The important role of land use and land cover in the Lake Urmia basin on the water consumption of this area due to better water management in the basin, has made it necessary to have in-depth knowledge of basic information such as land use and land cover. Unfortunately, the available information and statistical sources about LU/LC of basin sometimes are insufficient and contradictory. This study, as one of the important aspects affecting the address of the Urmia Lake issue, has determined the databases that provide land use maps from satellite images, also it examines the accuracy of these global products and compares them with the map which is created by object oriented method with eCognition software. The results of the overall accuracy assessment of the maps illustate that the land use maps extracted from the LCtype and GLCF global products are performing well, and Globecover has provided poor results in this regard. There was the best fit in the results of the MODIS product, so that the MODIS product is not only better in pixel dimensions than most products, but also has the longest land use extraction time in terms of time sequence. The results of this product in the study were in good agreement with the map produced by the object-oriented method, therefore it is recommended to use the MODIS land use product in studies related to the Urmia Lake basin.

Iran has long suffered from water shortages and insufficient rainfall. Due to this, the Iranians started to build agricultural wells to obtain suitable water for agriculture. With the advancement of technology and the advent of electricity and electric motors, the use and drilling of agricultural wells took on a new form. Today, it is observed throughout Iran that using various technologies, wells with many deep and semi-deep depths have been drilled throughout the country, which, in addition to its benefits for farmers, also poses many problems in terms of effects. They create an environment on groundwater aquifers. In 2017, electricity consumption in this area was about 37,285 GWh, which is 15% of the total electricity in the country, which shows a high figure. Another important point is that this figure has grown so much in recent years that it has risen from 11079 GWh or 10.8% in 2001. Given this, in this study, we intend to address the trend of agricultural wells in Iran and suggestions to reduce this amount of energy consumption. In this regard, methods to reduce the consumption of agricultural irrigation systems, improve performance, or use a diesel pump or solar power are examined. This analysis is based on the 5 main watersheds of the country.

Due to the advances made in remote sensing technology, collecting information on the quality of surface water resources by this technology, while reducing the cost and time of traditional sampling, can cover all surface water areas. To monitor. In this study, the capability of Sentinel-2 and Landsat-8 satellite images to estimate the concentration of water quality parameters including acidity, electrical conductivity, total soluble solids, alkalinity and surface water temperature were investigated. First, the Sentinel-2 and Landsat-8 satellite images were pre-processed and then the appropriate bands were determined to identify a significant relationship between the values of each water quality parameter and the images were determined using linear regression and their accuracy was calculated for the actual values. The results show the superiority of Sentinel-2 images with Pearson coefficient, standard error and RMSe for PH parameter equal to 0.58, 0.28 and 0.29, EC equal to 0.847, 78.7 and 77.22, TDS equal to 0.895, 45.8 and 44.37 and for the alkalinity parameter only through Landsat-8 images with Pearson coefficient, standard error and RMSe equal to 0.473, 22 and 21.8, respectively. Both satellite images can be used for the water surface temperature parameter due to the high Pearson coefficient. These values are 0.871, 2.9 and 2.85 for Landsat-8 and 0.752 for Sentinel-2, respectively. 0, 14.4 and 4.06.

Population increase, excessive consumption, agriculture development and climate change have caused a severe decrease in water sources. This dilemma is more tangible in developing countries such as Iran. Therefore it is necessary to adopt important policies in order to improve water management and decrease the water loss. The aim of this research is helping to improve the management of water distribution in irrigation and drainage network in GharaZia-addin city using Spatial Information Systems and Ant Colony Optimization. In this paper, the optimum area for each crop was calculated by designing an objective function and applying constraints such as minimum and maximum plant area for each crop. Then these areas were prioritized by Ant Colony Optimization method and particularly by the travelling salesman problem’s approach in a way that the crops with higher irrigation water demands and more irrigation periods to be planted in the beginning of the network channel. The aim of prioritization is to prevent the water loss during the transportation of water in the water network system. At the end, the obtained areas were used as the input data into GIS to analyze and evaluate the results on the case study field. The results of the study show that by applying Ant Colony Optimization method and the Travelling Salesman Problem, it is possible to improve water management in irrigation and drainage networks. In addition to prevention of water loss in the pipes, the net profit of the agricultural activities has increased 10% by using the method mentioned above

