فصلنامه پژوهش های ژئومورفولوژی کمی
سال دوازدهم شماره 4 (پیاپی 48، بهار 1403)

The wind erosion and the resulted landforms are the dominant landscape in flat and deep plains of Iran dry areas (Yamani, 2015). The importance of wind erosion in the deserts differs due to great variances in wind power (Goudie, 2013). This type of erosion which is controlled by the erosivity power of wind and the erodibility of impacted surfaces (sharma, 2010), is dangerous for three reasons: 1, the nutritious elements of the soil are destroyed and as a result the soil loses its power for keeping a conservative vegetation layer (Thomas, 2011). The deposition of eroded sediments can bury vegetation and river channels, pollute food and water reserves and also negatively impact the growth of vegetation, soil fertility, and the dynamics of ecosystem (Larney, 1998y; Worster, 2004; McTainsh & Strong, 2007 ). The transportation of eroded sediments through powerful winds can bring damage to buildings and products and also trouble visibility in roads and airports (Thomas, 2011).

In first step, the impacted area of fault spring in Daranjir playa are identified based on satellite images, Geology maps and field observations. In the next step, 100 milliliter of water was sampled for chemistry analysis from active spring across Bafgh – Poshte-badam fault (Kor spring). Thus, to determine the water table, chemistry analysis of the sediment and water samples across Bafgh – Poshte-badam fault, 4 points were selected for drilling and the locations of bores were determined by GPS. To this end, the sampling procedure across the fault was conducted by a hand auger with the length of 20 cm and diameter of 7.5 cm. In sum, four water samples and 22 sediment samples were collected. In the geomorphology laboratory, initially the amounts of TDS, EC, and pH in the sample waters were measured by a multi parameter device, version HI9811-5. To measure the amounts of TDS, EC and pH in sand samples, saturated paste method was utilized. Here, the samples were initially dried in a drying device, and then 50 grams of each sample was measured with an accurate scale and mixed with 50 millimeters of distilled water. In the following step, the distilled water was mixed with sediment samples and the amounts of EC and TDS was measured using the multi parameter device and other devices.

The results suggest that the active tectonic performance across Bafgh-Posht badam fault not only result in the emergence of springs across the fault but also lead to the reduction of groundwater and the creation of a wet zone across the fault in Daranjir playa due to the penetration of water to the aquifer. This wet zone across the studied fault caused a significant growth of shrubs and Tamarix mascatensis, and reduced the speed of wind in the examined area. Regarding this Pye & Tsoar and state that in desert areas the salinity degree of groundwater has an important role in the transformation and distribution of deserts’ vegetation. The analyses of the qualitative and quantitative characteristics of groundwater across Bafgh- Posht badam fault show that the minimum water table, TDS and EC across the fault are ,respectively. In fact, by injecting fresh water across the fault, the fault springs not only reduce the salinity of groundwater but also raise the the water table across the mentioned fault and bring the transportation of the sediments to a minimum level. As for this case, Silva et al., (2018) state that in areas with high water tables, the sand sources are limited and consequently the transportation of sediments reduces. Moreover, Kocurek & Nielson concluded that high water tables can reduce the transportable sediment by conserving surface moisture. In addition to the formation of vegetation, the increase of water level across the fault, the creation and change of Nebkha formation location are the main effects of spring faults which have a crucial role in controlling wind sediments. As a matter of fact, the fresh water of springs results in the formation of vegetation and this vegetation captures wind sediments and forms Nebkhas.

The results of this study show the strike-slip movement of Bafgh – Poshte-badam fault and the emergence of fault springs have a key role in controlling wind erosion and formation of eaolian landforms in Dar-Anjir playa. Indeed, the fault springs control the wind erosion in the present case study in three ways: 1: the formation of wet zone creates various types of vegetation and reduces wind speed in surface, 2: the raising of water table across Bafgh – Poshte-badam fault and the increase of the moisture surface impede the movement of sediment by wind and 3: With formation of nebkhas causes the aeoilan sediment accumulation around Shrubs.

Sediment that consists of solid particles with organic matter transported by water is called suspended sediment. In other words, the sediment load is the flow of the total sediment output from the catchment or drainage basin that can be measured in the desired cross-section and in a certain period of time. In most natural rivers, most of the sediments are transported as suspended load. The sediments collected by the rivers cause many problems, including sedimentation in the reservoirs of dams and reducing their useful volume, changing the course of the river due to sedimentation in their bed, reducing the capacity of canals and water transfer facilities, and changing the quality of water in terms of drinking and agriculture. . However, no direct or indirect experimental model developed to evaluate this process has been universally accepted. Therefore, sediment transport has been considered by engineers from different aspects and different methods have been used to estimate it. One of the methods of estimating suspended sediment is artificial neural network. Artificial neural network is a computing mechanism that is able to provide a series of new information by taking information and calculating it. Considering that the structure of the human brain has a very high ability to process complex, non-linear and parallel information.

