جستجوی مقالات مرتبط با کلیدواژه « آب زیرزمینی » در نشریات گروه « آبخیزداری، بیابان، محیط زیست، مرتع »

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

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

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

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

Water is the source of life and a strategic resource for human societies. The need for this vital resource is increasing exponentially due to the increase in population and the development of industry and agriculture. People are forced to use underground water because surface water is not generally and permanently responsive to diverse needs. A decrease in their volume and many problems have been caused by the excessive use of these resources. This crisis has caused regional crises caused by the imbalance of resources and consumption, along with climate changes, has raised the issue of integrated management of water resources more than ever. Agricultural land has been developed due to the increase in population and the need for more food. Programs without principles that rely solely on the quality and quantity of underground water resources have been harmful. Groundwater aquifers are transformed into sources of the country's needs due to the heterogeneous and untimely temporal and spatial distribution of discharges and surface water flows. In recent years, with the increase in water demand and the non-supply of a significant part of it by surface water sources, the extraction - permitted and unauthorized - of underground water sources has been given much attention; so that the level of underground aquifers has decreased dramatically across the country. The purpose of the present study was to investigate the impact of the important variables of precipitation, inflation and annual population as a representative of climatic, economic and social factors on the fluctuations of the underground water level in Urmia region.

In the present study, the impact of three factors, precipitation, population and inflation, on the subsidence of the Urmia Plain aquifer has been investigated. To do this, multiple linear regressions was performed between the data of the annual loss of the groundwater level during 38 years, 1981 to 2019 with three variables of precipitation, population and inflation index of the previous year. According to the previous researches, firstly, an index of inflation has been established by comparing the average loss of the piezometric level of the underground water in
Urmia region as a dependent variable, with the three independent variables of the average rainfall of water year as the most important climatic factor, the annual population of the major centers of human concentration located in the Urmia plain of previous year, and the base coefficient of the annual monetary value of previous year compared to 1981 using a multivariable linear regression. Then, the outcome is compared to the outcomes of artificial neural networks such as four-layer perceptron, three-layer perceptron, and radial basis function. All three networks have an input layer with three neurons to receive the values of the three independent variables of precipitation, population and inflation. One or two hidden layers with a number of neurons, to perform calculations and process the relationship between independent and dependent variables; and an output layer with a neuron to provide the processing results i.e., the estimated aquifer subsidence rate. The data used in the present study were derived from the years 1981-2019. The reference of the aquifer level data is the hydrograph extracted from 67 piezometer wells in the area by the underground water unit of basic studies of the West Azerbaijan Regional Water Company. The annual rainfall data reference is of the Urmia camp evaporation station located in the company premises, which is well controlled and highly reliable as an indicator of rainfall changes in the region. Population data is sourced from the Iranian Statistics Center, while inflation data is sourced from the Central Bank of Iran.

According to the results of the reviewed models, despite the differences in the values of the numerical results, in all four models: multivariate linear regression, perceptron artificial neural networks of the four layers MLP:3-2-2-1, and the three layers MLP:3-5-1 and the radial basis function RBF: 3-5-1, it can be seen that the importance of the independent variables under study are population, inflation and annual precipitation respectively. It is obvious that a larger population needs more food, clothing, housing, etc., which, according to the concept of virtual water, ultimately leads to more use of the limited available water and soil resources. Economic activity, particularly agriculture, is increased due to the depreciation of currency and decrease in people's purchasing power, which is a result of the decrease in purchasing power and the depreciation of currency. This problem has also led to the change of land use of natural resources to agricultural lands that are either rainfed or irrigated. Explaining that rain fed lands cause more rainwater loss through capture and then evaporation and transpiration by plants planted by farmers. Irrigation of agricultural plants or gardens of irrigated lands - mainly with unauthorized water harvesting - ultimately leads to more water consumption. Additionally, humans have exploited underground water resources due to the inappropriate and untimely distribution of rainfall and surface water resources. Although by adopting new management methods, both social and economic, and improving water productivity, despite the increase in demand for water, despite our efforts to protect this vital, sensitive, and strategic resource, statistical studies, including the current results, demonstrate that we have not chosen the correct solutions. Considering some irreparable effects of the aquifer level drop, including irreversible changes in the mechanical characteristics of the soil, which lead to more vulnerability of infrastructures and facilities; the emphasis is placed on comprehensive water resource management and the concept of virtual water and its trade.

Since the increase in the depth of groundwater and its intensification can indicate serious limitations in the exploitation of these resources, predicting the changes of this parameter plays an important role in managing these resources and preventing possible damage to them. For this purpose, the use of smart methods has been strongly recommended by researchers. In this research, the methods of multilayer perceptron neural network (MLP), fuzzy inference system (fis), adaptive neural fuzzy inference system (ANFIS), and the combined method of fuzzy neural inference system and particle swarm optimization (ANFIS-PSO) were used for simulation of groundwater Fluctuations depth in Haji Abad area between March 1995 to October 2022 on a monthly scale. The training and testing phases were done with 75 and 25 percent of data, respectively. To measure the accuracy of the models, root mean square error (RMSE), mean absolute percentage error (MAPE) and mean absolute value of error (MAE) indices were used. The best results in the training phase are related to ANFIS-PSO, ANFIS, and MLP models, respectively. Simultaneously with the training of the mentioned models, the testing stage of said models was also implemented. Finally, the best results in this stage belonged to the neural network model with time delay [1 3 5], the ANFIS-PSO model with time delay [1 2 3], and the neural network model with time delay [1 2], respectively. The accuracy indices in the test stage for the best models are (0.1871, 0.1865, 0.1857) for RMSE, (0.7402, 0.6715, 0.6684) for MAPE, and (0.1326, 0.1238, 0.1198) for MAE, respectively. These values show that all three models have an error of less than 20 cm, an error percentage of less than 0.75%, and an absolute error of less than 14 cm, which indicates the acceptable accuracy of these models. Also, the coefficient of determination obtained from the regression relationship of the calculated and measured values of the groundwater depth in the test phase for all three models is around 0.82, which indicates a relatively high linear relationship between these two parameters.

