فصلنامه پژوهش های ژئومورفولوژی کمی
سال یازدهم شماره 2 (پیاپی 42، پاییز 1401)

Earth is an active element in the human environment and has an important impact on other elements and general environmental characteristics. Identification and classification of land features are very important for the environment, hydrological research, geological structure analysis and other geological research (Liu et al., 2015). The land surface consists of various landforms formed by internal and external processes (Salz et al., 2016). ). Therefore, landform classification is one of the most important methods in geomorphological mapping to better understand the surface processes (Boko, 2001). Dynamic changes in different periods and existing conditions such as climate change and human activities act differently and the difference of these changes in different periods has changed the behaviors and shape of landforms, so to plan and create different models and algorithms. It is necessary to identify and measure the behavior of dynamic changes and, consequently, to identify the evolution of microlandforms. The diversity of existing UV systems is increasing rapidly and is a powerful tool in geomorphology in detecting topographic shifts to link processes and dispersions to erosion and sedimentation rates and patterns (Jeans 2012). The use of UAVs allows us to do this. Allows us to achieve the desired results by using data with a resolution of at least 10 cm, 3 bands, wide coverage and short visits (Dulrents, 2019). Recently, new algorithms and convolutional neural networks (CNNs) have become a new way of calculating several problems, such as image classification, object recognition, semantic segmentation, and so on. CNN can display a hierarchical image of the input data with acceptable resolution of the desired features. In recent years, these types of neural networks have been used to solve several tasks from different fields, including remote sensing, in which they have great advantages due to various problems such as pixel-based classification for land use, target detection such as landforms. Roads have shown human and natural features and image sharpness (Dolrenets, 2019).

In this study, the boundaries of the study area were limited using 1: 50000 topographic maps, Google Earth images, and UAV images. During a field visit to the area in the fall of 1398. UAV images were processed with ENVI 1.5 software, Arc GIS 3.10 and coded in Python program. The spatial resolution of these 10 cm images related to the two periods of 1396 and 1397 was prepared by the Ministry of Energy. Using UAV images and executing a random forest model with a map scale of 1.1000, the classification of microlandforms and their transformations were extracted. The steps and implementation method of the random forest algorithm are described below.The method used in this study to extract microlandforms is pre-trained transfer networks.In this method, the coefficients and weights trained to very deep neural networks were extracted using a UAV data set of a site with two images in the period of 1396 and 1397. In this method, very deep networks were used on this trained data in a ready-made manner with specific coefficients.

Classification based on stochastic forest modelIn order to study the changes of different microlandforms, the random forest algorithm was used and the UAV images were classified into five classes of road, bedrock rocks, soil, vegetation and water with a scale (1: 1000).g. A supervised learning algorithm was implemented on UAV images (1397-1397) using random forest. These images were used as input for both classification and regression. In the initial map, written with Python, the three major classes of soil microforms, vegetation, and galls were identified and classified into five classes by classification (Figure 5).Changes of microlandforms with stochastic forest model in the period 1397-1397After classifying and creating a class on UAV images using random forest algorithm, changes in microlandforms were identified during the period 1397-1397. This algorithm with an average accuracy of 89%, determined that the changes of Afjeh microlandforms in the period 1397-1397 occurred in the range of vegetation and soil (Figure 6). So that the first rank of the most area changes in vegetation to soil was 66.64 and the second rank of soil to vegetation was 16.59% (Table 1, Figure 7); These changes were observed due to the greater dispersion of vegetation around the Jajroud River and the rock bed in the west of the study area. Unchanged areas in the bedrock of the river and soil cover and related microforms were observed in the central region of Afjeh.

In addition to field observations, the accuracy criterion was used to evaluate the evolution of microlandforms in the Afjeh region; The ratio of correctly classified pixels to total pixels was considered. The percentage given for the accuracy was obtained from this criterion. The study of the effect of this model on accuracy showed that the use of the features obtained from this network in the ability to distinguish different classes in UAV images is very useful. Thus creating a near-ideal model in the random forest algorithm. The results showed that the most changes of microlandforms in this model are related to the change of vegetation to soil (66.64%) and in the next rank is the change of soil to vegetation (16.59%). According to the obtained results, it was found that the flood in Afjeh region in 1397 has caused major changes in the region. As it has the greatest impact on the vegetation of the region, which has destroyed a large percentage of it. Vegetation-dependent microlandforms have also undergone major changes, so that the graph of its changes shows the highest level of turbulence compared to the more stable microlandforms of the Jajroud river bed. The diversion of the river is one of the changes observed in this period. In addition to the above, due to declining rainfall, recent droughts and floods; Sheetwash, ditches and galleys are more prevalent in the study area, indicating large changes in microlandforms and high erosion rates in the study area.

In recent years, the necessity of using numerical multiphase models to separate and simulate bed sediments and suspended loads of rivers has received much attention. Most numerical models of sediment transfer of bed load and suspended load are examined separately and semi-experimental methods are usually used to predict bed load. Although these methods have been widely used, they do not show the details of the mechanisms controlling the sediment transport process well and in turn have problems (Oda 2019). Today, quasi-two-dimensional mathematical models are widely used as an optimal and efficient solution in hydraulic issues of flow and sedimentation of rivers. In these models, velocity changes across rivers are simulated by numerical solution of Navier-Stokes differential equations under steady and uniform flow conditions (Zahiri et al., 2015). Lai et al. (2019) in the study of flow and sediment transfer capacity with a three-dimensional model using the governing equations of flow and suspended sediment, showed that the model has a good agreement between flow and sediment with experimental data.

Ekbatan Dam watershed is located in the southeast of Hamadan city and is below the Qarachai river basin of Hamadan. In this research, the second-order discretization method of the Fluent model to separate the bed and suspended load from Reynolds stress numbers to determine the motion threshold and to analyze the motion pattern and sedimentation of sediment particles in different flow tubes in the laboratory glass channel, from soft Fluent and Acobas software were used. Then, the results of Flont model were evaluated and calibrated with the measured data in the laboratory glass channel. In this way, fine sand and silt particles were placed in the laboratory glass channel in a flow path with a speed of 0.5 m / s and the distance traveled. It was measured by a camera with a very high frame connected to the recording channel and with the output animation of Acobas software. In the next step, the simulated data of Flont model were matched with the data measured in the laboratory and the error percentage was measured. Finally, the appropriate mathematical model for the amount of displacement of different sediment particles was determined based on the particle diameter and the location of sediment particles in the flow path, the distance traveled by different sediment particles in the laboratory flume.