As one of the sub-basins of the Aras catchment basin, Gharasu catchment is located in the geographical coordinates of 47°31' to 48°47' east longitude and 37°47' to 38°52' north latitude.In this study, the statistics and information of 17 variables in 13 sub-basins of the Gharasu River, which were extracted by the regional water organization of Ardabil province, were obtained from this organization. In order to model the artificial neural network from the data of 3834 daily sediments recorded in 13 sediment measuring stations in the studied sub-basins during a 50-year statistical period corresponding to the statistical period of 1350 to 1399 and also from the digital topographic maps of the 1:25000 scale of the Geographical Organization of the Armed Forces to Validation of basin demarcation was used. In choosing this common time base, criteria of completeness, sufficient length of data and use of the latest available data were taken into consideration. Then the normality and correlation between the obtained data were evaluated and two methods of Radius Axis Function (RBF) and Multilayer Perceptron (MLP) were used in SPSS software to model the artificial neural network.

recorded suspended sediment (3834 cases) in the relevant statistical period was considered as a dependent variable and flow rate as an independent variable separately for each sub-basin, and Pearson's correlation method was used to check the correlation between the independent variable and the dependent variable.According to the correlation matrix of the variables, it can be seen that Barouk sub-basin has the highest correlation and Arrab Kendi and Pol Almas sub-basins have the lowest correlation. After modeling the data by two artificial neural network models (RBF and MLP), the amount of sediment for each year was predicted by these models and R2 and RMSE values were also calculated for them. In order to determine the number of neurons in the hidden layer, the values of the neurons in this layer were evaluated by trial and error, and according to the results, choosing the number of 4 neurons for the RBF model and 3 neurons for the MLP model has the highest prediction accuracy in the evaluation data and It also shows in the test data. The accuracy of prediction in RBF model with correlation coefficient R2=0.941 and RMSE=65.002 is compared to MLP model with R2=0.917 and RMSE=88.244.Based on the scatter diagram between the real data and the estimated data, it was determined that the average of the real values is 4.636, which is 4.367 for the RBF model and 3.534 for the LMP model, which indicates better accuracy in Modeling and the closeness of the RBF model value to the real value. Regarding the median index and the mode index, which represent the most repeated data in the statistical collection, for the real values, the numbers are 4.117 and 3.246, respectively, and for the RBF model, the numbers are 4.425 and 4.213, respectively, which are the closest values. It is considered as a real amount.

So far, various forecasting models have been used to estimate river sedimentation. Some of these models have estimated the amount of sediment by combining different physical parameters of the basin, climate and even the output of satellite images. Artificial neural network models are widely used in forecasting geographic models today.In this research, two artificial neural network models, radial axis function (RBF) and multi-layer perceptron (MLP) in SPSS software have been used to estimate the sediment of Gharasu River in Ardabil province. In this study, recorded suspended sediment (3834 cases) in a 50-year statistical period was considered as a dependent variable and flow rate as an independent variable separately for each sub-basin, and Pearson's correlation method was used to check the correlation between the independent variable and the dependent variable. It was found that Barouk sub-basin had the highest correlation and Arbab Kendi and Pol Almas sub-basins had the lowest correlation. After modeling the data by artificial neural network model, the amount of sediment for each year was predicted by these models and R2 and RMSE values were also calculated for them. The prediction accuracy of RBF model with correlation coefficient R2=0.941 and RMSE=65.002 is higher than MLP model with R2=0.917 and RMSE=88.244, and it has a better performance in estimating suspended sediment in the study basin.Also, the average value of the real values is equal to 4.636, which is equal to 4.367 for the RBF model. This research showed that in all studied stations, the RBF method provides more accurate estimates of suspended sediment than the MLP model. Of course, due to the existence of complex relationships between flow rate and suspended sediment, the appropriate model should be determined in each hydrometric station to estimate this variable more accurately,

Various forms of geomorphology in the region are a reflection of the rate of tectonic activities in that region. Folded Zagros structural unit is one of the active tectonic areas of Iran, where evidence of tectonic uplift can be seen in its growing anticline (Ansari Lari et al., 2019).Geomorphic indicators are a useful and reliable tool in evaluating these activities. The change in the axis of the folds causes a change in the shape of the drainage basins. Quantitative measurements of the watersheds and drainage network of the region make it possible to study the role of active tectonics in changing the shape of the landscape and geomorphological effects of the region by measuring geomorphological indicators. Many geomorphological indices.In the current research, the watersheds and drainage networks of anticlines in the southwest of Ilam have been studied. The purpose of this research is to evaluate the morphometry of the drainage networks of this region based on geomorphic indicators and its relationship with the tectonics of the region.

In this research, first, scientific sources have been collected through library research. Research data includes DEM 30 meters STRM, topography map 1:50000, geological maps 1:100000, 1:250000 and Google Earth images. In order to evaluate the indicators and also prepare the final output map of the software Zmap, Arc Hydroo, SPSS, Arc Gis and of the indices ∆a, Ha, Dd, R, Bs Hi, Hs, AD, AR, FSI are used in order to investigate the tectonic relationship. The results of the indicators were analyzed using Pearson correlation coefficient and the seismic data obtained from the ZMAP software were extracted and the seismic status of the basins was evaluated.And finally, the final result of the tectonic activity status of each of the sub-basins has been determined.