Semnan plain is very susceptible to land subsidence and drought, in recent years has greatly increased the occurrence of subsidence. The aim of current research is land subsidence susceptibility assessment using frequency ratio model. At first locations of the land subsidence were specified using Landsat satellite images and field surveys. After classifying conditioning factors maps, the weight of each map was calculated using the frequency ration model. The highest weight was related to water level less than 41 meters, slope less than 2 degrees, topographic wetness index more than 12, agriculture land use type, plan curvature -0.01 to 0.01, profile curvature -0.001 to 0.001, distance less than 1260 meters of road, less than 7000 meters of faults, Quaternary formations and less than 200 meters of drainage network. Finally, by combining the weights, the final subsidence susceptibility map was prepared. The AUC for the frequency ratio model was 0.76 that showed this model is acceptable for land subsidence susceptibility mapping in the Semnan Plain. Land subsidence susceptibility maps produced in this research can be useful and functional tools for regional planners and policy makers for land use planning, resource management, and natural hazard mitigation.

The objective of this study is to investigate the quality of water resources in Tahroud region in the northwest of Bam city, Kerman province through hydrogeochemical studies. For this purpose, 13 water samples, including 5 samples from the agricultural wells, 4 samples of Ghanats, 3 samples from springs and 1 sample of Tahroud river were sampled and analyzed in the laboratory using Inductively coupled plasma mass spectrometry (ICP-MS) method. Based on the hydrogeochemical analysis, the water resources of the studied area have dominant Na-Cl facies and are classified as saline waters. The average concentration of EC (6230 µS/cm), TDS (4050 mg/L) as well as of Clˉ (1391 mg/L), Na+ (9031 mg/L) and SO42- (771 mg/L) in the investigated water samples were remarkably higher than the normal or recommended values. The highest amount of these soluble ions were observed in the water samples collected from the playa section of the catchment basin, which was mainly covered by the Quaternary fine-grained deposits. In addition to the hot and dry climate and the high evaporation rate, the existence of Neogene formations containing gypsum and sodium salt under these sediments is another important factor that increase the solutes in underground water sources in this area. Among the investigated potentially toxic elements, the concentration of arsenic with natural origin and higher than the permissible limit of drinking water was observed in some water samples. The evaluation of the water quality of the region using the Schuler diagram also showed that these water sources have an unfavorable to unusable quality for drinking and even for agriculture in some cases.

Drought and population increase are important factors that have caused more attention to ground water. Groundwater is one of the most valuable natural resources that affect human health, economic development and environmental diversity. Due to several inherent characteristics, these waters have become a very important and reliable source of water supply in developed and developing countries. Over the years, the importance of ground water due to the ever-increasing need for water has led to unscientific exploitation of ground water and the creation of water stress conditions. This alarming situation requires a cost-effective technique for proper assessment of groundwater resources and planning for the management of these resources. Geographic information system (GIS) and hierarchical analysis are samples of these tools. The purpose of this research is to prepare the ground water potential map using hierarchical analysis in the Ilam Dam watershed.

For this purpose, seven criteria of geology, slope, land use, soil, drainage density, lineament and precipitation were selected to identify the potential areas of ground water. The selection of these parameters is due to the effect that each of these factors has on the ground water. Geological features are important in controlling the infiltration of water into the ground due to the weathering, porosity and fracture that occur in them. On the other hand, increasing the slope of the land causes an increase in runoff. As drainage density increases, permeability decreases. Agricultural, forest and pasture land use can increase infiltration, but residential areas increase runoff due to impervious surfaces. Sandy and loamy soils have a high permeability coefficient, and finally, the higher the rainfall in the region, the higher the groundwater level. In order to prepare these layers, ArcGIS and remote sensing (RS) were used. First, by using the digital elevation model (DEM), the slope of the area, the drainage density in five classes were prepared. By using Landsat 8 satellite images of 2020 and in the environment of RS software, the land use of the region was created in five classes of agriculture, forest, pasture, bare soil and residential areas using a supervised classification method. Kappa coefficient confirmed 93% classification accuracy. The rainfall map of the watershed was also obtained from the synoptic and rain gauge station that existed in and around the basin. Finally, the geology map was prepared from the digital geological map in the GIS environment and the soil map from the Natural Resources Organization. After preparing these layers in the GIS, using the opinion of experts regarding the valuation of these criteria, each of these criteria was given grades from 1 to 9. Then, this valuation was transferred to Expert Choice software to determine the weight, and the weight of each criterion was obtained. Then, using these weights as well as raster layers created in the GIS environment and using the weighted overlay method, these layers were superimposed and the ground water potential map was obtained.