The simulation results showed that most of the sediment load of fine sand and silt in the laboratory channel is carried by the Soffman lifting force in the second flow tube. And the performance of this force has caused the transport of most sediment load in the form of suspended load in the Yelfan River. The simulation results showed that after the passage of 0.2 m from the beginning of the flow in the channel, the sedimentation process begins and the accumulation of sediments increases with the continuation of the flow downstream and near the reservoir of the dam. Studies show that due to the presence of isothermal lines and creating a constant flow and velocity in the second flow tube, the suspended sediment load is transported in the riverbed throughout the year to the dam reservoir and the main volume of the reservoir during this process by fine sand sediments and The silt is filled. The study of the measured error percentage indicates the high agreement of the Fluent model with the data measured in the laboratory and shows that the model has a very good ability and accuracy in simulating the movement of sediment particles with different diameters.

The use of multiphase and multiphase models in the analysis of sediment transport by considering suspended particles as a second phase continuous with the fluid phase interaction seems very necessary. Evaluation of the obtained results shows that Flont software with very high and acceptable accuracy has well simulated the transport, transfer and sedimentation of sediments with a range of different ranges. This is important in the sense that the fluent model has high efficiency and accuracy in the study and evaluation of suspended sediments such as fine sand and silt, which in most studies due to the fine grain of these sediment particles, difficult to study and Or not possible. Examination of the percentage of measured error for laboratory and simulated data shows the high agreement of Flont model with data measured in laboratory conditions and the correlation between laboratory results and Fluent model is more than 97%, which is acceptable. Therefore, the combination of Fluent model and laboratory conditions can be a very useful and accurate tool to simulate the movement of sediment particles, determine the location of sedimentation, control erosion and sedimentation and select soil conservation and watershed management projects in river basins.

Glaciers provide researchers as important sources for obtaining environmental information, water resources, agriculture, as well as climate change trends in the past, present and future.In the study of glacial circuses, allometric and morphometric study of circuses helps to identify the nature and how the processes affect during different periods on these glacial landforms.By measuring the dimensions and geometric shape of these landforms with mathematical and statistical methods, a lot of information about environmental and climatic conditions can be extracted from them.In this study, the morphometric and allometric indices of circuses in the heights of Silveh Basin in northwestern Iran on the border of Iran and Iraq have been identified, classified and analyzed using geomatic models and new methods invented by Seif (2014). For this purpose, digital DEM altitude map (10 meters) (received from Aster satellite), topographic map sheets of 1 / 50,000 Piranshahr and Sardasht, geological maps of 100,000 Naqdeh and Sardasht and Google Earth satellite images were used. Arc GIS 10.5, Global Mapper18, Google earth, Surfer11, Minitab16, Excel software have been used to produce composite maps and extract the required data and information. After determining the study area and cutting it using the DEM map, the layers needed to identify and analyze the morphometric and allometric parameters of glacial circuses were prepared and produced To identify and classify the glacial circuses of the region, the methods of Rudberg-Wilburg and Evans-Cox have been used. For morphometry and allometry of circuses in this area, indices such as (W), (L), (H), (W / H), (L / H), (L / W), and the size of circuses have been used. . Based on the research results, 33 glacial circuses were identified in the heights of Siloheh basin, of which 2 circuses are in N2 category, 11 circuses are in N3 category, 15 circuses are in N4 category and 5 circuses are in N5 category. Allometric study of basin circuses shows that the coefficient b for the longitudinal axis of circuits N3, N2 is equal to 0.88 and for circuses N4, N5 is 0.90 which is B <1. As a result, the allometric behavior of the circuses in this area is negative and in general, the circuses studied in this area have a lower degree of development and Quaternary glaciers have had a poor performance in this basin.From the glacial circus formed in the heights of Silohe Basin, according to the Wilburg and Rudberg classifications, 2 circuses are equivalent to 6.06% of the total circuses in category N2, 11 circuses are equivalent to 33.33% of the total circuses in category N3 and 15 circuses, equivalent to 45.45% of all circuses, are in N4 category. Also, 5 circuses equal to 15.15% of all circuses are in N5 category. According to Evans and Cox classification, there are 2 circuses in the good and developed category, 11 circuses in the definite category, 15 circuses in the weak category and 5 circuses in the border category in the study area.The average amplitude of the coefficient b changes for the longitudinal axis of circuses N2 and N3 is higher, ie these circuses move more towards evolution and development. In N2 and N3 circuses, the coefficient b for the longitudinal axis of the circuses is equal to 0.90. This value is equal to 0.90 for N4 and N5 circuses. In circuses of both categories is B <1. This indicates that the allometric behavior is negative for the longitudinal axis of the circuses of both categories. Also, the coefficient a is 0.92 for the transverse axis of N4 and N5 circuses and 0.70 for N2 and N3 circuses. Also, there is no isometric situation for circuses of both categories. Therefore, in general, the activity of glaciers during their rule and now has not had much impact on the development and evolution of circuses in these altitudes, and circuses in these altitudes need a long time to grow and develop. Glaciation in these roughnesses acts as valleys and due to tectonic activity, circuses have less development and evolution.In the study of glacial cirques, the study of regional power and strength of cirques helps to identify the nature and how the developers of the effect during different periods on these glacial landforms. By measuring the dimensions and geometric shape of these landforms with mathematical and statistical methods, a lot of information can be extracted from them in terms of environmental and climatic conditions. The purpose of this study is to identify, classify and also analyze the morphometric, allometric and isometric characteristics of glacial cirques in the heights of Silveh basin on the border line between Iran and Iraq in West Azarbayjan province. In this work, the digital elevation model and its adaptation to the slope map classified in the software environment has been used. To identify and classify the glacial cirques of the region, the methods of Rudberg-Wilburg and Evans-Cox have been used. For morphometry and allometry of cirques in this range, indicators such as (W), (L), (H), (W / H), (L / H), (L / W), and the size of circuses are used. Be has been. Based on the results of the research, 33 glacial cirques in the heights of Silveh basin were determined, of which 2 circuses are in N2 category, 11 cirques are in N3 category, 15 cirques are in N4 category and 5 circuses are in N5 category. Examination of the forces of the basin shows that the coefficient b is 0.88 for the longitudinal region of N3, N2 circuses and 0.90 for N4 circuses, which is B <1. As a result, the behavior of the power forces is regional, and in general, the circuses under study in this area are not less than the degree of development, and Quaternary glaciers in this basin have had a poor performanceKeywords: Glacial Cirques, Morphometry, Allometry, Silveh Basin

One of the environmental hazards and ecological crises that the world is facing today is the phenomenon of land use change (Mousavi et al., 2015) and awareness of land use changes over a period of time for planners and managers. It is very important (Tachizuka et al., 2002). On the other hand, soil is one of the most important natural resources that plays an important role in agricultural production and food security (Moghadasi et al., 1397) that during the erosion process, soil particles are separated from their main bed and with the help of a transfer agent to They are transported to another place (Maslink et al., 2017; Research et al., 2011). Surface soil erosion reduces the depth, reduces the moisture capacity and the loss of organic matter and nutrients and thus reduces soil fertility (Parvizi et al., 1399).