In this research, basins with parallel pattern and scaffolding have the highest increase in indicators R,RB,Hi,a,LN1 and have tectonic activity. The drainage pattern in most of the tectonically active areas is scaffold and parallel pattern(often on the side of anticline) and in some cases a branch pattern is seen in comb or eroded anticlines. According to the type of formations in the region, the waterways in Siah Kouh East and Samour flow in the direction perpendicular to the anticline axis. The difference in the results of morphometric indices is related to the type of formations in the region. Among the anticlines , the highest value of Δa is related to the black anticline of the to anticline Siah Kouh east (6.5), in anticline of Samour-Siyah Kouh East, the highest index LN1. The highest value is related to (Sieh Kouh East and Samour) with numerical values of 3.28 and 3.26 and In the Bifurcation index (R), the highest value is in anticline, Samour 23(0.34), 37(0.69) and The Siyah Kouh East (0.39) and the Siyah Kouh western is obtained (0.43) and in the hypsometric integral index (Hi).The highest Hi related to basin 32, 39 with a value of 0.67, 0.68 and basin 33 with a value of 0.56 (Siyah Kouh East). In the examination of HS, AR, FSI, Ad indices and seismic data of the regionAccording to the changes in the geometry of the folds in the region, the highest amount of tectonic activity in anticline, in order of age. In the Siyah Kouh East, the Siyah Kouh western, Samour and Gnu can be seen. in relational investigation between geomorphic indicators using Pearson's correlation coefficient between Dd-Dd1 indicators There is a strong positive correlation and On the other hand, there is a strong negative correlation between the pair of Dd-Hi indices

The present research shows that the use of indicators to determine tectonic activity together with other sources provide valuable information about regional developments and the drainage network are among the most important features that have been used in this study., Changes in the geometry of folds in the region in some parts of the region have caused significant differences in the pattern of the drainage network and the anomaly of waterways. The indices (AD, AR, Hs, Fsi), It indicates the most tectonic activity in the eastern Siah kouh, according to the age of folding and the amount of erosion, the ratio of the direction of folding, the distance between the axes of the anticlines and the inequality in the two edges of the anticlines. The differences in the type of indicators are somewhat dependent on the type of regional formations and the type of faults and changes in the geometry of fold.In examining the statistical compatibility between the studied indicators, this point is also determined that the differences in the formations of the region have the greatest impact on the variables. In the calculation and analysis of the seismic parameter are observed. The highest frequency of indices ∆a, Af, Df, Dd, FLi.Hi and branch drainage pattern according to the type of formation is obtained in the eastern and southeastern parts, away from the ZFF fault and close to the MFF fault. and in the western and northwestern parts of the region, the indices of ∆a, R, RB have the highest frequency ratio and the highest a-value parameter and other geomorphological evidences according to the type of formation of the region and lithology and the pattern of parallel drainage and scaffolding. In general, the most active basins in the region are basins 42 (east), 31 (south), 11, 18 (center) and 2 in the west of the region, and among the taqdis, Siah Kouh Sharq and Samourmi, and the highest ratio of abundance in Dd, R, RB, LNI, ∆a, Bs, indicators has been obtained in these basins from the point of view of geology. The ratio of the pattern of waterways network is also changed from branch to scaffolding and parallel according to these activities. there is a connection between flowing waters with different patterns and the way of formation of waterways with different ranks and branches and tectonic activity andForms of erosio and they can be reasons for hydrocarbon traps or water sources.

Soil is one of the most vital issues for the sustainability of the environment, which provides human needs and livelihood on the surface of the earth. Therefore, reducing the phenomenon of land degradation is one of the leading challenges for the sustainable development of the environment and economic activities, which is why comprehensive planning and management against erosion is essential. Today, several methods have been developed for preparing soil erosion maps, which can be mentioned using experimental methods; that these methods include equal weights for all parameters in calculating the average erosion; While each criterion has a point value that is affected by environmental, geomorphological and physical factors related to soil erosion. Among other methods, we can mention machine learning, which is an advanced method that requires high-performance computing systems. However, it is necessary to use statistical methods for fast, understandable and accurate modeling, and there is no requirement for high-performance systems in these methods and Among these methods, Entropy Index, Frequency Ratio, Information Value, Certainty Factor, and Witness Weight methods can be mentioned. Therefore, the aim of the current research is to identify the most important criteria and sub-criteria that are effective in preparing the erosion sensitivity map of the watershed upstream of the Tajen River using the Integration of two data mining models Entropy - Information Value.

The erosion inventory map with 252 erosion points for the upper watershed of Tejn River was identified using Google Earth images, and 70% of these erosion points were classified for training and validation of the model. Then, to evaluate the sensitivity of erosion and also to identify the most important driving factors in the occurrence of erosion, the criteria of elevation, slope direction, soil type, land use, Rainfall Erosivity, distance to stream and Topographic Wetness Index were used and The erosion sensitivity map of the studied area was obtained from the integrated entropy-information value model. In order to evaluate the success rate and predict the model, Receiver Operating Characteristics and Area Under the Curve were used.