The results showed that geology criteria and land use have the most weight with 0.347 and 0.191, respectively, and soil and precipitation with 0.062 and 0.054 have the least importance for ground water potential. A big part of the watershed has medium to high potential for ground water. This part has a lot of forest and pasture cover, moderate slope (20-40 degrees) and high drainage density and high amount of precipitation, which is consistent with the results of Suri et al. (2016). A significant part of the basin has loam and sand soil, which have high permeability and can absorb water and increase the groundwater level. Kazhdomi formation has medium to high potential and Bangestan group formation has low potential.

In general, the final map has four potentials, including very low, low, medium to high, and very high, which respectively account for 0.98%, 41.8%, 55.9%, and 1.32% of the study area. Medium to high potential has the largest area. In general, the north of the watershed has medium to high potential, the south of the watershed has low potential, and a small part of the east of the study area has high potential of ground water. Preparing a map of ground water potential in watersheds can be a suitable strategy for exploiting these resources.

The most important problem in the development and construction of underground dams is the complexity of determining suitable areas for dam construction. This problem arises from the fact that many criteria and factors including social, economic, geological and hydrological criteria are involved in its proper location. Therefore, it is important to use methods that can determine suitable places for the construction of underground dams with high accuracy and with the least amount of time and cost. The construction of an underground dam is recommended as one of the solutions for water supply in arid areas where there is no access to usual sources, such as wells and permanent rivers, or they have few water resources. For this purpose, in the present study, the location of the prone areas for the construction of such dams has been investigated. The studied area is the Rodan Watershed in Hormozgan Province, which has a good potential for the construction of an underground dam due to its dry climate and special geological conditions.

In this study, the number of eight initial locations were identified as potential points for construction underground dam by combining digital elevation model, topographic features, geological and hydrological features in GIS. In the following, after forming the decision matrix using Vicor model, ranking, determining the index and selecting the smallest index as the best option were done. Finally, the options were sorted based on the values of desirability index, dissatisfaction index and Vicor index. Then, the best option that has the smallest Vicor index was selected.

According to the obtained results, the value of Vikor index (Q) was 0.0158 and 0.097 for sites 5 and 2, respectively, and that way, based on Vikor index, the first rank belonged to the site 5 and the second rank belonged to the site 2. Therefore, out of the initial eight locations, only two places were suitable spots and other suitable sites were rejected due to the distance from the centers of population concentration and agriculture. Rank one, located in the east of Ziarat Ali, is one of the best places to build an underground dam due to the hydrological and topographical conditions, including the fact that the slope in this site is less than five percent. The second priority, located in the north of Brentin district, was considered as a suitable option for the construction of an underground dam due to its location in the vicinity of a sparsely populated village where drinking water is supplied through a well. Among the criteria used in the present research, the criteria of water need, distance from the village, pH and EC parameters, and water quantity were the most important in the sites that have been assigned the first and second priority.

Examining the results of the reservoir surface factor in this research showed that the larger the reservoir surface, the higher the priority in locating this structure. In underground dams, unlike surface dams where the large reservoir surface is considered a disadvantage due to losses by evaporation, regardless of other factors, the best place to build an underground dam in a river is the canyons that have the maximum area of the reservoir in upstream. Looking at the axes selected in the current research, it can be seen that the highest priorities and the most valuable axes are selected in the quaternary formations, which can indicate the accuracy of the structure's positioning. Since the peak of water consumption in the region is in the spring and summer seasons, therefore, by constructing an underground dam in the proposed sites, part of the water shortage and crisis in the hot seasons can be compensated.

The water resources of the earth have currently been reduced due to various factors such as rising population, and an increase in human activities, including the growth of urbanization and industries, and increasing agricultural and economic activities. Therefore, water shortage seems to be one of the most important crises that threaten the future life of living creatures. In this regard, arid and semi-arid regions are subject to more risks due to reasons such as climate change, drought, and excessive extraction of groundwater resources for industrial, agricultural, and drinking purposes. On the other hand, in addition to the increase in temperature, climate change will also cause changes in precipitation and evaporation rates, leading to the loss of large amounts of water by decreasing precipitation and increasing evaporation rates, respectively. In such a situation, the groundwater resources are highly pressurized, considering the continuous drop in the water level, the fact that the amount of harvest is always more than that of the recharge, and the irreparable damages that may follow. Therefore, this study sought to investigate the influence of climate change on the groundwater level of the Ravansar-Sanjabi basin and to analyze its results. To this end, first, the groundwater simulation was carried out by Mudflow code. Then, the effect of climate change on groundwater resources was investigated during the future period (2021-2040), taking into account different climate scenarios.

Known as a relatively rectangular plain with north-south extension, the Ravansar-Sanjabi plain is located in the northwest of Kermanshah city (the center of Kermanshah province) between 18'26°46'' to 00'50°46'' eastern longitudes and 00'25°34'' to 34’50’48’’ latitude''. According to the latest nationally published statistics, there are 881 wells in the Ravansar-Sanjabi basin with a discharge of 27 million cubic meters per year (Figure (3). Moreover, the main sources of the basin’s recharge are precipitation and the amount of water returned from exploitation wells, with approximately 17% of the precipitation in the area being considered as recharge.