Since the selected habitat indexes provide a description of the habitat characteristics of a species, this study was conducted to investigate the habitat preference of Garra rufa in Dinorab River (Kermanshah Province), a tributary of the Karkheh River basin. For this purpose, the habitat characteristics, including water depth, water velocity, river width, potamal area width, predominant type of bedrock cover, pH, temperature, electrical conductivity (EC), total dissolved solids (TDS) were measured and recorded in 18 sub-stations belonging to six main stations from downstream to upstream. The used and selected habitat ranges were obtained according to the availability of each habitat unit for each variable. The results showed that the most preferred water depth is 26-30 m with a suitability index (SI) of 0.779, river width of 6-7.2 m with SI of 0.7, the water velocity 0.24-0.31 m/s with SI of 0.38, bed structure with medium diameter of 5-5.5 cm with SI of 1, water temperature 18-19 °C with SI of 0.618, pH 7.32-7.44 with SI of 0.545, EC 290-310 with SI of 0.767, TDS in the range of 580-610 ppm with SI of 0.712 and potamal width 4.8-6 with SI of 0.634. The results showed that the Dinorab River is a moderately suitable habitat for Garra rufa.

Today, due to uncontrolled withdrawal of groundwater resources and declining water table, especially in arid and semi-arid regions, planning and management in the consumption of these valuable resources are of great importance, which requires a study of the behavior of the aquifer in relation to the changes made on it. The purpose of this study is to investigate the efficiency of random forest algorithm in predicting the water table of the unconfined aquifer of Birjand plain and to compare the results with two models of decision tree and artificial neural network. In this regard, first, the input data to the model was collected on a monthly basis during 2010-2011 until 2016-2017 water years, and after checking the trend and removing it, to create the mentioned models, the rattle software package in the statistical software R was used. The results of simulation using the random forest algorithm based on evaluation criteria of R2=0.714, RMSE=0.003 and NS=0.598 (m) show that this algorithm has a relatively high ability to simulate the aquifer water table. Comparing the results of this algorithm with two decision tree and artificial neural network models, it can be seen that the results of the random forest algorithm compared to the decision tree model with R2 = 0.5409, RMSE = 0.0072 and NS = -0.0187 (m) is more consistent with the actual water table of the aquifer and is in line with results of the artificial neural network with R2 = 0.7055, RMSE = 0.003 and NS = 0.6046 (m).

Due to the location of Iran in arid and semi-arid regions and type of soils common in Iran, the high rate of erosion and sediment is one of our country problems. The amount of sediment produced is the result of complex interactions between climate, soil type, landuse and human activities. Therefore, obtaining appropriate methods in predicting sediment load can be considered as one of the most important challenges. The main purpose of this study is to identify critical areas in terms of erosion and sediment in upstream watershed of Nahand Dam located in East-Azarbaijan province. In this regard, SWAT model was calibrated and validated using SUFI-2 algorithm to predict monthly discharge and sediment load. Nash-Sutcliffe (NS) as the objective function for discharge in the calibration and validation periods were 0.84 and 0.75, respectively. The Nash-Sutcliffe coefficient of sediment load was calculated to be 0.65 in the calibration period and 0.8 in the validation period. Then, using the results of the SWAT model, the average runoff and sediment outflow of the sub-basins were classified by method of Natural Breaks (Jenks) and the critical areas of erosion were determined. Accordingly, 5,200 square kilometers (25%) of the watershed area, which are classified in the class with more sediment production, are critical areas in terms of erosion and sediment. Since erosion causes the destruction and reduction of soil fertility and on the other hand, the produced sediments are deposited in dam reservoir, so it is necessary to perform erosion control operations in these sub-basins.