The research is an applied research and the result is the study of land use change and analysis of soil erosion potential in the basin upstream of Yamchi Dam in Ardabil province. This study is based on the use of remote sensing methods to achieve land use change over a period of 21 years and the use of ARAS multi-criteria analysis method in GIS environment to zoning the potential of soil erodibility of the basin. It is above the Yamchi Dam. ENVI, Ecognition, Arc GIS, Idrisi and Excel softwares have been used for image processing and data analysis. In order to investigate the risk of erosion in the data collection stage, first according to the natural and human conditions of the region, slope factors, lithology, land use, rainfall, distance from the communication road, distance from waterway and soil, as effective factors in Basin soil erosion was identified. In the next step, information layers related to each factor were prepared in the GIS environment. The information layers of communication routes and waterway network were prepared and measured using the map of communication lines and rivers of Ardabil province. The slope layer was prepared using a digital model of 12.5 m altitude, Alos satellite, Palsar sensor, obtained from the site (vertex.daac.asf.alaska.edu). To extract a layer of information related to lithology (resistance of rocks), from the geological map of Ardabil province; Used at a scale of 1: 100000. The precipitation map of the basin was drawn according to the data of meteorological and rainfall stations using the precipitation gradient equation (P: 0.227H-85.04).

It can be said that in the erosion map of both study periods, mainly high-risk and high-risk areas in agricultural uses, poor and medium rangelands, man-made areas and barren lands are located. According to the erosion zoning maps in the study area, in 2000, the area of high-risk and high-risk floors was 74.35 and 206.51 square kilometers, the amount of these risk classes in 2021, respectively; Increased by 79.40 and 219.98 square kilometers. The reason for the increase in areas with the risk of erosion can be considered in the reduction of good pastures, medium pastures and mountainous lands and their conversion into agricultural areas, poor pastures and man-made areas. Saffari et al. (1397), Asghari Saraskanrud et al. (1398), Miyahi et al. (1400), Santos et al. (2017), Kiden et al. (2019), Kojo et al. (2020), Lee et al. (2021), Also, increasing the area of agricultural lands, barren lands and residential areas and in contrast to reducing pastures have been mentioned as the main reasons for increasing the potential risk of soil erosion.At the level of the study basin, by the villagers of the region, most rangeland lands; They have changed the use of agricultural lands, especially low-loss land. Although rainfed fields play an important role in increasing agricultural production and food supply, but land use change due to the impact on vegetation and soil surface erosion, intensifies soil loss and surface runoff and thus soil quality It affects. This change of use, if it is combined with not paying attention to land capability and observing the correct principles of tillage, leads to the production of surface runoff and thus intensifies erosion, which ultimately results in reduced fertility and reduced yields. According to the combination of slope and land use map, most of the sloping meadows in the basin, which are the focus of erosion, are scattered in the middle half and to some extent in the southern parts on slopes of 15 to 35%. Given that most agricultural lands in particular; The meadows of the region are located on sloping slopes, so plowing in the direction of the slope, especially during heavy rains, leads to soil erosion. Thus, in parallel plowing, the water from rainfall flows more easily in the cultivation furrows and is removed from the arable land and as a result, water and soil loss increase. On the other hand, uncontrolled harvesting of forage from pastures to feed livestock in the cold season and early grazing in spring has reduced the amount of pastures and intensified runoff with the onset of the rainy season, and this affects the morphology of rivers. It also has a direct effect and leads to a change in bed behavior.

Knowing the ratio of uses and how it changes over time is one of the most important things in planning and policy making. In addition, soil erosion can be considered as one of the biggest obstacles to achieving sustainable development in agriculture and the use of natural resources. For this reason, the phenomenon of erosion has been considered globally. It can be added that land use change is one of the important factors in causing soil erosion. Therefore, in the present study, land use change and its role in soil erosion using telemetry techniques and ARAS multi-criteria analysis for the two periods of 2000 and 2021, has been investigated.

Changes in the morphology of the riverbed at the confluence are a function of parameters such as the amount and direction of velocity, discharge and fluxes and the angle of collision of two different rivers, which is easier to measure during floods due to sudden changes in water flow and sediment. . Research focuses more on laboratory studies, while on land it may also be influenced by the morphological shape of two rivers. However, the normal flow of the river, especially with water exploitation, makes it difficult to observe bed changes. Occurrence of floods in the western region of Iran in 1398 will allow the study of a confluence of 110-degree meander to Meander of Gamasiab and Qarasu rivers.

The Gamasiab River flows in northwestern Iran in a northeast-southwest direction, near the Harsin in a mountainous region, in a northwest-southeast direction. The Qarasu River joins the Meander Gamassiab from outside Meander as it flows through the arch.The study on this link is based on the SRH-2D model. For this purpose, first water and sediment data were gotten from the water organization and then sediment samples were taken in the field and the river channel was survey with two-frequency GPS. By examining the sediments in the laboratory and entering all this data into the software, different models were implemented and finally the most accurate model was selected. The results of SRH-2D model were validated by ground controls and comparison of satellite images before and after the flood.

