rainfall in daily time scale. On monthly time scale both ECMWF and PERSIAN products correlated very well with gauge measurements (CC statistic is more than 0. 9) but TRMM with the CC equal to 0. 57 correlated moderately with observations. According to the categorical verification statistics for SefidRood catchment, ECMWF yields better results compared with other satellite data sets, for detection of precipitation events on the basis of Probability of Detection (POD), Critical Success Index (CSI) and False Alarm Ratio (FAR). Therefore, in ungauged catchments or for hydrological modeling which requires an accurate precipitation dataset, using ECMWF dataset is suggested.

Due to the uneven spatio-temporal coverage of precipitation over Iran and using rain gauge stations to measure rainfall, there is a need for gridded data with proper spatial and temporal resolution. For this reason, global rainfall data centers are being used in water resources studies. In recent years, the number of these gridded datasets increased and many of them 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 Karoun basin as a case study. The datasets used in this study were 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 ERRAINTERIM 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. Among satellite datasets, TRMM had 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 socioeconomic life of Sistan region. Long term assessment of water potential of Hirmand River requires the use of rainfall-runoff model. The present study focused on simulating the daily discharge of the upper Helmand basin in 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 objective function. Then it was simulated using semi-distributed model by adding the logarithm of the flow to the objective function. The results indicated that the model is efficient in the semi-distributed mode by using two objective functions for calibration of parameters. The coefficients of NS, NS-log in the calibration period were respectively estimated to be 0. 86, 0. 92. They were estimated in validation period as 0. 76 and 0. 81, respectively. Pareto front analysis gave the best optimum set for each parameter used in model simulation. The model gave satisfactory results based on monthly calibration and can be used to investigate the drought and climate change research in study basin.

The purpose of this research was to 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 then the sensitivity of each region to water crisis was calculated. Based on the results, three classes of sensitivity were recognized: low, moderate, and high. In other words, 51. 47% of the basin regions have a high sensitivity to the lake crisis, 23. 52% are less sensitive to this crisis, and other regions have a moderate sensitivity. Also, the results of one-way ANOVA analysis showed studied regions are different in the terms of variables such as: unemployment rate, Education less distance from the lake 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 in the study regions.

Extracted hydrological similarity, derived from the catchments’ similar reaction to the input rainfall, is the basis for classification of catchments for the transfer of information, hydrological understanding and as well as understanding the potential impacts of environmental changes. 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 understand 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. Selection of characteristics was done based on the hydrological response specification which provided insight into the hydrologic performance of the catchments. The components and main characteristics were extracted in RStudio software, using PCA algorithm and then the number of optimum clusters was determined against the Davies-Bouldin criterion 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 the main attributes out of 28 attributes. Also, the Davies-Bouldin criterion was 2. 46 for the number of clusters equal to 3, which indicated 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 and especially flash floods, are known as the most devastating hazard which cause serious damages and fatalities in residential areas. Importance of estimating the maximum possible number of fatalities due to flash floods in urban watersehds is undeniable in order to consider appropriate management plans to reduce the number of casaulties and lives lost. Applying some global equations to Kan River watershed, located in the north of Tehran, led to this conclusion that their accuracy for estimating the number of human fatalities is not reliable 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 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 for watersheds with high flood fatality potential developing a regional equation could be more accurate and practical than existing of general relationships and global models.

The economic effects of large dams which were constructed in Iran during the last two decades are explored in this paper and their impacts on agriculture and welfare in the township of their origin as well as downstream townships are analyzed. Ordinary least squares (OLS) method was used to investigate these effects and for more accurate results we controlled for geographical variables and rainfall. The results showed that dam construction leads to higher agricultural yield, production value and irrigated area in dam’ s own township but it does not affect yield, production and irrigated area in downstream townships. Also, dam construction results in planting more water-intensive crops in their own township and less waterintensive crops in downstream townships. In addition, per capita expenditures in rural regions of downstream townships decrease in response to dam construction, but urban regions of the downstream townships as well as urban and rural regions of dam’ s own township are not influenced by dam construction.