As for the groundwater modeling, there was an acceptable correlation between the simulation and observation data under both stable and unstable states, indicating the appropriate performance of the MODFLOW simulation model in the Ravansar-Sanjabi basin. Moreover, the error-index value was found to be 0.95 for groundwater modeling with RMSE, suggesting an appropriate accuracy of the model in an unstable state. In addition, the values of the explanation coefficient and MAE were reported as 0.98 m and 0.87 m, respectively, falling in a suitable error range. On the other hand, the calibrated hydraulic conductivity values showed that the hydraulic conductivity values varied from 52 and 30 meters per day in the north of the basin. However, the greatest hydraulic conductivity values were found in the southeastern part of the basin, ranging from 16.5 to 29 meters per day. Also, the average values of hydraulic conductivity belonged to the central area of the basin, ranging from 8 to 12 meters per day. According to the results obtained for the selection of an appropriate climate model, it was found that out of 20 existing models, the HadGEM2-ES, CanESM2, and CSIRO-MK3-6-0 had the greatest values (15.5, 15.5, and 17.25, respectively), being selected as the best models in this research. Moreover, the results of climate change indicated that the precipitation rate did not change much throughout the study period (2021-2040). On the other hand, while changes in the precipitation rate were found to be small under the RCP2.5 scenarios, they were significant under the RCP8.5 scenarios, especially the reduction of precipitation in some months. As regards the temperature changes throughout the study period (2021-2040) under all three climate scenarios, the results indicated a decrease in temperature rates, with the lowest and highest decrease occurring under the RCP2.6 and RCP8.5 scenarios, respectively. Accordingly, the temperature is predicted to decrease by approximately 0.5 degrees Celsius in the worst case. It was also found that the groundwater level varied from 20 cm to 60 cm in all months, with the lowest balance reduction having occurred in January, and the highest balance reduction having occurred in April, May, and June. Moreover, according to the results of changes in temperature and precipitation under the three climate scenarios, it could be argued that the greatest and slightest decrease in the groundwater level will occur under the RCP 85 and RCP 26 scenarios, respectively.

In recent decades, following the exploitation of groundwater, especially in areas with limited surface water and in which groundwater is the greatest resource in meeting the needs of water demands, the trend of reducing the volume of aquifers has increased. Meighan watershed, which includes Meighan wetland, is one of the most important plains of Iran that supplies a significant part of Arak city's drinking water and many agricultural wells. Since the drought causes a rapid reduction in surface flows, declines the ground water level, intensifies the wind and water erosion, changes the quality of water resources, causes ground settlement and especially, leads to the problem of salinization of drinking and irrigation water, it is necessary to evaluate the effects of drought and manage its risk.

The study area of Meighan is located in Central Iran with 2854.63 km2 area. To investigate the possible drinking water crisis in the region, water level decline of agricultural wells, and the risk of ground settlement in the groundwater measurement network, the observed groundwater level and absolute height of groundwater level data were collected in 46 piezometric wells in the statistical period of 1986-2006 and 2006-2020. For each year, an average isopieze map was drawn. Then by deducting the maximum and minimum values in each well, the amount of loss in each year was determined. These data were used to draw maps of annual decline. The reason can be the lack of proper feeding of the aquifer due to the decrease of precipitations and drought and as a result of the reduction of the aquifer storage due to the excessive exploitation.

From 1971 (the first data collection) to 2004, with the increase in the number of deep and semi-deep wells, the discharge rate of the wells has increased by a total of 531.5 mm3. In 2009, despite the increase in the number of wells, the discharge rate of wells has decreased by 153.9 mm3 in 6 years. In the last data collection in 2020, the number of wells and their discharge rate have decreased which indicates drying up of the wells due to the decline in the groundwater level in many areas of the plain which has led to the disuse of wells.Reviewing the decline maps of 1986-2006 and 2006-2020 indicate that the northern and eastern areas of the plain do not show significant changes and have a relatively constant trend. However, as it is shown in isopieze maps, in the western regions and in the south of the plain, groundwater level has had the highest decline. From 2006 to 2020, in the north and northeast, as well as in the south, west and southwest of the basin, there are areas with the highest rate of decline.

According to the analysis of rainfall data and the absolute height of groundwater level of Arak Plain, it can be concluded that the amount of rainfall does not directly affect the decline of the groundwater level. Research results indicate that before 1986, the hydraulic slope of the Arak plain aquifer conforms to the level of the plain and the Meighan playa has been a natural drainage of the plain. However, during the period of 1986-2006 with the increase and concentration of exploitation wells in the western and southwestern parts of the plain, the hydraulic slope of the aquifer has inclined towards the western regions. From 1986 to 2006, it can be concluded that the maximum groundwater level decline of 20 meters occurred in the western and southwestern areas of the basin and extended to the eastern areas of the basin. However, from 2006 to 2020, the decline classes have increased significantly, such that in the west, southwest, north and northeast of the basin, an increase in the groundwater level decline up to 70 meters has been observed.