The results of the present study showed that the effect of elevation on soil erosion is increasing, so that this effect reaches its maximum value in the elevation class of 2745-3742 meters with an Information Value of 1.65. The influence of the slope directions on soil erosion showed that the south-west slope direction with an Information Value of 1.04 has the greatest effect on the erosion of the region. The results of overlapping the distance to stream layer with the erosion map of the region indicate that the distance layer of 0-456 meters has the highest Information Value of 0.63. The barren land use class with an Information Value of 2.74 has the greatest effect on the erosion potential of the region. The results of the overlap between the Rainfall Erosivity map and the regional erosion map showed that the 302-325 layer of rain erosion has the highest Information Value of 1.28. Examining the relationship between types of soil groups with regional erosion showed that the Inceptisols soil group with an Information Value of 0.66 has the greatest effect on soil erosion in the region. The results of the overlap between the Topographic Wetness Index layer and soil erosion in the region indicated that the 6.2-8.6 layer of the Topographic Wetness Index with an information value of 0.25 has the highest erosion potential. According to the curve (ROC-AUC), the success and prediction rate of the combined model of Entropy Index - Information Value was obtained as 0.831 and 0.837, respectively which indicates the good performance of the model for training and validation courses.

Soil erosion is one of the most important issues of land destruction on a global scale, which causes muddying of waters and lakes, loss of fertile agricultural topsoil and biodiversity; Therefore, it is essential to evaluate the sensitivity of soil erosion. The current research was conducted with the aim of identifying the most important criteria and sub-criteria effective in soil erosion with the integrated model of Entropy - Information Value in the upper watershed of Tajen River. The results of the present study showed that out of the total area of 693.23 square kilometers of the study area, 156.75 and 94.71 square kilometers are in the high and very high categories, respectively. The prepared soil erosion sensitivity map in the studied area can be a useful tool for management and planning in line with soil protection measures.

Today, the study of Mud Volcano as one of the unknown and unique effects of the earth has been the focus of various experts in different sciences. West Drabul Mud Volcano is located in the east of Rimdan village and 5 km northwest of the Drabul Mountains, the common border between Iran and Pakistan, and East Drabul Mud Volcano is located exactly one km east of West Drabul Mud Volcano. In the first step, by being in the area, direct field studies were conducted and all the geomorphological parameters of Mud Volcano were recorded and mud and water samples were sent to the laboratory for chemical analysis and XRD and XRF analysis. The results of this research show that the western Drabul Mud Volcano has become higher due to the outflow of mud flows with a higher concentration and less viscosity and has a greater slope in the slopes, but the eastern Drabul Mud Volcano has a higher height due to the thinner outflows. Less and the diameter of the base, the area and circumference are more. Also, the presence of shells, bivalves and gastropods in the Mud Volcano indicates the low depth of both Mud Volcano. In the results obtained from the chemical analysis by XRD method, both Lavas have the main phase including quartz, chamosite, illite and albite and the secondary phase including calcite. In chemical analysis by XRF method, the elements (Sio2) silicon dioxide or quartz, (Al2o3) aluminum oxide, (Na2o) sodium dioxide, (Mgo) magnesium oxide, (K2o) potassium dioxide, (Tio2) titanium dioxide, ( Mno) Manganese oxide or mangensite, (Cao) Calcium oxide, (P2o5) Phosphorus dioxide, (Fe2o3) Hematite, (So3) Sulfur trioxide and (LOI) There are organic substances that differ in their amount slightly.

The most important part of this study is related to the field survey of the mud volcano, which at the time of the field visit, the West Drabul mud volcano was inactive and the East Drabol mud volcano was active. In the first step, the location of the mud volcanoes was recorded with the Global Positioning System (GPS), the ambient temperature was measured with a thermometer, and then all its geomorphic and morphometric parameters were measured. In the next step, mud and water samples were collected from mud volcano. For the purpose of mineralogical and geochemical investigations, several samples were taken from the periphery and central parts and from different depths of about 15 to 20 cm. The collected samples were stored in special storage containers and then sent to the laboratory to perform XRD and XRF chemical analysis tests and determine its mineral composition. The results were prepared and used in the form of tables, maps and charts.

West Drabul mud volcano is located at 25 degrees 20 minutes and 4.32 seconds north latitude and 61 degrees 35 minutes and 39.5 seconds east longitude. Its height above the sea level is about 21 meters and its height above the level of the region is 17 meters, which is the highest mud volcano located in the Dashtiari plan. This mud volcano has a main cone and a main opening with a diameter of one meter, which has a cone on top of the main mud volcano and at the top of the mud volcano and does not have a secondary mud volcano. The area occupied by West Drabul mud volcano is about 5214.16 square meters. Also, the circumference of this mud volcano is about 255.91 meters.The main mud volcano cone of Eastern Drabul is located at a height of 10 meters above sea level and 6 meters above the level of the region. The secondary crater, which was active at the time of the visit, was 6 meters above sea level and 1 meter above the regional level. This mud volcano has 2 main cones and 6 secondary cones. Also, its main openings are 2 and its secondary openings are 6. The main openings with a diameter of 1.5 meters and the secondary openings with a diameter of 40 to 80 cm were measured and recorded. The depth of the main craters was not clear, but the depth of the secondary craters is about 40 cm.