Evapotranspiration is one of the key components in 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. Remote sensing methods based on surface energy balance are being more widely used to estimate evapotranspiration. The purpose of this study was to estimate the actual evapotranspiration of maize based on integration of Landsat 8 and MODIS satellite images using the SEBAL algorithm in Mahidasht, Kermanshah province. Linear with Zero Intercept (LinZi) method was used to integrate satellite images. Also, actual evapotranspiration of maize in 15 farms in the study area was estimated based on ground surface data. The results of the SEBAL algorithm were compared with ground-based actual 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 actual evapotranspiration compared with that obtained by Landsat 8 images. The mean absolute error of estimated actual evapotranspiration during the growing 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 actual evapotranspiration using the SEBAL algorithm and based on the integration of satellite images with different spatial and temporal resolutions could result in acceptable values.

Precipitation is a major component of the hydrological cycle, which has significant spatial and temporal vriations. 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 evaluated the accuracy of some of these data types at the upstream of the Maroon Dam, including highresolution spatial data consist of ERA-Interim, CHIRPS and PERSIANN-CDR on daily, monthly and annual timescales. With respect to evaluation, gridded precipitation data and observational data from 2003 to 2014 were considered. The results showed that estimation of the annual rainfall data of the gridded precipitation models was underestimated so that the estimated average annual precipitation was evaluated less than the mean annual observational precipitation. In the estimation of monthly precipitation with regards to the Nash-Sutcliff coefficient at Dehno, Idenak and Margoon stations, the ERAInterim model and at the Ghale-Raeesi station CHIRPS model indicated the best performance compared to other models. In the daily rainfall estimation, like the monthly rainfall, the best estimate at the Idenak station was the ERA-Interim model, which had an NSE of 0. 63 and the best estimate of precipitation in all stations was by ERA-Interim. ERA-Interim had the best performance from the 3 gridded models in the correct detection of rainy days. The best performance of this model was in determining the correct rain days with POD = 0. 53 at Idenak station.

Water quantity and quality criteria in the reservoirs operation is one of the most important issues in the water resources management. In this paper, a multi-objective simulationoptimization model is developed for reservoir selective withdrawal considering different releases scenarios from 4 reservoir outlets of dam, model fusion technique, NSGA-II multi-objective optimization model and calibrated CE-QUALW2 simulation model. To generate possible reservoir releases as well as automatic running of calibrated CE-QUAL-W2 model for different possible scenarios, two individual codes are developed in MATLAB® software. The three main objective functions of this study were minimizing difference between allocated water from the reservoir to agricultural sector and its demands, maximizing Iran Water Quality Index (IRWQISC) of reservoir and the reservoir storage. Based on this methodology, the input-output data sets of automatic running of CE-QUAL-W2 simulation model for all of the scenarios were saved and utilized for training and validating the MLP (Multi-Layer Perceptron), GRNN (Generated Regression Neural Network) and RBF (Radial Basic Function) individual Meta models. The Ordered Weighted Average was utilized to fuse the individual Meta models in order to determine the model’ s weighting based on Orness method. Then, the fusion model was linked to NSGA-II multi-objective optimization model to determine the Pareto optimal solutions between the objectives of the different stakeholders. For obtaining an appropriate solution considering different involved stakeholders on the Pareto front, Nash-Harsaniy bargaining theory and different social choice rules method were utilized. At the end, the fallback bargaining theory was used to choose the best compromise solution between stakeholders in the reservoir’ s selective withdrawal. The results showed that Nash-Harsanyi bargaining theory, Condorect choice and Borda social rules were most efficient models to find the compromise solutions on the Pareto front between the objectives of the involved main stakeholders.

During the past decades, Tehran metropolitan has suffered from land subsidence crisis. Prolonged droughts and excessive exploitation of groundwater for agricultural and industrial purposes have reduced the level of wá ter in aquifers and reduced the density of the subsurface soil layers. This study focused 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 under study. The result indicated 15 centimeters of displacement in southern part of the study area where it reaches Shahriyar and Tehran plains. However, displacement is not limited to plains and nonurban 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 experienced 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 tracks 28 and 35, these areas had little Horizontal displacement. Displacement vector was high in vertical movement. Vertical displacement was computed for ascending and descending tracks in the second study region and was verified by the data from a GPS station.

As a source of drinking water, groundwater is very important in coastal aquifers. Groundwater vulnerability maps can be used in order 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 rating models and needs to be calibrated for each study area. The novelty of this study was 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). 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, Fuzzy-AHP model is the optimal model for the study area. The results of the vulnerability map indicated that areas in the northwest and west of aquifer 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.