Qanat is a technique for obtaining water and transferring it for various uses. Due to the widespread arid and semi-arid areas in Iran, Qanat is the most sustainable method to obtain underground water. Considering the role of the Qanat in providing water to dry areas in the current situation of the country, where the issue of water shortage and water resources management is very important. Due to the importance of the Qanat in supplying water to dry areas in the country, the issue of water shortage and water resource management is very important knowing and studying the Qanat is very important and necessary. The purpose of the present study is to investigate and prioritize the most important physical and human parameters affecting Qanat discharge using the Analytical Hierarchy Method (AHP) according to the opinion of experts in the Mashhad-Chenaran plain. In this regard, firstly, the factors affecting Qanat were identified and studied by reviewing the sources and using the opinions of experts specializing in the field of Qanat and underground water. Then, using the hierarchical analysis method in the Expert Choice software environment, the weight and importance of each of the different parameters were determined. The results of parameter prioritization using the hierarchical analysis method showed that physical parameters with a weight of 0.545 have more value in Qanat discharge than human parameters. Also, based on the results of the prioritization of the physical parameters effective on Qanat discharge, the parameters related to the characteristics of the aquifer with a weight of 0.497 have the most importance in Qanat discharge. Also, according to the results obtained for the prioritization of human indicators, the ownership parameter with a weight of 0.539 has the most importance in Qanat discharge.

The aim of this study was to model the subsidence of Abarkouh plain using inSAR and artificial intelligence techniques. At first, the subsidence map was prepared using the 46 Sentinel - 1 radar images (2014 – 2018) and radar interferometry techniques. Then, the Feedforward artificial neural network (ANN) algorithm was used to model the subsidence. In this algorithm, groundwater level changes (2014-2018), groundwater level, aquifer thickness, clay thickness in the aquifer and the clay thickness in the range of groundwater level changes (2014 - 2018) were introduced as input layers and the subsidence layer obtained from the radar interferometry method was introduced as an output layer to model training. These five parameters were obtained from the measured data set of 34 piezometer wells and 77 logs available in the archive of Regional Water Company of Yazd province. After initial checking of the data accuracy, the Kriging interpolation method was used to extend the five parameters to the whole region and the raster layers were prepared. The results of inSAR showed that maximum subsidence in parts of the studied area, i.e. in east, north - east and north, were 6, 2.7 and 1.6 cm/year respectively. Also, in order to verify the accuracy of the map resulting from using a neural network model, it was compared with the map with the radar imaging method. For this purpose, model evaluation criteria such as Nash-Sutcliffe (NS), RMSE,,MAE)and MARE were used, which 0.9524, 0.0018, 0.0012 and 0.1545 were obtained respectively.

Groundwater recharge or deep drainage or deep percolation is a hydrologic process where water moves downward from surface water to groundwater. Recharge is the primary method through which water enters an aquifer. Groundwater recharge depends on several factors such as infiltration capacity, stochastic characteristics of rainfall, and climate factors. Groundwater recharge is of great importance especially in semiarid regions. In arid and semi-arid regions of the world, groundwater serves as an essential alternative to surface water resources for water supply purposes. It plays a significant role in meeting the water demands of man and the ecosystem and is perceived as the panacea to the looming water scarcity scare. Determination of recharge quantity provides worthy help for managers in water resources management. Ground water recharge includes recharge as a natural part of the hydrologic cycle and human-induced recharge, either directly through spreading basins or injection wells, or as a consequence of human activities such as irrigation and waste disposal. The Soil and Water Assessment Tool (SWAT) is a river basin scale model developed to quantify the impact of land management practices in large, complex watersheds. SWAT is a public domain hydrology model with the following components: weather, surface runoff, return flow, percolation, evapotranspiration, transmission losses, pond and reservoir storage, crop growth and irrigation, groundwater flow, reach routing, nutrient and pesticide loading, and water transfer. SWAT is a continuous time model that operates on a daily time step at basin scale. Its objective is to predict the long-term impacts of management and of the timing of agricultural practices within a year (i.e., crop rotations, planting and harvest dates, irrigation, fertilizer, and pesticide application rates and timing). It can be used to simulate at the basin scale water and nutrients cycle in landscapes whose dominant land use is agriculture. It can also help in assessing the environmental efficiency of best management practices and alternative management policies. In this study, the hydrologic process of the Marvast basin was simulated using SWAT Model in order to determine the amount of groundwater recharge in Marvast plain. In this way, firstly, the required maps i.e. slope, soil and land use maps were produced. In order to produce land use maps, panchromatic and multi-spectral imagery were fused to enhance the spectral and spatial resolution of Landsat imagery. In the next step, the fused imagery was used to produce land use maps using pixel based and object oriented image processing techniques. The slope map was produced using digital elevation model. The soil map was also produced using soil profiles in the regions. The requisite climatic data were also imported to the model with a daily scale. According to the importance of irrigation and its effect on evapotranspiration and groundwater recharge, irrigation amounts ​​were also considered importing irrigation plan in SWAT Model. Afterwards, the model was calibrated using SWAT CUP software and the SUFI-2 algorithm. Finally, the verification showed that the model with Nash-Sutcliff of 0.59, coefficient of determination of 0.83 and the root mean square error of 0.05 has a relatively good performance. The results showed that object oriented image processing technique outperformed pixel based technique. It was shown that the amount of groundwater recharge was 27082602 cubic meters and the irrigation water return coefficient is 34%. It was confirmed that SWAT Model has a relatively good performance for groundwater recharge modeling. Improving the cropping pattern, preventing development of unauthorized wells and excessive groundwater withdrawals, as well as proper irrigation systems, can be effective in reducing the groundwater storage deficiency and preventing an increase in water resource crisis. This study showed that this model is not efficient for short term runs, however, its performance is better for long term runs. It is suggested that the SWAT and MODFLOW Model be used together to study both surface and underground currents. Also, lysimeters or SWAP Model can be used to better determine the amount of return flow and groundwater recharge.