Comparison and investigation of all geomorphological parameters and the results obtained from geochemical tests determine the differences and similarities in the compositions of the studied mud volcanoes eruptions. In terms of shape, the Western Drabul mud volcano is a complete and inactive cone, and the Eastern Drabul is a double-opened cone and is active. The results obtained from the height, slope of the slopes of the four directions, the radius of the mud flow, the diameter of the base, the circumference and the area show a higher concentration and a lower viscosity of the materials of the West Drabol effusive mud. Also, the spreading radius of the mud flows, the diameter and the larger area of the Eastern Drabul flower show that its activity is more continuous and as a result, the diameter of the base, its area and its circumference will also increase. The results of the XRD test showed the elements of the West Drabul mud volcano in two main phases including quartz, chamosite, illite, albite and a secondary phase including calcite, and in the Eastern Drabol mud volcano, the main phase included quartz, chamosite, illite, albite and a secondary phase including calcite. has categorized There are identical and completely similar elements in both East Drabul and West Drabul mud volcano, both in chemical analysis by XRD and XRF methods, with the difference that their amounts are slightly different from each other, which is not significant.

Floods are the most important and abundant environmental hazards that cause yearly human and financial losses. Aji Chai basin, located in East Azerbaijan province, is prone to destructive floods due to special topographical conditions. The primary purpose of this study is to prepare a flood hazard potential map using the weight of evidence (WOE) statistical method. To achieve this aim, 18 parameters effective in flood occurrence were investigated. The investigated parameters were Elevation, Slope, Aspect, Topographic wetness index, Sediment transport index, Stream power index, earth curvature, Rainfall, Normalized Difference Vegetation Index, land use, Distance to dam, Distance to bridge, Distance to the river, River density, hydrological soil groups, Drainage texture, Geomorphology and lithology.

Aji Chai basin is located at latitudes between 37° 41΄ and 38° 29΄ North, and at longitudes between 45° 48΄ and 47° 53΄ East. The study area, with an area of about 10985.9 Km2, is one of the largest sub-basins of the Urmia Lake basin. The most important river that drains the surface water of this basin is Aji Chai.This study used the weight of evidence (WOE) statistical method to prepare a flood hazard map in the Aji Chai basin. The weight of evidence model is one of the bivariate statistical methods. In this method, the weight of each parameter class is calculated based on the presence or absence of flood in the desired class. The weighting of the classes was done using the location of the floods that occurred in the area. From 274 flood points, 70% were selected as training data and 30% as validation data.

The weighting results of different classes for each layer show that the 0-10% class has the highest weight in relation to the slope layer. Due to having more humidity, the northern slopes have the highest weight in terms of flood potential. About the parameter of distance to the river, as expected, the areas around the rivers have experienced many times more floods than other parts. Therefore, the 0-250 meter class had the most weight. In the investigation of the river density parameter, it was found that the areas with the highest drainage density are the most susceptible to floods. The weight calculation results for the classes of land use layer showed that the classes of agriculture, garden, and built areas have the most weight in the occurrence of floods in the area. Concerning the parameter of distance to the bridge, the areas around the bridges have a high potential for flooding due to human manipulations. Investigating the topographic wetness index layer showed that the areas with higher values of this index have a high potential for flooding.

The final map was obtained using the Raster Calculator tool and the product of the weight of the parameter classes in its information layers. The analysis of the final map showed that the downstream areas of the basin have a high potential for flooding. These parts mainly include low, flat, and low-sloping surfaces, which are the places where all the runoff formed in the region's highlands is accumulated. Therefore, these areas are constantly flooded with heavy rains and sudden melting of snow in the region's highlands. The important cities of the basin, such as Tabriz, Sarab, and Bostanabad, which are formed along the main rivers, are also located in high-risk areas, which shows the vulnerability of these cities when flooding occurs. The calculation of the area of each hazard class showed that 32% of the area is in high and very high classes in terms of flooding. The evaluation of the model's accuracy based on the ROC curve and the area under the curve (AUC) showed that the model's accuracy had an excellent performance in training data with a coefficient of 0.898.

Gilan province is one of the most populous regions of the country, with a population of 2,530,696, making it the twelfth most populous province of Iran. These areas have become unstable due to factors such as the increase in immigration and the lack of recognition of the effective landforms in the quality and quantity of groundwater, especially in coastal areas, and require proper management and potential. Alluvial fans are an important landform in the plains that start from the mouths of the rivers coming out of the mountains and continue to the lowlands of the plains. In the present research, after identifying the boundaries of alluvial fans in the low-altitude eastern and central plains of Gilan province, the morphometric characteristics of each alluvial cone were calculated independently and quantitative analyzes of the geomorphic features of alluvial fans were provided. Therefore, in this article, we have tried to identify the boundary of the morphometric changes of alluvial fans according to statistical classification, and determine the ratio of changes in underground water parameters, so that the results of this research will help to identify underground water sources according to the morphometric characteristics of alluvial fans. Also, the results of this study show that geomorphic studies before carrying out implementation plans can be the basis for reducing errors in determining the right place to feed an aquifer or dig an underground water well.