The study of statistics and information on annual damages caused by floods in Iran indicates the extent of flood damage to natural resources. The use of geospatial information and remote sensing technologies can be very helpful in reducing these damages and better planning. In the present study, these technologies have been used for flood zoning in the Karun River in Ahvaz city. The zoning of the study area was done by combining hydraulic model and ArcGIS software through HEC-Geo RAS extension along 33 km of this river. In order to extract the border of the river banks in the urban area of Ahvaz, the supervised classification and Landsat satellite images were used. After introducing the geometric information to the model, the value of the Manning roughness coefficient is determined for different periods and then the return periods of 2, 50, and 100 years are introduced. The maximum speeds in the return periods were 2.6, 6.15, and 7.2 m/s, respectively, which are within the allowable flood speeds. This means that if the river banks are organized and fenced, scouring, erosion, and sedimentation will not occur and water will flow in the main canal without destruction. Preparation of flood warning systems based on precipitation with a high return period that leads to extreme floods, walling, beach construction, and river management in unstable and erodible sections of the river and improving the slope of the bed and canal dredging in the required sections, including the proposed executive solutions for organizing Karun River.

Flow resistance is a key factor in open channels hydraulic analysis. Resistance to bed particles causes energy loss. As the particle size increases, the resistance increases. Experimental evidence shows that large particles in the river bed exert flow resistance. In this study, the factors that cause flow resistance in rivers have been investigated and the effective parameters (depth and width of flow, equivalent roughness height) on the habitat have been discussed. To investigate the effect of flow resistance parameters on aquatic habitat, Jajrood River and rainbow trout species have been selected. During the field visit, the coordinates of the map were matched with the location and samples of surface and subsurface materials were taken. By performing gradation in the laboratory and using Manning’s equation and stage discharge curves, the hydraulic roughness coefficient was calculated. Then grain size roughness was obtained using experimental relationships. Shape roughness coefficient was calculated by subtracting the two roughness coefficients and was used in the hydraulic simulation. Water levels obtained from the hydraulic model were used to simulate the habitat. The effect of flow depth and width and equivalent roughness height parameters on the habitat at the three life stages of the target species, namely fry, juvenile and adult, was analyzed using simulation results. In general, with increasing the width and depth of the stream and the equivalent roughness height, the habitat suitability for the target species increased. The factor that causes the most change in habitat suitability is the width of the stream,

Assessment of drinking water resources quality and determination of natural and anthropogenic effective factors on their chemical composition has an important role in sustainability of ecosystems depending on these resources. In this study, aimed at assessing water quality of rivers and springs in Shirin Darreh dam watershed and the reservoir and investigating the effect of formations lithology on their quality, water quality data in 2018-2019 water year for 33 samples of the rivers, 6 samples of springs and one sample collected from the reservoir were used. Three water quality indices including WQIB, WQIMT, and WQIDD were calculated for these samples. 10 sediment samples were collected from the study area and their mineral content were determined to study the lithology effect on water quality. The results of Gibbs diagram showed that rock weathering was more important than evaporation and precipitation in determining the chemical composition of the study water resources. Also, the major type and face in the collected water samples, and gypsum, shale and marl were detected as the most important source of these ions. The results reflect the effect of the lithology on the chemical composition of the study water resources. Gypsum and the various clay minerals that were in accordance with the hydrogeochemical studies.The stored water in the reservoir had higher quality for drinking that can be contributed to the springs joining in adjacent to the reservoir. The higher quality of these springs can be due to their origin in the Tirgan karstic Formation.

In recent decades, increase of population and development of industries, the occurrence of drought and increasing water consumption has put pressure on the province's water resources. This situation has many environmental and socio-economic consequences. Therefore, the aim of present study is to monitor drought and evaluate its economic and social effects. The present research is applied terms purpose and descriptive-analytical in terms survey. The statistical population in this study includes experts and elites the study area, that finally 80 elites in the province were selected by census method. SPSS Amos and GIS software were used analyze data. Based the results obtained from the processing of precipitation data and TRMM satellite images during the period 1998-2019, it was found that there was no significant difference between frequency of occurrence drywet periods in Tehran province. However, in the last years the study period, rainfall anomalies in Tehran province are more prone to drought, and the last 7 years, three widespread and relatively severe droughts have occurred. In general, it can be said that the phenomenon of drought in Tehran first caused psychological and social tensions and injuries (with the highest factor load of 0.894) with development this phenomenon, the ground for creating a crisis production and livelihood (factor load 0.850) becomes. Following these effects, another phenomenon called poverty and misery appears (with a factor load of 0.698) and finally these factors underlie the migration of individuals and changes in population structure (with a factor load of 0.733) at the origin and destination.