 Considering the rapid changes occurring in natural phenomena of the earth and their considerable influence on human life throughout time, it is crucially important to thoroughly examine such changes so that one can better understand the natural and human processes involved in those changes. Monitoring and assessing the areas where the aforementioned changes occur are considered as important steps in national development and the management of natural resources. In this regard, remote sensing technology is uniquely applicable in collecting information concerning such phenomena, taking into account various advantages of multispectral satellite imagery, including their availability and interpretability. This study, therefore, sought to investigate the changes made in Arjan wetland using RS and GIS technology. To put it more precisely, the current study examined the changes that occurred in the wetland’s banks, the decline of the area covered by the wetland’s water, and the changes made in the earth’s surface temperature and groundwater level. Throughout the past few decades, remote sensing technology has widely been used by scholars to detect such changes over time. On the other hand, coastal areas, especially inland lakes, have received special attention as ecological environments.

 This study used two types of data: meteorological data including precipitation, temperature (average, maximum, minimum), humidity, evaporation, and transpiration data, and remote sensing data, including the information collected from Landsat and MODIS images to calculate water indices and surface temperature. It should be noted that MODIS satellite images used in this study possessed low spatial resolution and high temporal resolution. Moreover, the NDWI was calculated for the study period (1968-2018) using coding in the google engine system. On the other hand, grace satellite imagery was used to estimate the alterations made in the groundwater level within the study area. Moreover, the data regarding the observed wells within the study area were used to validate the results and zone the aquifer’s water level. To determine the optimal position of the earth's surface and remove hydrological effects, the GRACE satellite (GLDAS model) was used.

 Like other lakes, the Fars province’s lakes are completely dependent on the status of water resources in the related watershed. Having been dried up since 2013, Arjan seasonal wetland, where the water height reaches one meter during high water periods, is currently in critical condition. In winter and spring, the surplus water is stored in the surrounding plain due to the increase in the plain’s surface inflows and the limited irrigation capacity in its eastern part, turning the wetland into a lake. In this study, first, the area of ​​Arjan wetland was examined in terms of climatic parameters. While Arjan Wetland experienced lots of fluctuations throughout the study period (1986-2018), it could be argued that its main crisis started in 2010 when the area of ​​the lake was reduced to less than half, and finally became zero in 2013.According to the obtained results, the wetland had its largest area in 1989 (14.78 square kilometers) when, based on data recorded at the meteorological station, the precipitation rate was 488 mm, which is regarded as one of the maximum precipitation rates throughout the study period. On the other hand, the time series data collected from the GRACE satellite and validated via Piezometric well’s data were used to examine the status of groundwater in the Arjan aquifer during the study period (1986-2018). The time period considered for the investigation of the changes that occurred in the aquifer was from 2003 to 2017. According to the data extracted from the GRACE satellite, the highest amount of groundwater decline occurred in 2018 by 20 cm. Also, the analysis of the general trend of changes shows that the decline rate is more than 8 cm per year.

 The consequences of climate change may be exacerbated in different regions by human activities-induced changes in the climate and the drying up of inland continental lakes. As a climatic hazard, the drying up of lakes is a critical issue to be taken into account, the consequences of which, as shown in this study, will affect the climatic conditions of the region and even the surrounding areas. Arjan wetland is an Iranian seasonal lake with fresh water whose area has been declining in recent years due to climate change and reduced precipitation rate, getting totally dried up recently. As found in this study, the wetland has completely been dried up as a result of a significant decline in its area from 1986 to 2018. It was also found that the Arjan aquifer’s groundwater level has decreased by roughly 20 cm.

Rapid population growth, increasing water demand, decrease in precipitation, and occurrence of drought may increase the use of water resources, especially the extraction of groundwater resources, leading to a drastic decline in groundwater level, and consequently the occurrence of land subsidence phenomenon. There are various methods for monitoring land subsidence. However, from among ground and space-based methods for the detection of earth crust deformations, the application of Interferometric Synthetic Aperture Radar (InSAR) on the collected data is considered as the most proper method in terms of accuracy and continuous spatial coverage. 

Located in central Iran in the west of Yazd Province, Abarkouh plain is a part of the Abarkouh – Sirjan basin, covering an area of 1390 km2. The area consists of alluvial fans and plains, surrounded by mountains on the west, south, and southwest and bounded on the east by Abarkouh Playa. This study used 46 satellite images taken from 2014 to 2018 to measure the amount of land subsidence in the Abarkooh plain. Moreover, the Shuttle Radar Topography Mission (SRTM) DEM was applied with 30 m resolution to remove the topography effect. A small Baseline Subset (SBAS) time series analysis was also performed to examine the short-term and long-term behavior of the subsidence.Decline in groundwater level and the subsurface sediment thickness are the two most important factors affecting the subsidence. The data used in this study were collected from 34 piezometric wells and 77 geologic logs. Finally, the most effective factors involved in subsidence and their relationship with other factors were investigated by comparing the output of the subsidence map and other existing maps.