The alluvial fans in the east and center of Gilan province are located in the geographical range of 40.50° to 49.00° east longitude and 30.36° to 25.37° north latitude (Figure 1) and are influenced by the Anzali and Darya lagoon catchments. These areas, with an area of 3820 square kilometers, start from the west of the city of Masal and continue to the city of Chabaksar (originally the political border of Mazandaran province) in the east.In this research, first, information on the depth of water table, standard deviation of time changes of water level, well discharge and electrical conductivity of 23559 rings of drinking, agricultural and urban wells were obtained from Iran Water Resources Organization. Also, the border of 28 alluvial cones was drawn using Landsat 8 satellite images, Sentinel 2 satellite and 1:50000 topographic maps in Arc Gis software. The parameters used and how to calculate them in this study for alluvial fans are: area of alluvial cone in kilometers, radius of the cone, sweep angle, height of the top of alluvial cone, height of the base of alluvial cone, degree of roughness of the cone, length of the cone, slope of the alluvial cone, concavity of the cone Alluvium, the length of the base of the cone, the volume of the alluvial coneAfter extracting morphometric data and groundwater data for each alluvial cone, statistical methods and tests were used to make decisions about the impact of morphometry on groundwater parameters. For this purpose, SPSS version 23 software was used to classify the morphometrics of alluvial fans using cluster rank-order cluster analysis and its tree diagram was drawn. In the current cluster analysis, Euclidean geometry was used to determine the distance of members from each other.
Then, each separated cluster was evaluated separately by Pearson's correlation test, and the correlation of the morphometric parameters of each cluster with the changes in the groundwater parameters of that cluster was measured. In the end, RFFLOW software was used to draw the model of the influence of geomorphic parameters.

Due to the fact that the flow rate of the wells in the alluvial cone largely indicates the stable or unstable potential of underground water in the direction of exploiting these resources. Therefore, the results of the correlation test of flow rate with alluvial cone morphometry show that the area, length and total volume of alluvial cone in the study area have a positive correlation of 99% with the groundwater discharge of the area. In fact, with the increase in the area, length and volume of alluvial cones, the amount of water that can be extracted from the wells increases. This point has a positive and strong correlation of 99% with the height of the top and base of the cones, which indicates that in alluvial cones whose morphometry is higher than others, the amount of groundwater flow is also at that time. Alluvial cones are more. The slope of the alluvial cone, as an important factor in the duration and degree of water infiltration in the soil, has a negative and strong correlation of 99% with the flow rate, which indicates that by reducing the slope, the water flow rate has been reduced to a minimum. underground increases.

The results showed that the changes in discharge, electrical conductivity and depth of the sedimentation surface from the total of 11 morphometric parameters of the alluvial cone are affected by the morphometric characteristics with the amount of 82%, 45% and 45% respectively. are considered important for identifying and zoning the appropriate potential of underground water on a larger and local scale. Based on this, the highest amount of discharge can be observed in the alluvial cone of the third cluster. The reason for this issue is the direct relationship between the volume and area of the cone with the changes in the underground water flow. Also, in the third cluster, with the increase in the area of the cone from the average (19.3 km) to the maximum area (71.3), the flow rate of the wells also increases. The depth of the water table is also not significant because of the same conditions in the entire region and the water table depth of all three clusters is close to the total average .In general, the results of this research showed that geomorphological landforms and the difference in their morphometric characteristics can be used as an important indicator in evaluating the potential of underground water and can be used as a model in the studies of underground water in areas with the climatic characteristics of the studied region.

Almost most of the installations located in natural beds face many threats over time, and in order to reduce the damage, it is necessary to identify the threatening factors and use the results in the appropriate location or in taking measures to reduce the damage. Today, the increase in consumption Gas has caused an increase in the density of the gas transmission pipeline network and, as a result, an increase in its potential risks. The first step in risk analysis is to identify the effective factors in the occurrence of accidents and breakdowns on the pipeline. According to the environment around the pipeline, various factors cause pipeline damage and accidents. After identifying the damage factors, the amount of damage caused by each is calculated and the results are expressed in the form of risk. It is possible to establish a connection between the risk estimation process and the geographic information system and make appropriate zoning. It was determined by using models and geographic information system. Therefore, in this research, the process of estimating environmental risk with geographic information system and using hybrid-fuzzy algorithms has been investigated. Valuable information such as risky components can be determined by assessing the risk of gas pipelines, and a suitable response and strategy can be used to reduce or even eliminate it. In order to achieve this goal, it is necessary to use a suitable technique that can accurately and reliably assess the existing risks, so that planners and managers can act with a wider horizon and a lower risk factor towards the optimal management of gas transmission lines. The extent of gas lines in Tehran and Qom province and considering the environmental and natural characteristics of the two provinces, it is very important to assess the amount of damage. In this research, MATLAB version 2019b software was used in order to assess the risk of the gas pipeline using the multi-layer perceptron neural network model. Due to the fact that the number of input nodes and hidden layers are varied in the specified range, the optimal number of input nodes and hidden layers was determined by model selection criteria on the test data and the WIC model was used. Due to the existence of 11 criteria in this research, 11*11 modes were created. Also, in this research, the input layer has 6 neurons and 1 neuron in the hidden layer and the algorithm used is Levenberg- Morquardt according to the purpose of the research and high accuracy. In this model, there were 740 data, 70% of which were used for training, 15% for testing, and 15% for evaluation. For risk assessment, criteria were weighted by VIA method. In this method, using the feature eliminate process, a criterion was removed in each step and the network error was measured. In this research, in addition to the MLP model, the Random Forest model was used. In this method, an estimate of the classification error can be obtained based on the training data. The number of trees should be enough to stabilize the error rate and the additional index that is created in the RF method. To estimate the feature importance, first the OOB components are run among the trees and the votes are counted for correct classification. Then, the prediction accuracy is obtained many times after randomly changing all the values of this feature while all other features are the same. In order to assess the risk of the gas pipeline using the random forest model from MATLAB version 2019b software and from the model Regression and RF Regression function were used. In this model, the selection of training and test data is random and 740 points are samples, 80% of which include training data and 20% of test data. In this model, the number of decision trees used by the tree bagger function is 500. To check the validity of the models, the estimated values obtained from the networks and the measured values in the test phase were used. To validate the model, the root mean square error (RMSE), mean error of exploitation (MBE), and mean absolute error (MAE) were used.According to the results of ANP landslide index, 0% of the area is in the low risk class, 17.28% in the medium risk class, 73.14% in the high risk class, and 9.58% in the high risk class. Therefore, it can be said that 19.008 km of the investigated area are located in parts with moderate vulnerability, 80.454 km with relatively high vulnerability and 10.538 km with high vulnerability. According to the results of the Fuzzy model landslide index, 41.85% of the area is in the low risk class, 11.60% in the medium risk class, 22.52% in the high risk class, and 24.03% in the high risk class. Based on the landslide criterion and the results of the fuzzy model, it can be said that 46.035 km with low vulnerability, 12.76 km with moderate vulnerability, 24.772 km with relatively high vulnerability and 26.433 km with vulnerability. In this research, the systematic error (MBE) of the MLP model is estimated to be 0.002812, and the absolute error of the model is 0.042168. The RMSE error rate is 0.05020. The systematic error (MBE) of the RF model is -0.151848. The absolute error of the model is 0.179101. The systematic error (MBE) of Fuzzy_ANP model is -0.16893. The absolute error of the model is 0.170337. The RMSE error was 0.12262.

