فصلنامه پژوهش های ژئومورفولوژی کمی
سال دهم شماره 4 (پیاپی 40، بهار 1401)

Geodiversity can be defined as the natural diversity of geology (rocks, minerals, fossils), geomorphological (land form, physical processes), and soil properties. This combination includes sets, relationships, properties, interpretations, and internal systems. Geodiversity emphasizes biodiversity and provides the community with the benefits of regulating, supporting, providing cultural services and services, and with a set of actions to inform the management of geological sites, including inventory and assessment, conservation, legal protection, interpretation and monitoring of sites strives to preserve landscapes and the environment. Karaj Dam Basin is a natural area in which human intervention is very low up to the Karaj Dam. Recent research has investigated the extent of geodiversity and diversity of geosites in the upstream basin of Karaj Dam with the aim of environmental management.

This research has been done using data extracted from Landsat 8 images, Aster elevation data and field surveys. The research method included assessing the diversity of Karaj Dam basin using PR (Patch Richness), SHDI (Shannons’s Diversity Index) and SIEI (Simpson’s Evenness Index). In this way, a 25 km cellular network has been placed on the basin. The purpose of this operation was to create smaller units to calculate the result of the indicators more accurately. In the next step, using the typology method in terms of intrinsic value, the sample geodiversity representative and geological dimensions have been identified and evaluated. In this regard, visual observations, field sampling and Landsat 8 image have been used in the following criteria.

The results of the study of selected geodiversity indicators showed that the area around the Karaj Dam Lake and the south of the basin are more suitable conditions in terms of the number of classes obtained. These results are based on the visible bands of the Landsat image and the elevation model. The PR index, which shows the natural richness of the earth, means the presence of diversity, which is shown in visible images. The maximum of this diversity is observed around Karaj Dam Lake and south of the basin. The SHDI index is an index used to describe the diversity of species in a community (Sarma and Das, 2015, 635) and And the SIEI index, which indicates the probability that random features belong to different species (Goudarzian and Erfanifard, 2017, 10) And the SIEI index, which indicates the probability that random features belong to different species, is also calculated based on the color spectrum diversity of the visible bands, which theoretically represent the diversity of the ground or geodiversity. On average, in the cells that had the most replication among the indicators in the very high geodiversity class, the height and slope also varied. To study the earth typology in terms of vulnerability and protection of geosites, although sampling has been done from the whole basin, but according to the above results, most of the field observations have been made around the lake and south of the basin. In this regard, by examining geological and geomorphological maps, Landsat 8 satellite images and field observations, features and sites of the basin were identified. Based on origin in lithology, hydrogeology, geomorphology, stratigraphy and tectonics, as well as by shape; Point, section, area, viewpoint, and complex were classified. After identifying the sites and classifying them, the values of each site, including tourism, science, and protection were evaluated. Each site can have a variety of values within it that need to be protected. Geosite protection can be beneficial in terms of ecotourism and tourism and revenue generation.

The geodiversity of Karaj dam basin was evaluated by PR, SHDI and SIEI indices. The results showed that the Karaj dam basin has a significant geodiversity that is closely related to landforms. The results of typological analysis and vulnerability assessment in Karaj dam basin lead to the identification of point features such as waterfalls near roads, main rivers and geological features of this basin due to increased construction (road construction, recreational areas, restaurants and restaurants) or caves which are prone to destruction due to dumping of waste and garbage. Most of the geosites in Karaj Dam are on a point scale, which are very vulnerable, and in the next stagevare section, they are also more vulnerable, and in total, 82% of the studied species have a high vulnerability that needs protection. Thematically, geomorphological and tectonic geosites are a total of 67% with high vulnerability. Comparison of recent findings with Fernandez results in 2010 has shown a great deal of similarity in terms of the shape and subject matter of geosites and the level of vulnerability. In general, these complications are scientifically very important due to the specific conditions of their creation and persistence. Also, the existence of these features is aesthetically valuable and can create valuable places to attract tourists, so the management of such environments is essential.