The spatial variation of the Froude number in the Chanel occur greatly in the first few hours of the flood. The variations disappear at the peak of the flood and the high but subcritical Froude number are set to only a few points, and when the flood subsides, almost uniform and subcritical characteristics usually prevail throughout the width of the Chanel. This situation is also seen in the pattern of shear stress distribution, so that it finds very small spatial fluctuations at the end of the flood. However, the most important thing that happens during the rising and recession of flood in the bed and riparian is the first that deposition occur at the first hours of the confluence point and then in the middle of the Gamasiab,s bed after 12 hours. The deposition is ended at the peak and transfer to the riparian. The most important effects of this sedimentation are bars that have expanded during the flood. Point bars are the most important among of the bars. However, in this place, the development of Meander Gamasiab is limited by Qarahsu river and since the steep slope of the valley does not allow to sedimentation inside the river, deposition is done on all zones of inner arch. Instead, Qarahsu take on this task and place sediment on the inner surface of the arch.Comparison of the results of this research with the results of the recent research which took place in the same flood valley (Gamasiab-Dinver confluence) with a distance of 37 km above this research shows relatively different results. However, It should probably expect less capacity to make change in morphology in Gamasiab-dinver than the same flood happens in downstream, in Gamasiab-Qarasu, due to less flood volume (700 m3/s at the peak of flood in Gamasiab and 200 m3/s in Dinver) and flood peak time (approximately 100 hours after the onset of flood), but the mode of evolution during the flood is such a way that the role of channel morphology is emerged very important. This needs to focus to following differences:1- Difference in sedimentation site - in that study, during the same flood, the stagnation area and the meander Gamasiab concave area were among the most active areas in terms of sedimentation, while in this study, the stagnation area did not experience much morphological changes and both the Gamasiab and its sub-branch (Qarasu) convexity area underwent many changes in terms of deposition.2 - Difference in sedimentation time - in that area sedimentation expands after the peak of floods, while in Gamasiab- Qarahsu is limited after the peak of sedimentation.3- Difference in erosion development - Erosion in terms of how it spreads in the Gamasiab-Dinever starts from the lower reaches of the main canal and continues retrograde upwards. But in this study, erosion starts from parts of the sub-branches and then, when the flood reaches its peak, the conjunction site becomes the most important place for the production of scour hole and then it develops downstream.4- Difference in erosion development time - scour hole development timing in Gamasiab - Dinver continues until the peak of flood and at this time, it almost stops, while in Gamasiab Gharasoo, the erosion reaches its maximum development at the hours after the peak of the flood.

At the confluence of mountain rivers, which are environmentally similar to the study area, that is, mainly one meandering branch receives another branch at a large angle, the structure of landforms is formed up until the peak of floods and erosive features develop in the middle of the canals almost some hours after the peak of the flood, while only a few kilometers above, when another confluence with the same river but with a different morphology and topography took place, the type and the form of evolution took place in a different way. The result is that the morphology of the canal produces various variables in terms of the angle of collision of the two branches, the method of collision (meandering or non-meandering), the position of the junction (point of collision of the two meanders), the valley constraint, the slope of the canal sides and previous landforms. They can affect the hydraulic factors of flow and sediment and play important roles in the production of new canal landforms.

Southeastern Iran has experienced a complex history of geomorphological, hydrological and climatic conditions during the Quaternary period.Considering that Jazmourian Playa is located in one of the driest regions of Iran and the world and is very sensitive to climate and environmental changes.Therefore, it is a very important area for studying climate and environmental changes resulting from dry and wet cycles in the past. The history of sedimentation under the influence of climate and the identification of dry and wet periods during the Holocene in Jazmourian Playa isthe subject of the present study.

Jazmourian plateau between latitudes 58˚-40' to 59 ˚-14' and latitudes 27˚,10' to 27 ˚, 41' in southeastern Iran and west of Sistan and Baluchestan province and east of Kerman province. It is located at an altitude of about 360-500 meters above sea level . The catchment area is about 69,600 square kilometers, of which about 34,160 square kilometers are mountainous areas, 32,440 square kilometers are plains and foothills, and the remaining 3,000 kilometers are swamps and salt marshes.For this study, intact sediment cores were used to reconstruct the Paleo climate. Five sedimentary cores with a maximum depth of 7 m and a total depth of about 30 m were collected and investigated from the sediments under of different areas of Jazmourian Playa using a hand-held core.Sedimentary facies were identified and distinguished based on sediment texture and composition, composition of destructive sediments and organic matter, color, presence of plant and shell residues, and other macroscopic components. According to sedimentological studies and changes in sedimentary facies, eight separable sedimentary facies belonging to river, playa, lake, delta and wind environments were identified.To estimate the time of climatic events in the region, the results of the survey of Vaezi et al. (2019) were used.

The stages of this research include data collection, published statistics, climatic data, telemetry surveys, field operations and coronation, laboratory operations, data processing and then interpretation and conclusion. In order to study the paleoclimate, changes in the sedimentary facies of the kernels based on macroscopic evidence (type of stratification surfaces, geometric form of sediments, sedimentary structures, fossil traces and contents, plant remains, color and changes) as well as sedimentation environment conditions, 5 intact sediment cores were harvested with a maximum depth of 7 m. The cores were prepared by a handy auger type. After determining the sedimentation status and type of sediments, studying the climate change and water level of the playa over time, the progress and regression of the coastline and the effect of these changes on the type of sediments and plant content of the playa, the harvesting position was such that Playa bed sediments should be allowed, maximum plaque sediment environments should be covered, at least one sample should be taken in each homogeneous unit. The location of the cores at the playa level was determined with appropriate distances and scattering so that climatic changes could be observed in them and the harvested cores could interpret various sedimentary environments in order to regenerate the climate in the region. Photographs were taken from the captured cores with a digital camera. The description of sediment cores and facies was carefully written and then sampling was done from inside the core collector for relevant analyzes according to the change of facies and type of sediments. As a result, eight major sedimentary facies were identified in the five studied brains . Facies were mostly clay, silt, sand, gravel and intermediate (combined) sediments with plant debris and evaporative sediments (gypsum and salt), which in most cases, alternation and interference in the mentioned sediments were seen frequently.