Soil erosion in Iran is one of the most important problems of drainage basins that can be mentioned as main barriers to the sustainable development of agriculture, geoscience, and natural resources. Therefore, soil erosion control is one of the most urgent environmental issues which need to identify in erosion-prone areas in the watersheds. In many watersheds, the role of land use in soil erosion is greater than of other factors. Knowing the contribution of different types of land use to soil erosion leads to managing land use and reducing the severity of soil erosion, and even increasing the income of the watershed stakeholders. Evaluation and identification of soil erosion in coastal regions are one of the most important measures for comprehensive coastal management. Therefore, the current research was carried out with the aim of estimating soil erosion in different temporal and spatial scales with the G2 model, according to the land use/land covers of the Caspian Sea basin.

The northern region of Iran encompasses the Caspian Sea basin, which spans approximately 91,176 km2, equivalent to around 10% of the country’s total area. It is situated between latitudes 45°39'-35'N and longitudes 59°59'-44'E. With an average elevation of 1,195 m, the watershed exhibits significant variation, ranging from the highest point at Mount Damavand with an elevation of 5,699 m to the lowest point along the Caspian Sea coast at -28 m. The Caspian Sea basin is divided into seven primary basins and further subdivided into 108 sub-basins using the Strahler stream ordering method. In order to prepare soil erosion map in the study area, the input factors of G2 model were prepared in appropriate spatial and temporal scales using meteorological data, satellite images, application of GIS and RS. The G2 model combines five input erosion parameters in a multiplicative equation to produce month-time step maps and statistics of soil erosion. Ideally, a single layer suffices for S, T, and L factors, while a collection of 12 layers (one for each month) is required for the dynamic factors R and V. Also, the values of soil erosion were estimated for different types of land uses/covers in different time scales for the Caspian Sea basin.

The results showed that the average annual soil erosion for the study area is reported to be 11.24 t ha-1, the highest soil erosion rates observed in the West Azarbaijan, Mazandaran, North Khorasan, and East Azarbaijan provinces. On the other hand, the highest monthly soil erosion with the rates of 1.49, 1.48, 1.32, and 1.27 t ha-l were in November, October, April and May, and the lowest monthly soil erosion with the rates of 0.54 and 0.59 t ha-1 were in August and December, respectively. The highest amount of soil erosion occurred in autumn and spring compared to winter and summer. One of the reasons for the increase in soil erosion in the autumn season is the high intensity of rainstorms that occur in lands with little vegetation and in the spring season, may be due to the increase in rainfall and snow melting in this season and its effect on the increase of soil erodibility. Also, minimal soil erosion in summer and winter seasons can be caused by the decrease in the amount and intensity of rainfall or the absence of effective rainfall. In addition, it was found that with the increase of rainfall erosivity, soil erosion increased on a monthly time scale. The highest annual soil erosion with the rates of 16.87, 15.96, 11.51, and 11.22 t ha-1 were in rangeland, shrubland, barren lands and forest II, respectively. As a result, annual soil erosion values in the western, central, and eastern parts were estimated equal to 11.94, 13.47, and 10.53 t ha-1, respectively. Although the difference of soil erosion in monthly, seasonal and annual time scales in all different land use/land covers is significant at the 99% level, but it is not significant in a number of large land use/land covers in the Caspian Sea basin in the western-central, central-eastern and western-eastern parts.