Marand aquifer is one of the large plains with extensive agricultural and industrial activities and it is categorized in critical aquifer class. One of the problems of groundwater decline is groundwater quality changes that affect how they are used and managed. Therefore, in this study, using 46 water samples from wells, qanats and springs in June 2014 and June 2017 and analyzing the parameters of main, secondary and rare ions to calculate the GQI and GWQI groundwater quality indices. According to the output maps of these two indicators, which show the difference in determining the quality of drinking water in the region, it was not possible to choose one of these two indicators to determine the drinking water capacity of the region. The two indicators used, in order to achieve a single map, the method of unsupervised combination was introduced and used. The results indicate that a higher CI than the results of the two indicators. The results showed that Marand plain is in the middle and acceptable classes in terms of GWQI and GQI index. The highest and lowest GWQI and GQI indices were observed in the south and northwest of the plain, respectively. Comparison of drinking water quality index maps of the study area in 2014 and 2017 shows that in 2017 the area of plain, indicates a decrease in water quality over the last 5 years.

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

Water, food and energy are the main resources needed for the development of communities. The nexus view emphasizes the interconnected management of these resources and has been applied with a focus on three sources at the macro level. In this research, evaluation and prioritization of effective factors and methods of optimal resource allocation based on the nexus approach of water, energy and food production with the Analytic Hierarchy Process (AHP) in Alborz province has been considered. For this purpose, the criteria were compared in pairs in a hierarchical analysis with the opinions of experts and their importance was determined. Criteria including water, food and energy were considered. Factors affecting the optimal allocation of resources in Alborz province were determined and presented as multiple choice and compared in pairs based on questionnaires completed by experts. The results showed that the water criterion with the relative weight of 61.4% has the greatest impact on the evaluation process compared to other criteria and the energy and food criteria with the relative weight of 26.2% and 12.4% have the most impact, respectively. Among the developed strategies, education and awareness raising with a score of 35.9% was ranked first, and environmental policy with a score of 26.6% was ranked second. Therefore, it is suggested that strategies for education and promotion of awareness and environmental policy be given priority.

Water is one of the most essential elements in nature that forms the basis of human life and contributes to the economic growth and development of societies. Healthy water is closely related to environmental health and activities. The life of all animals on Earth depends on water and oxygen. In addition, adequate dissolved oxygen (DO) is essential for the survival of aquatic animals. Therefore, in this study, to simulate the dissolved oxygen of the Cumberland River in the United States from the combined artificial neural network (ANN) model with wavelet and meta-heuristic algorithms of gray wolf (GWO) and bat (BA) on a monthly time scale during the statistical period. Used 2020-2010. The criteria of correlation coefficient (R2), squared mean square error (RMSE), absolute mean error (MAE) and Nash-Sutcliffe productivity coefficient (NSE) were used to evaluate and compare the performance of the models. The results showed that all three hybrid models have better results in hybrid models than the other designated models. Also, according to the evaluation criteria, it was found that among the models used in the simulation of dissolved oxygen in river water, the model of artificial neural network-wavelet with coefficient of determination (R2 = 0.958), the root mean square error (RMSE = 0.651), The mean absolute value of error (MAE = 0.334) and Nash Sutcliffe coefficient (NS = 0.962) in the validation stage showed better performance than other models.