The study's results indicated that the subsidence occurred in the east, northeast, and north of the area with the maximum accumulated value of 21, 10, and 6 cm, respectively, over four years. Moreover, the study of groundwater level and the thickness of fine-grained sediments showed that despite the decline in water level throughout the whole plain, subsidence is observed only in regions with clay subsurface sediments. According to different trends of decline in the groundwater level of the study area, groundwater level variations are changed during three periods. Accordingly, the water level declines during the first period in the east, northeast, and north of the area, while it increases in the west and southwest of the region. However, the decline in water level occurs throughout the whole region during the second period, and it is decreased at a lower rate in the east, north, and northeast during the third period.

In the first period, the comparison of the location of areas with increase or decrease in their water level with their corresponding areas on the Landsat showed that the water level declined in those residential and agricultural areas where there are more water wells, and, therefore, the subsidence rate is much more than other areas. On the other hand, the study of areas with an increase in water level suggested that the aquifer of these areas was recharged by mountains and alluvial fans.In the second period, those areas whose water had declined in the previous period experience more decline. Therefore, it can be concluded that the aquifer had not sufficiently been recharged in wet periods. In other words, the increase in the decline of the areas' water level occurred due to the decrease in the recharging of the underground waters because of several years of drought, and the increased groundwater withdrawal caused by the development of agricultural lands. However, despite the sharp decline in the areas' water level, no subsidence was found in the region.In the third period, some piezometric wells were dried, and the water level decline was significant in the west and southwest areas, which could be attributed to factors such as increased acreage, creation of new industrial centers, etc. Therefore, it could be argued that the subsidence rate of this four-year period will certainly return to the hydraulic conditions before this period. Thus, it can be concluded that in addition to the decline in groundwater level, other geological and hydrogeological factors play an important role in causing subsidence.

In this research, it is tried to identify the potential status of groundwater resources in different parts of the Telvar watershed using two machine learning models including support vector machine and random forest models. Initially, information about the wells in the region was received from the Regional Water Company of Kurdistan. The wells in the area were randomly divided into two groups of training (including 70% of data) and validation (including 30% of data). Elevation, slope, slope direction, lithology, pedology, surface curvature, land use, topographic moisture index and distance from the river were selected as predictor variables and their map was prepared in the GIS environment. The data of the training group along with the maps related to the predictor variables were entered into the support vector machine model and the random forest model. Based on the data of the training group, the parameters of the model were calibrated and adjusted and the potential of groundwater resources was predicted. The prediction accuracy of the models was determined using the statistical method of performance characteristic curve in two stages of training and validation. The results showed that accuracy of the random forest model (98.4%) was more than the support vector machine model (98.1%).

Morphometric analyses play an important role in understanding the geo-hydrological conditions of basins such as identification of the and potential management of groundwater resources. A hydrological DEM was prepared to draw the drainage network in four sub-basins of Lake Urmia. Linear, surface, and topographic morphometric parameters were calculated to prioritize the potential of groundwater resources in the sub-basins. The mean values obtained from the rank of the parameters in each sub-basin were close and the sub-basins were prioritized as Nazluchai, Baranduzchai, Shaharchai, and Rouzehchai, respectively. Furthermore, the morphometric indices of TPI, TRI, VRM, surface curvature, and surface ratio were studied to prepare the spatial value map of the groundwater resources. Each map was prepared and classified with the same cell size in seven classes and the morphometric index map was combined with the same weights. The map of potential groundwater areas under the study area was obtained with values of 2.2 to 5.0. The highest value in the map of the spatial value of groundwater resources belonged to the pixels that had the lowest TPI, the lowest TRI, the highest VRM, the lowest surface curvature, and the highest surface ratio. The findings were confirmed by examining the location of springs and yielding wells in the study area.

Desertification is defined as the reduction of the ecological and biological potential of the earth, which occurs both naturally and artificially. This phenomenon is one of the important problems of countries for sustainable development management programs, which is the result of a combination of various environmental, human and climatic factors. Water is recognized as an important and influential factor that is the main source of life and also guarantees the survival of sustainable ecosystems. Since water is more important in arid and semi-arid climates than in other climates, measures should be taken to properly manage water in order to prevent critical conditions in these areas. The purpose of this study is to investigate the status of water criteria to assess desertification. Due to the many effects that water indices have on the development of desert areas, in our study, we used quantitative and qualitative indices of groundwater such as electrical conductivity (EC), sodium absorption ratio (SAR), color (Cl), falling groundwater level and irrigation systems to study and determine the class of desertification intensity in Mehran plain. The IMDPA model was applied to evaluate the desertification situation. The results showed that the indices of decline and irrigation systems with average values of 3.11 and 1.75, respectively, have the greatest impact on the desertification process in the region. According to the groundwater status map in the destruction of resources in the study area, it can be concluded that 32% of the total area is in the low class, 48% in the middle class, and 20% of the total area is in the severe desertification class. In general, water resources management should be a priority for executive agencies to prevent desertification.