Sedimentological, paleoclimate and geographical studies of Jazmourian Playa have the following results In the sediments of the studied cores, there are five sedimentary environments including wind, river, deltaic, lacustrine and layered sediments. Facies of windy environment are often dry brown colored sands with high sorting and medium grain. River environment (flood plain) with mud and silty sediments, usually hard, without organic matter and with gypsum and brown color, lake facies with gray to light green sediments (characteristic of regenerative environments) muddy and granular with organic matter, soft and juicy Thin laminae were identified with coarser (silty) sediment layers. Deltaic environments with very high frequency of granular and granular sediments due to many changes in the energy regime of rivers leading to the blue basin are dark gray to brown due to the seasonality of the rivers in the catchment. Playa environments are characterized by the presence of large amounts of evaporative minerals such as salt and gypsum, dark brown sediments. The rate of sedimentation rate in Jazmourian Playa is different in different parts. This rate is 0.1 mm per year in surface parts and 0.4 mm per year in deeper parts. It seems that during at least the last 25,000 years, Jazmourian Playa has often experienced playa conditions. Due to the changes in sedimentary facies along the harvested sedimentary cores, dry periods are often observed with the spread of windy sands in the playa bed and wet periods with alluvial facies, which sometimes extend to the center of the playa. Wetter conditions are evident in late Pleistocene than in the Holocene in harvested kernels. Holoceneconditions in Jazmourian Play were similar to today

Mass movements (landslides, creeps, falls, mudflows, etc.) as one of the natural disasters, many environmental and human factors can affect their occurrence. The role of us humans in the occurrence of these movements in relation to environmental factors such as tectonics, rainfall, altitude, slope, etc. is very small. On the contrary, it is very much related to human factors such as land use change, irrigation and road construction, which are among the most important of these factors.Landslides are generally complex geomorphological features. Landslide sensitivity analysis requires consideration of their environmental context. Given the importance of spatial variables in natural hazard management, a large number of researchers have investigated the effects of these factors in modeling landslide risk and sensitivity. Landslides are one of the natural hazards that most people around the world suffer a lot of human and financial losses due to this phenomenon. Landslide risk management is critical to reduce the number of occurrences due to a set of topographic, geoenvironmental, hydrological and geological conditions.

Ziveh watershed with an area of 21686 hectares is located in West Azarbaijan province, southwest of Urmia city and in Margor Silvana section. This basin has an average height of 2265 meters, a minimum height of 1500 meters, a maximum height of 3479 meters and an average slope of 16.5 degrees. The average annual rainfall is estimated at 395 mm.Through extensive field visits and GPS, the location of landslides that could be accessed for recording was first captured as a polygon. The rest were recorded through Google Earth images. A total of 167 landslide polygons were identified in the area. By reviewing internal and external sources along with notes on the factors affecting the occurrence of each slip during the harvest of information layer points, a total of sixteen environmental, human and morphometric indicators were considered. Digital elevation model map with a resolution of 12.5 12 12.5 meters from the University of Alaska site. Land use map was prepared from the archives of the General Directorate of Natural Resources of West Azerbaijan Province and modified using Google Earth images. Fault data and petrology of the region from the geological map of Silvana sheet (1: 100000), and from the statistics of 13 stations around the basin of the rainfall map using simple kriging interpolation method considering the common statistical period Prepared in 1392-1368.Maps of environmental and human factors in ArcGIS10.5 environment and maps of geomorphometric indices in SAGA_GIS.6.4 were prepared through digital elevation model with pixel size (12.5 * 12.5). After obtaining the weight of each factor using Shannon entropy models, WOE and LNRF of landslide susceptibility zoning maps were prepared and evaluated using ROC curve.

The results of determining the most important factors affecting the occurrence of landslides and its relationship with effective factors in both WOE and LNRF models showed that Shannon entropy model in relation to identifying the most important factors influencing landslide occurrence and sensitivity zoning Landslides have been very effective in Ziveh watershed. According to the results of Shannon entropy model, the factors of topographic position, distance from waterway, distance from fault and land use had the greatest impact on the occurrence of landslides and the least effect related to annual rainfall, profile curvature and altitude. Investigating the weight of subclasses based on the frequency of the effect of each sub-factor for each layer of information expressing the greatest effect of geological factor, land use and then in the following categories of distance from waterway factor: fault and land use for WOE model And then LNRF. Therefore, there is a relatively good relationship between the effective weights identified from the sub-factors in the above models. Evaluation of zonation maps and landslide sensitivity using ROC curve shows that Shannon entropy model with sub-curve surface value (AUC = 0.915) has excellent performance in terms of quality and WOE and LNRF models respectively. With the area below the curve (AUC = 0.899 and (AUC = 0.860)), they have performed well in determining landslide sensitive areas.

The main purpose of this study was to investigate the relationship between factors and sub-factors affecting the occurrence of landslides. The results show that there is a good relationship between Shannon and WOE entropy models and then LNRF in identifying the effective factors based on the weight of the sub-factors. Therefore, in future research, these models can be used well in different conditions to zoning landslide sensitivity. According to the superior model of topographic position index, the factors of distance from waterway, distance from fault and land use have had the greatest effect on the occurrence of landslides. While in comparison, the effect of the weight of the sub-factors is more of the sub-factor that has an effect on the occurrence of landslides than the lithological factor. In general, it can be concluded that the role of natural factors in this basin has been more than human factors and the basin is inherently sensitive to landslides. In most cases, preventing and controlling landslide-prone areas due to natural causes is not possible or will not be easy and, if possible, can be very costly. The high sensitivity of this area to the occurrence of landslides to natural factors causes the least interference to cause a critical situation in the basin. Preparation of landslide susceptibility zoning map and identification of factors involved in controlling and implementing preventive measures in the instability of this basin and formulating a strategic plan - can be very efficient and management of unstable slopes in the study area Facilitate.

Instability of slope is one of the geomorphological and geological phenomena that plays an effective role in deforming the earth's surface. This process can affects human activities, because it can be dangerous phenomena. One of the important tasks of applied geomorphological knowledge is to study the location of hazardous places against various geomorphological hazards. Landslides is one of the most dangerous gemorpgholocal event, due to the recurrence of this phenomenon and its harmful damages, it is very important. The aim of this study was to identify landslide risk zoning in Kameh basin in the south of Semirom city, in Isfahan Province. Hu et al. (2020) used altitude, slope direction, curvature, lithology, distance from fault, slope, precipitation, land use, and NDVI to predict landslides in China's Jinsha Basin. The evaluation results show that the negative samples of "non-slip regions" produced according to the FT model are more reasonable and the combined method supported by the FT and ML models has the highest advance efficiency of about 94% of the total production accuracy. By Scenario-FT and then Scenario-SS (87%) and Scenario-RS (65%)Semirom is one of the landslide sensitive areas due to being located on the seismic zone of Zagros Mountain. Occurrence of many landslides is evidence of the sensitivity of these areas, which highlights the need for this study.