Based on this research, the range of average isotopic values in Polezahab precipitations have been obtained between-2. 9‰ and-6. 6 ‰ for δ 18O and between-14. 4 ‰ and-31. 6‰ for δ 2H. The isotopic meteoric water line obtained for the study area (δ 2H = 6. 6*δ 18O + 12. 1) represented high deuterium excess (dexcess = 12. 1‰ ) and the high values of rainwater d-excess for Sarpolezahab, Qasr-e Shirin and Kerend (8. 7‰ to 20. 9‰ ) weather stations confirming the impact of Mediterranean vapor mass. The average isotopic compositions for groundwater (alluvial and karst) ranged between-5. 3 ‰ and-6. 8 ‰ and between-29. 2 ‰ and-36. 6 ‰ for δ 18O and δ 2H, respectively. The isotopic composition of karst water in Sarpolezahab with little seasonal variations indicated sufficient time for mixing of infiltrated water with water in phreatic zone and long groundwater residence time within formation. The least seasonal variations in the isotopic composition can be seen in the largest karstic springs of the region, including Srabgarm, Ghaleshahin, Gharebolagh and Ryjab springs. Therefore, the water from these springs has the greatest residence time within formation and in turn has high relative age. Marab spring has less residence time and low relative age of water due to more karstic development and fast movement 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, in situ measurement of snow pack is challenging based on traditional methods and techniques. In order to deal with this issue, remote sensing based on satellite images can be considered as efficient method for identifying snow cover and computing snow depth and volume. Within the current research, the Landsat 8 satellite images were employed to detect snow cover surface for Yamchi Basin using NDSI indices and object based image analysis methods. The ground control points were applied to compute the accuracy of the results and 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 snow cover investigation using Landsat 8 images, the satellite images for September indicated no snow cover for the study area 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 obtained results were verified by ground data. Accordingly, the correlation coefficients between observational data and estimated snow depth 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 and the obtained snows depth from differential radar interference were employed to compute water discharge in the study area. Results of this study are of great importance for applying remote sensing image processing methods and analyzing their capabilities for future research. Results are also important for regional decision makers and authorities for regional water resource planning and management.

The optimization of the Muskingum method coefficients is important for increasing the accuracy of the method. One of the main problems in this method is the estimation of the outflow rate at the time of flood initiation, which usually is taken equal to the inflow rate at the same time. In this study, due to the uncertainty of this assumption, the Particle Swarm Optimization (PSO) algorithm was used and 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. The calculated coefficients and the optimized input outflow rate using a flow considered as observed flood can then be used to calculate the flood outflow for other related floods at the same hydrometric stations. The accuracy of the Muskingam method has been increased using the proposed approach in this research.

Almost all real-world decision-making issues, especially in the water resource management area, are multi-objective issues that incorporate different and conflicting objectives. Due to the wide range of such applications, different models have been proposed to tackle multi-objective optimizations, among them NSGA-II and MOPSO are the most important 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. The results showed that by reducing the minimum daily energy production from about 1040 MW to 650 MW, we will meet an increase in the revenue of about 10% of the total annual revenue.

Proper estimation of evapotranspiration is a key data in designing and managing irrigation and drainage systems. Among widely used methods to estimate and predict evapotranspiration for such applications, 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 year climatic data of the station were selected as inputs to the models. Qnet2000, MATLAB and WEKA software were respectively used to implement artificial neural network model, Nero fuzzy model and decision tree M5. 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 accuracy of Artificial Neural Network model and ANFIS model with the help of statistical indices R2, RMSE and MAE were obtained as 0. 0999, 0. 099, 0. 0500 and 0. 0999, 0. 051, and 0. 01119, respectively which showed high accuracy of both models in simulation. Also, the correlation coefficient (R2), RMSE and MAE for the decision tree model were calculated to be 0. 7064, 0. 0935 and 0. 0414 respectively, which indicated the proper performance of the M5 tree model in predicting the reference evapotranspiration rate.

Water scarcity is now one of the most critical challenges in most countries around the world, and in particular in Iran. One of the key ways to control and manage this issue is to investigate water demand. Qom city has always been encountered with water shortage 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 face serious hazards in this regard. The purpose of this research is the investigation of water demand dynamics in Qom city using system dynamics method. Dynamic of various variables such as population, water demand, surface water resources, ground water, and water supply have been incorporated in 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% would result in 29% reduction of water demand level in year 1405 in comparison to current trend. Base on the result, the policy of population control had the most important effect on water demand. On the other side, the effect of price on water demand is negligible, so that, 20% increase in price would lead to 2. 04% reduction in level of water demand in 1405 compared to current trend.