The Hyperic region is an area immediately below the riverbed in which the mixing of downwelling surface water with subsurface flow occurs. This area plays a very vital role in the ecology of the river and causes self-purification of the river flow. Rockboulders in riverbeds usually act as impermable barriers, creating a hydraulic head difference upstream and downstream of these structures, and a hydraulic jump occurs downstream. Since scour hole is usually formed downstream of these barriers, so the purpose of this study was to determine the different pattern of hyperic exchanges around rigid river barriers in three different flow conditions(i.e., clinging nappe, rapid variable flow and hydraulic jump-scouring. To evaluate the results, a laboratory flume was used to determine the flowpaths of hyperic streamlines. The numerical model was also used for simulation of hyporheicflow. The results showed that there was a good agreement between the observed and computational flowpattern in the hyperic area for both clinging nappe and hydraulic jump, and Upstream Directed Upwelling(UDU) was observed in the area between the vertical barrier wall and the point of maximum scour depth and downstream Directed Upwelling(DDU) was observed in the numerical model. Also, the results showed that there are a power relations between total exchange rate(Qex), the residence time(Rt) and the percentage of exchange rate(Qp) against Reynolds number and correlation coefficient of 95, 81 and 86% was obtained for Qex, Rt and Qp, respectively. The accuracy of estimation shows that these relations can be used for estimation of hyporheic characteristics.

Currently in Iran, due to the availability of fossil resources, a huge amount of the country's electricity needs are met with the help of fossil power plants. But limited water resources will be one of the main challenges in generating electricity for our country in the future. Therefore, the purpose of this study is to calculate the amount of virtual water consumption in electricity generation in various fossil and renewable power plants and also the cost of virtual water used to generate electricity. Water consumption in steam turbine, combined cycle and gas turbine is equal to 1.38, 0.29 and 0.025 liters per kilowatt-hour, respectively, and in photovoltaic and wind power plants is very low. Therefore, in order to develop and grow the country's power industry, choosing the type of power plant and especially the type of cooling system plays an important role in saving water consumption. Although the cost of virtual water is negligible due to the low cost of each unit of industrial raw water, drinking water in government centers and irrigation of green spaces, the high consumption of water in power plant processes to generate electricity as a water industry shows Shows that by consciously choosing the path of energy development, a significant amount of waste of water resources can be prevented and also the reduction of heat pollution of water resources (in single-pass cooling systems) can be prevented.

Investigating the issue of resilience of drinking water wells and presenting an optimal model in determining their quality privacy is one of the most important tools for managing and protecting valuable groundwater resources. In this paper, the drastic model is used to evaluate resilience based on the inherent vulnerability of the aquifer based on the MODFLOW model and track the movement of particles in the aquifer by MODPATH to determine the catchment area of wells.

By Combining the results of both models in GIS environment, the pollution risk map and the resilience of drinking water wells in Maragheh city were determined regionally and in the catchment area of drinking water wells. Also, determination of resilience based on damage caused to pollutants to the aquifer within the quality area of wells. A quality assessment model based on pollutants was used to determine the quality area more accurately.

Most of the drinking wells in the area were less resilient with agricultural land use. Nitrate content in Maragheh drinking water wells averaged 7.3 mg/L, which is below the standard. Phosphate content was 0.35 mg/L on average, which is higher than the standard.

Due to determining the quality of drinking wells in different years, a larger quality area (ten years) should be considered for wells in these areas. Smaller protection can be applied to areas with high resilience and other land uses.

Over the last two centuries, natural hazards and widespread human activities have led to significant changes in water, soil, and vegetation covers. Although, multi-temporal remote sensing (RS) images provide continuous monitoring of changes in land surface, one of the most important challenges is applying multi-sensor images to detect land cover changes in unsupervised flow. This study aims to provide a method for changes detection in water, soil, and vegetation covers within multi-sensor RS images. In this regard, new biophysical parameters have been defined for the Sentinel2B sensor, as well as a new unsupervised method for binary and multiple changes detection has been developed. Landsat8 OLI and Sentinel2B images of the southwestern shore of the Urmia Lake were used to evaluate this method. In the proposed method; first, the generalizability of the Tasseled Cap (TC) transformation was investigated and a new TC transformation for the Sentinel2B sensor was estimated. After TC, the images were transferred from multispectral feature space to biophysical feature space, and a binary changes map was generated using the proposed multivariate iterative trimming method. Then, via FCM clustering, the changed samples were separated into a certain number of clusters determined by the WSJI criterion which is one of the innovations of the proposed method. Overall accuracy, missed error, and false alarm of the proposed approach are %92.06, %9.62, and %6.27, respectively. The proposed method in this paper can be used as an unsupervised, accurate, and reliable technique for changes detection in water, soil, and vegetation covers.

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