In this study in first step we have collected the landslides locations with using aerial photos, filed survery, and google earth images (GE). The second step of this research was to preparing 13 the most important variable including: Elevation, slope, aspect, geology, vegetation density, land use, soil texture, distance from fault, distance from road, distance from stream, topographic moisture index, waterway strength index and average annual rainfall . In the last step we applied the Maxent model for zoing of the landslide map. The Maxent model is one of the most common machine learning algorithms. The principle of this method goes back to the maximum entropy or close to reality. Maximum entropy or maximum turbulence is the name of the second law of thermodynamics, also known as turbulence law.

In this study, the Area-Under-Curvae index (AUC) for the ROC curve was used to evaluate the validity of the final model. The area under the curve was calculated for traing and testingdata. If the area under the curve is more than 0.9, the detection power of the model is considered very high. This value was obtained for educational data equal to 0.931 and for testing data 0.887 and shows that the detection power of the model is considered very high and the model can well cover different areas of landslide risk. To determine the effect of each variable on the landslide risk in the region, the percentage of participation of each variable was used using Maxent output. Percentage of participation in the model indicates that the most influential parameters on the landslide risk model are distance from waterway (17.1%), geology (14.1%) and distance from road (13%), respectively. And the least effective parameters are aspect (0.5%), stram power index (SPI)(0.7%) and topographic moisture index (0.9%), respectively. Based on the results, of the total area of the study area, 139760 hectares (84.69%) very low risk, 15449.5 hectares (9.36%) low risk, 6903.39 hectares (4.18%) relatively low The risk is 2,456.85 hectares (1.48%) high risk and 445.91 hectares (0.27%) are in the high risk category.

In this study, in result of poorly vegetation and agricultural, the amount of landslides is high. The results of this study showed that from 0 slope to slope of approximately 35%, the probability of landslide has increased exponentially and then with a gentler slope, the amount of landslide has increased.According to the classification of images, the area of very low-risk to very high-risk areas were 84.69%, 9.36%, 4.18%, 1.48% and 0.27%, respectively. To evaluate the validity of the final model, the sub-curve surface index (AUC) for the ROC curve was used. If the area under the curve is more than 0.9, the detection power of the model is considered very high, which in this study was equal to 0.931, indicating that the detection power of the model is considered very high and the model It can well differentiate between different areas of landslide risk In the slopes of zero to 35%, where man-made areas and agricultural use are the predominant uses in the region, it shows the great impact of man on the occurrence of landslides. Slope direction factor in the region shows that the most effective slope in the northern direction of the region due to rainfall and humidity, play an effective role in creating slippery movements in the region.

Rivers are among the most dynamic natural systems that any intrusion and occupation in them is associated with a negative reaction of the river in the form of floods, erosion, bed changes and so on. In this study, Kordan river due to its special geographical, ecological and ecotourism location is highly exposed to adverse human interventions such as severe harvesting of materials, agricultural and industrial activities, implementation of development projects in the riverbed, villa construction and encroachment on the river There are tourist activities, each of which has been very effective in changing the balance of the river. Since the life of this river affects groundwater nutrition, agricultural activities and climate adjustment of Hashtgerd plain, so its maintenance and optimal use is essential. In this study, the role of human factors in the imbalance of the Kordan River using Satellite images and HEC-RAS software have been studied. In many projects, only HEC-RAS software and hydrometric data have been used to simulate floods. The advantage of this research is the combined use of satellite images. The effect of land use change around the river as a result of human activities such as harvesting materials and its role in creating floods and changes in cross-sectional profiles in the Kordan River using HEC-RAS software. Therefore, in this study, in addition to flood simulation The role of human factors in creating imbalances and changes in the bed of the Kordan River was investigated. The main required data include Landsat 7 and 8 and Sentinel 2 satellite maps with an accuracy of 30 and 10 meters, respectively, from 1999 to 2021, Kordan River 1: 2000 topographic maps, hydrometric data and river boundary conditions. In order to calculate the maximum instantaneous flow rate with different return periods, the completed and extended annual maximum instantaneous flow rate of hydrometric stations in the region, including Deh Soomeh, Fashand and Najmabad stations, has been used for a statistical period of 40 years. Also, Pearson type 3 distribution was found to be suitable for fitting data from statistical distributions. Based on the results obtained from satellite maps for 22 years, it was found that a large part of the land around the river has been converted into industrial units and residential areas as a result of land use changes. For example, the area of ​​industrial units located around the river has increased from 59 hectares to 466 hectares (nearly 8 times), which is related to the expansion and construction of mammoth factories, Persia and asphalt production plants, crushers and New Jersey products. . Also, about 60 hectares of the main bed and floodplain of the river have been reduced. In the continuation of the work, using HEC-RAS software, floods with a return period of 2 to 1000 years were simulated. According to the results, the maximum depth The flow is related to the area of ​​sand holes before the old Hashtgerd road bridge. Regarding the speed, the railway bridge with a flow rate of 9 meters per second has the highest speed in the study area. The results of flood distribution show that in case of floods with a return period of 2 to 5 years, there is no danger to the lands and structures around the river, but in case of floods with a return period of 10, 25, 50, 100, 200 , 500 and 1000 years, 8, 17, 25, 32, 41, 53 and 64 hectares of residential, industrial and barren lands around the river, respectively, will be exposed to floods and will be submerged. Also, the width of flood zones for the return period of 2 to 10 years was 278 meters, 25 to 100 years 355 meters and 200 to 1000 years 473 meters. The area before the bridge is the old Hashtgerd road. From the results obtained according to the method called the Australian Standard, it can be seen that in 2 to 10 year floods, most of the study area is located in the category of safe or low risk areas and only at the exit of bridges in the path to The reason for the high flow velocity mentioned at 4 m / s is the critical situation. Regarding the return periods of 25 to 100, catastrophic and critical points are like the return periods of 2 to 10 years, with the difference that the area between the Tehran-Qazvin highway bridge to the old Hashtgerd road is in a very high danger class. Results It is different in terms of periods from 200 to 1000 years. Also, the entire area between the Tehran-Qazvin highway bridge to the old Hashtgerd road will be in the category of high to critical and catastrophic areas.