According to the current research, 40.53% of the lands in the studied area have soil erosion of less than 1 t ha-1 yr-1, which are in the range of low erosion, because this amount of wastage is almost equal to the annual soil construction limit and is normal, and these areas do not need watershed operations and the risk of soil erosion is low. While about 18.73% of the land surface of the studied area, soil erosion exceeds 20 t ha-1 yr-1, and it is recommended that in these areas, in addition to biological operations, mechanical operations are also performed to reduce and control soil erosion. The results obtained from the present research provide managers and policymakers with information and appropriate decision-making bases for the management and sustainable use of soil and water resources.

The landscape of the earth's surface as a complex system is the result of the interaction of factors such as geographical, climatic, temporal processes and human activities. The physical development of cities, without observing the principles of urban planning and taking into account the potential of their natural hazards, leads to the high vulnerability of cities. One of the most important dangers in the plains and plains of our country is the dangers caused by land subsidence, which for various reasons, such as over-harvesting of underground water resources and climate changes, causes many problems for agricultural lands, roads, and transmission lines. has become power and energy; Therefore, it is very necessary to investigate the causes and to control and reduce its risks (Abedini et al., 1402). Groundwater is one of the most important sources of water needed by the agricultural, drinking and industrial sectors, especially in the dry areas of the central plateau of Iran. Therefore, investigating the process of its qualitative changes is very important in the sustainable management of water resources (Arshad Hosseini et al., 1400). . Yilaghi city of Shandiz, which is a part of Targaba Shandiz city, is 1400 meters above sea level and is located at 59 degrees and 17 minutes of latitude and 36 degrees and 23 minutes of latitude. This city is adjacent to the central part of Mashhad from the north, Targaba city from the south, Neishabur from the east and Golbahar from the west, and has an area of about 37,825 square kilometers. Since Shandiz Mashhad is known as one of the holiday areas of Khorasan and is surrounded by thick and dense vegetation of towering sycamore trees and flowing rivers and tourist attractions (Karizno Aqueduct, Shandiz Historical Tower, Shandiz Padideh, Cozy Cottage Garden, Panjan Nama, Park It is mountainous and...), has a cool and summery climate and is one of the main centers of travelers and tourists in Mashhad and all over Iran. All over the south of this city are the heights of the Binalud mountain range of Khorasan, and Shirbad peak in the Zashk region of Shandiz is also considered the highest point of this mountain range and Khorasan province.

In order to investigate the subsidence rate of Shandiz city and its relationship with the drop in the underground water level, first the rate of land subsidence in the period of 2016-2023 was calculated annually by radar interferometric method and then the trend of changes in the water level of piezometric wells during 29 years was investigated. took Finally, the research results were verified by field surveys. In order to process by radar interferometric method, SNAP software was selected to obtain the final results of the subsidence rate based on the phase difference between the images taken on different dates. In order to study the latest status of the groundwater level in the study area, the statistical information of piezometric wells from 1370 to 1399 was obtained from Razavi Khorasan regional water, which was then prepared in the GIS software after annual averaging using the IDW interpolation model to prepare the groundwater level map. and was evaluated.

In the investigations carried out with SLC radar images of Sentil 1 satellite in relation to the city of Shandiz, 8 images were processed two by two in the Snap software, the image of the year 2016 with 2017, 2017 with 2018, 2018 with 2019, 2019 with 2020 and 2020-2021, 2021-2022 and 2022-2023 images were checked and the amount of subsidence recorded for each period was 2 cm for 2016-2017, 6 cm for 2017-2018, 2 cm for 2018-2019, 5 cm for 2019-2020, for The 2020-2021 period was about 2 cm, 4 cm for the 2021-2022 period and about 1 cm for the 2022-2023 period. In the survey of the water level of Shandiz city from 1370 to 1399, the number of 2 main wells, Hassan Abad and Qasim Abad, which are located in the northeast and east of the city at a distance from it, were obtained with the same data, which information was obtained from the Khorasan Razavi Regional Water Organization. and was investigated. The data were averaged every 5 years and its maps were prepared using the IDW tool in the GIS environment for the study area. In the east of the region, the villages of Hesarsokh and Sarassiab were located in the area of high risk. The minimum and maximum water level drop in the 30-year period from 1370 to 1399 was calculated as 57.86 and 76.84 meters.

The results of interferometric studies showed that the amount of subsidence during 5 statistical periods in the studied area was 22 cm. The amount of subsidence recorded for each period is 2 cm for 2016-2017, 6 cm for 2017-2018, 2 cm for 2018-2019, 5 cm for 2019-2020, and 2 cm for 2020-2021. 4 cm for the 2021-2022 period and about 1 cm for the 2022-2023 period. According to the obtained results, the highest amount of subsidence has happened in the east, north and south of Shandiz from east to west. The water levels of the wells have reached their maximum decrease in the period from 1370 to 1399. The water level drop in this time period is at least 57.86 meters and the maximum is 76.84 meters, and all areas of Shandiz city have water level drops and are at risk. The subsidence has also covered most of the city areas. Shandiz city is a tourist area and all its geosites (Carizno Aqueduct, Shandiz Historical Tower, Shandiz Phenomenon, Cozy Cottage Garden, Finjan Nama, Mountain Park, etc.) are vulnerable to damage, therefore it needs special attention.