Due to various sources of contamination in the urban aquifers, the potential for pollution of groundwater resources is high. Thus, the vulnerability of groundwater resources can be very effective in identifying vulnerabilities and sensitive groundwater aquifers. The aim of this study was to present a modified DRASTIC Model to determine groundwater vulnerability in Urmia urban aquifer. To this end, parameters with low impact such as slope and aquifer media were ignored from the DRASTIC Model. Instead, land use, urbanization index, water value and pollution sources were added to the model. Also, the impact of unsaturated zone media and recharge layers were corrected. Results of the modified DRAST-VUL Model in the study area demonstrate that in most areas, the risk of pollution is low to moderate and the vulnerability in 29% of study area is high due to agricultural and industrial activities and low groundwater depth. Considering the results, the vulnerability index is the most sensitive measure to the parameter of pollutant sources, land use and the unsaturated zone. The sensitivity of the model to recharge, transmissivity and water value parameters were low due to the increase of impermeable surface in urban area. Based on positive results obtained from model validation through nitrate, the proposed model can be considered as an effective tool for the protection, revention and optimal utilization of groundwater resources in the study area. Also, this vulnerability model can be used for other urban aquifers.

groundwater. In the present study, the 3-year drought and wet periods were determined using 23-year rainfall data of four meteorological stations and the SIAP index. To investigate the physicochemical properties of groundwater, after considering the data of observation wells in the Eastern part of Gorgan plain, 14 deep and semi-deep wells were selected. Then, three criteria of EC, SAR, and Na were used to assess the water in the agricultural sector and the Schoeller diagram was used to assess the water in the drinking sector. To estimate the significant differences between the physicochemical properties of groundwater in the three periods of the wet period, drought, and long-term, an F-test at the probability level of 0.05 was used. The results revealed that the water quality of semi-deep wells is better than for deep wells in agriculture and drinking water sections. Based on the Piper diagram, the chemical facies of semi-deep wells are less diverse than deep wells. The results of both deep and semi-deep wells showed that chemical facies in the dry season show a greater tendency to achieve seawater composition. The results of the F test showed that there is a significant difference with 95% probability between groundwater quality parameters in semi-deep aquifers in wet and dry periods. In contrast, the occurrence of wet and dry periods in the study area had little effect on the physicochemical properties of deep aquifers.

In recent decades, flood-spreading and artificial flood recharge have been used at the proper time and place for optimal utilization of floods in arid and semi-arid regions. The importance of these projects in Iran is mainly due to the excessive use of groundwater resources and recent droughts, which have rapidly decreased the level of underground aquifers. Therefore, in a country like Iran, which is regarded as an arid and semi-arid region, performing such projects is essential for water resources management and flood control. Evaluation of the performance of watershed management projects in different countries worldwide has a history of more than 80 years. Thus, this study sought to determine the long-term effects of this project on flood control and underground water recharges, especially in dry years, through a technical investigation of the Mehriz flood-spreading project.

This study used technical evaluation methods to evaluate the Mehriz flood-spreading project, which was carried out in two ways: statistical analysis and fieldwork. In the first method, all necessary data were collected and analyzed. In the second method, field visits to the project were made, the pros and cons of the note plan were identified, and the technical evaluation of the plan was performed. This way, the discharge of qanats was investigated before and after applying the water-spreading project.

The comparison of average annual discharge in Fakhrabad River's hydrograph before and after the project shows that from July to November, the flow rate in each period was equal to zero, and from December to April, the river's flow rate was less in the pre-project period than what it was in the post-project period. Moreover, the average discharge rate in the month before the project began was lower than the rate reported after the project finished. Also, the average rate of post-project discharge in May and June was less than the rate reported for the pre-project period. The study's results indicate that while most pre-project floods occurred in late spring and early summer, the post-project floods occurred in late winter and early spring.

As mentioned earlier, this study investigated the effect of the Mehriz flood-spreading project on qanat discharge. According to the study's results, Baghdadabad's qanat in pre-project years was less than that of control 1 (Ibrahim Abad) and control 2 (Henza). During the years since the project was implemented, these qanats' discharge rate was higher than that of both control qanats. A comparison of the three-year mean discharge of the Baghdad qanats in May, August, and February in two ten-year periods before and after the implementation of the project showed that these qanats' discharge rate was increased in pre-project years. Therefore, implementing the flood-spreading project has helped increase the volume of water in those qanats. Also, the result of the statistical t-test showed that this aqueduct's flow rate has increased in pre-project years.The changing trend of the Khairabad qanat's discharge in Yazd indicated the positive effect of implementing the flood-spreading project on the qanat's discharge in post-project years. On the other hand, the result of the t-test for Mohammadabad qanat before and after the implementation of the project suggested that the qanat's discharge rate in pre-project years was less than the rate reported for the post-project years. Also, a hydrological comparison of the average quarterly discharge rates of the qanats with those of the control qanats pre and post-project years showed that the discharge rates of Khairabad and Mohammadabad qanats had gone through a downward trend from 1987 to 2007, indicating no effect of the flood-spreading project on increasing the discharge rate, which is considered as one of the drawbacks of the flood distribution plan. This could be attributed to the fact that the project area is located in a place where flood water naturally spreads and nourishes most channels. Moreover, diverting the water of the Fakhrabad channel and spreading the flood water to a particular place prevents some downstream qanats (such as Mohammadabad) from being fed by the floodwater, which, in turn, may upset the floods' balance and negatively affect the behavior of the basin's residents.