Flood modelling and watershed routing are the main topics of interest for hydrologists in the process of transforming rainfall into runoff hydrograph and streamflow through a watershed. In the design of some water systems, it is necessary to know the changes in flow over time (hydrograph). Empirical formulas, drainage pattern, simulation method, statistical estimation of maximum instantaneous flow rate, regional analysis and flood index method can be used to estimate maximum instantaneous flood in ungauged watersheds. Each of the flood modeling methods can be used in specific conditions. In the meantime, only methods that lead to the preparation of hydrographs are able to provide accurate details of flood hydrograph characteristics. Flood management based on hydrograph analysis approaches in ungauged watersheds is very difficult, so the use of empirical methods and physiographic parameters in flood prediction models can be considered as an in-hand and easy to use method. The direct runoff of a watershed, in addition to the temporal and spatial distribution of rainfall, depends on soil properties, topography, geomorphology and watershed drainage network. Obviously, there is a close relationship between the geomorphological characteristics and the hydrological response of a watershed. The use of Gamma distribution has been significantly expanded due to the production of smooth shape and flood hydrograph as well as the ease of extracting its parameters from the geomorphological characteristics of the watershed. The main aim of this study is the application of Gamma distribution using catchment characteristics to modeling the direct runoff hydrograph of Tamar watershed.

The Tamar watershed which located at east of the Golestan Province (1515 km2), was divided into subwatersheds and required parameters for simulation procedure were calculated and rainfall-runoff process modeled for each hydrologic unit, as well as simulated flow routed through the main reaches of the watershed. Since the reservoir gamma distribution is considered linearly in the two-parameter distribution, the storage coefficient of this reservoir can be estimated using the watershed characteristics. In this regard, the data required to determine the parameters used in the gamma distribution in flood simulation were extracted. Then, using the gamma distribution, the flood current in each sub-watershed was simulated. In the next step, using the Muskingum method, the flood hydrograph was routed through sub-watersheds. Then, taking into account the location of sub-watersheds and routing intervals, the unit hydrograph of flood moments was estimated for the whole watershed and converted into a unit hydrograph equal to one third to one fifth of the watershed lag time based on SCS method. In the next step, by multiplying the dimensions of the resulting hydrograph in the effective precipitation pulses, the flood hydrograph was modeled for each storm. Based on the available data and their relevance, eight corresponding flood and rainfall observational events were selected. The simulation results were evaluated with the criteria of coefficient of determination, relative efficiency coefficient, agreement index, and relative agreement index.

Based on the presented results and the visual comparison of the simulated hydrographs, it can be stated that the model results in estimating the components of flood hydrographs had an acceptable accuracy. The results of simulated and observed hydrographs comparison using coefficient of determination (60%), and index of agreement (74%) show that the accuracy of existing method is on the average at predicting complete shape of flood hydrograph. However, due to the use of experimental methods and coefficients in estimating the inputs of the modeling process, the existence of errors in the model results is largely expected.

As a concluding remark, it should be noted that using physiographic and easy obtained parameters can be considered as an appropriate approach in flood modeling, so the relationship between geographic and properties of the flood hydrographs be more elaborated in future research. The proposed flood modelling approach and application of Gamma distribution can provide a significant contribution towards flood management program in areas that limited data were available. It is identified that direct run-off hydrographs and model results are more responsive to variations in the value of the uncertain parameters. It should be noted that the modeling of complete hydrograph as well as the extraction of peak discharge components, time to peak and flood volume at storm events is one of the advantages of the proposed method. In other words, in addition to the possibility of comparing sub-watersheds in terms of flood occurrence, the shape of the hydrograph and its change over time in different parts of the drainage network can be obtained. Thus further investigation is required in order to evaluate variations in the model input parameters in different climate conditions.

The sensitivity of the drainage pattern to the active tectonics processes leads to a geomorphic expression that provides a useful tool to evaluate relative tectonic activity (Cox, 1994). Geomorphic indices provide a useful method for assessing the extent of tectonic activity; Especially in areas where earthquakes happen on faults in which there was not enough information in advance. The study area is in the west of Lut block, southeast of Iran, which is in the range of longitude from 55°22ˊ 15˝ to 58° 31ˊ17˝E and latitude from 28°50ˊ4˝ to 31°9ˊ30˝N. This region has a long history of devastating earthquakes, the historical types of which date back to around 1850AD. The occurrence of earthquakes on previously unknown faults (Bam, 2003) and the need to pay attention to areas in this part that have not yet experienced a devastating earthquake despite being surrounded by active faults (Kermen city), are the most important reasons that led us to find the best way of morphotectonic analysis and compare the results to seismic structures and data as a tool to identify structures and their activities also to estimate the seismic risk.

To obtain the drainage network layer, basins area, and water dividing layer in the study area, the hydrological modeling process was done by Arc GIS10.3 software. The basic data used are 30 m resolution DEM and geological maps. Also, to investigate the relationship between seismicity and tectonic activity, seismic data were used for earthquakes greater than 0.4 Mw. In this study, the results of calculating 7 geomorphic indices, including stream length-gradient index(SL), drainage basin asymmetry(Af), hypsometric integral(Hi), the ratio of valley-floor width to valley height(Vf), index of drainage basin shape(Bs), index of mountain front sinuosity(Smf), and Transverse Topographic Symmetry Factor(T), for 51 basins were analyzed by Iat and AHP methods. Finally, by using seismic data and field studies, we discuss our findings to compare the accuracy of AHP and Iat methods in analyzing morphometric indices to assess seismic risk, which is the aim of this paper.

The evaluation of the distribution of relative tectonic activity in the study area according to Iat, which is obtained by averaging the different classes of morphotectonic indices, divided the region into three categories in terms of tectonic activity. Class2, class3 and class4, have allocated 5.9%, 54.9%, and 39.2% of the total study area to themselves, respectively. It should be noted that none of the basins were in class1. 43.2% of epicenters were located in basins with high activity and 17.6% in low ones. Since the Iat index is not based on the weighting of the indices, all the indices were calculated with equal importance ratios. Therefore, there are some inconsistencies in comparing the Iat distribution map with the main structures of the region and the epicenter of the earthquakes. The AHP makes it possible to determine the amount of tectonic activity in the study area base on the weight and importance of each index compared to others, instead of relying solely on the average of each index (Iat). The values of the coefficient of determination(R2) are extracted from the graph of the indicators relative to each other. The correlation coefficient(R) was calculated from the roots of R2. After checking the acceptability of the Inconsistency, the final weights assigned to each of the indicators are (0.015)Bs, (0.012)Smf, (0.025)AF, (0.021)T, (0.104)Hi, (0.116)Vf, (0.708)SL. These results were classified into four categories. Accordingly, class1, class2, class3 and class4, occupy 21%, 24%, 31%, 24% of the total study area, in turn. The basins with very high and high tectonic activity, are all located along the main faults of the region, in addition, the distribution of earthquakes in these basins (81.8.% of earthquakes were in high active basins and 4.4% in low ones), shows how they are consistent with the results of AHP.

In this study, we tried to more accurately assess the impact of active tectonics and determine the most appropriate method for analyzing geomorphic indices, by comparing the results obtained from Iat and AHP methods. Proper matching of geomorphic features, calculated indices, and classification of relative tectonic activity obtained by the AHP, with the main structures, field observations, seismic data and previous studies in the study area, confirms the significant superiority and higher accuracy of AHP over the Iat in the identification of tectonically active areas which subsequently leads us to seismic hazard assessment. Based on the final map derived from the AHP, the study area was divided into four tectonic activity classes. The results show that morphological features in the study area are strongly affected by the main faults. The basins along them, generally show very high to high tectonic activity rates. The existence of many active faults, the epicenter of earthquakes and the location of most cities in the study area within or adjacent to basins with very high to moderate tectonic activity indicate the need for attention and additional studies there.The findings of this paper show how using a suitable way of morphometric analysis can help us to identify areas with the potential for seismic hazards. Due to its low-cost and timesaving, this method can be a good alternative for expensive and complex methods, especially in vast and remote places. As a result, it can be a useful tool for regional planners and decision-makers involved in seismic risk assessment and disaster risk reduction.

Groundwater is the most important source of water in many parts of the world, used in drinking water, agriculture, industry and related ecosystems. However, the lack of control over human activities and climate change can lead to the destruction of these valuable resources.Accordingly, in this study, the groundwater level of Parishan catchment in Fars province in the period 2008 to 2019 in relation to groundwater abstraction has been investigated and using Madflu modeling in different scenarios to reduce the level of aquifer for future years. Predict for different areas of this basin in order to show different degrees of crisis in different parts of the basin.

Parishan Lake catchment area is one of the semi-enclosed cups in Fars province (Kazerun city) between the eastern longitude of "251-52" to "501-43" and the northern latitude of "25.22" to "29.27". This basin leads from the north to the Kazerun basin, from the east to the Boram basin, from the south and west to the Jarreh and Baladeh basins. The area of this basin is 225 square kilometers, of which 40 percent (90 square kilometers) is covered with heights and 60 percent (135 square kilometers) is covered with plains and lakes. The maximum altitude of Parishan Basin is 1800 meters and the minimum altitude is 855 meters above sea level, and these altitudes extend from northwest to southeast.

In the present study, data and information from the study area such as exploitation and observation wells data including data related to 25 exploration wells and 960 exploitation wells were collected from Fars Water Resources Management Organization (Fars Water Organization Statistics, 1398). After collecting the required data, the conceptual model of the area was determined as a geometric form and based on the parameters that have the greatest impact on the aquifer. Then other characteristics of the aquifer such as permeable and non-permeable boundaries were determined using lithological properties parameters, geological characteristics and characteristics of boundary formations in the region as well as inlet and outlet flow to boundary cells in the range. And Natrova was prepared in the aquifer and by preparing intermediate maps, the amount of groundwater reduction in different parts of the zoning basin and the extent of expansion of critical areas were determined.Madflow is a physical, three-dimensional model capable of stable and unstable simulations of free-pressed and free-pressed aquifers. The Madflu model solves the equation governing groundwater flow based on the finite difference method. In this regard, Marvdasht aquifer is networked into smaller cells, assuming that the characteristics of the aquifer are uniform in each cell. According to the law of mass conservation and groundwater movement, the equation governing groundwater flow is obtained as a second-order partial differential equation. This equation is given as (Equation 1) in unstable, inhomogeneous and three-dimensional conditions.T_XX (∂^2 h)/(∂ x^2 )+T_YY (∂^2 h)/(∂y^2 ) +T_zz (∂^2 h)/(∂z^2 )=S ∂h/∂t±R ( x,y,z) In this equation, ℎ: height of the hydraulic load; ((𝑥, 𝑦, 𝑧: flow directions; 𝑡: time; [𝑇]: 𝑇𝑧𝑧, 𝑇𝑦𝑦, 𝑇𝑥𝑥; aquifer transfer coefficients in the directions (x, y, z);: S storage coefficient; 𝑅 (𝑥, 𝑦, 𝑧): Power supply (positive sign (or discharge) is a negative signDue to the fact that abstraction of groundwater by agricultural wells is one of the important causes of water reduction in the troubled basin. In order to explain the trend of groundwater level changes, the general trend of the annual water level of all observation wells (25 piezometers) in the period 1398-1387 was studied.The results of simulation of groundwater level reduction in Parishan basin showed that this model with high spatial variability power well determines the effect of different parameters on groundwater level in different parts of the aquifer. In the study area, 960 wells and 25 piezometric wells with different uses of agriculture, drinking and industry have been located, which are scattered in other places except in the southern parts of the plain. The concentration of these wells in the central areas is higher due to flat ground and in the northern areas due to higher groundwater levels.In this research, the sensitivity analysis method combined with the calibration step has been used. The results of sensitivity analysis of effective parameters in calibration of Parishan Basin aquifer showed the maximum effect of hydraulic conductivity parameters and horizontal hydraulic conductivity anisotropy and a set of linear groups of waterways. Hydraulic conductivity of the aquifer is one of the parameters that has a high uncertainty in this model and by changing the values of this parameter, the model shows great sensitivity. Therefore, the reason for the high sensitivity of the aquifer hydraulic conductivity is the existence of wells with high discharge in these areas, so it is consistent with the statistics received from the Fars Regional Water Organization. Also, the anisotherapy parameter has a significant sensitivity in this model.In order to check the accuracy of the model after the calibration step in the unstable state, it is necessary to refer to the mean errors calculated by the software. According to what has been said before, RMSE error is one of the best criteria for measuring the error rate. The following is a table of average error types calculated by the software and a series of related calculations.The results of calculating the water balance in the aquifer of Parishan Basin, which was done during the period (1387-1388) indicate that the amount of 42.4 million cubic meters of water has been reduced from the constant storage of the aquifer. As a result, the amount of water entering the area, in addition to dependence on the physical conditions of the disturbed basin, such as hydrodynamic coefficients and gravity, is directly dependent on the amount of pumping discharge wells. Therefore, by increasing the abstraction from the aquifer, a change in the amount of exchange volume of the effective parameters in the balance can be expected.