The morphology of rivers is constantly changing due to their dynamic characteristics. Water flow and sediment transport play a major role in the dynamic activity of the river and in interaction with environmental factors, they cause different behaviors in the river. River adjustment occurs in three groups: riverbed adjustment, lateral adjustment and whole river changes. In flood hazard mapping are usually evaluated probabilistically the hydrological characteristics of the flow, include the frequency and magnitude of the flow and do not consider the dynamics of the river morphology. Therefore, analyzing channel morphological changes with geomorphological approaches and methods to study river dynamics and instability reduces this problem. The aim of this research is to classify the morphological dynamics of Babol River for flood and river channel management. Another purpose of this study was to investigate the relationship between environmental variables and river morphology dynamics.

In this study, the dynamics of Babol River were investigated based on the characteristics of river form and process, artificial features and river adjustment by morphological dynamic index (MDI) method, which has been proposed in the framework of IDRAIM (Rinaldi et al, 2015). River morphological dynamics index are (MDI) divided into three categories: morphology and process indices (M), artificial indices (A) and adjustment indices (CA). First, eight reach of Babol River (Mazandaran province) were selected in foothill and plain area. Geomorphological map of river landforms including river channel, lateral bar and point bars, floodplain and alluvial terraces has been prepared and drawn using Google Earth images of 2020, 2007 and fieldworks. To study the long-term changes of the river, aerial photographs from 1335 and studies conducted by other researchers were used. Some of the changes were assessed based on terrestrial evidence. Each indicator was scored and then the final value of MDI was calculated. River reaches were classified into several categories (very low, low, medium, high and very high) based on the morphological dynamics of the river.

Eight river reaches were studied in this research. The reaches are in the range of 200 meters to -25 meters above sea level. Their slope varied from 0.001 to 0.018 m/m. The mean width of the channel ranged from 12 to 77 meters and the mean width of reaches, which includes channel and floodplain, ranged from 41 to 83 meters. The river confinement index was between 1.1 and 4.4 and confinement degree of the reaches varied between 18 and 100%. In general, this reaches of Babol River are mainly partly confined. The channel sinuosity coefficient varies from 1 to 2.2 and the river pattern in these eight reaches are straight, sinusoidal and meandering. Based on the total scores of MDI, reaches 1 to 4 were in the high class, reaches 5 and 6 were in the middle class, and reaches 7 and 8 were in the low and very low classes of river morphological dynamics, respectively. By calculating the ratio of each group of indicators to the maximum value of the same group, the relative value of each group was obtained. The value of MDI decreased from upstream to downstream, indicating a decrease in the morphological dynamics of the river in the downstream areas. The trend of MDI changes and its constituent indices with the width of the river channel are most consistent with exponential regression and indicate a decreasing exponential trend. These trend of changes are faster for the morphology and process index and the index of river adjustment, and then have a milder trend. Thus, upstream reaches are more active in terms of morphological dynamics than downstream reaches and show a significant relationship with the width of the river channel.Active river width and confinement degree had a correlation coefficient of -0.92 and -0.78 with MDI index, respectively, which shows that with increasing each of these two variables, the morphological dynamics of the river has decreased. The variables of height, slope and confinement index had correlation coefficients of 0.68, 0.62 and 0.78 with MDI values, respectively, which indicated an increase in the morphological dynamics of the channel with increasing these variables. High correlation (0.94) of group M indicators with CA group indicates the high effect of morphology and natural processes of the river on the rate of adjustment and artificial factors could not have much effect on the natural characteristics of the river.

The analysis of the results shows that in the reaches with medium and high morphological dynamics index (MDI) where the river plan and channel geometric dimensions can be further changed, by identifying the previous river path and channel dimensions, different scenarios can be presented for zoning and flood hazard mapping. The study of the relationship between different variables and morphological dynamics indices (MDI) shows significant changes from upstream to downstream and the decrease in MDI downstream and high correlation coefficients between variables is consistent with the pattern presented in the model. Therefore, this model can be used in geographical types similar to the study area and has been required for other cases and has been validated.

One of the quantitative and experimental methods that has been used by researchers in recent decades to study the relationship between drainage network and hydrograph forms is the use of fractal dimension. Some hydrogeological and morphometric parameters of watersheds that have a special geometric shape can be studied more accurately with fractal geometry and by calculating the fractal dimension of each of the characteristics of the river basin, new parameters can be prepared for watersheds that can Explain more features of watersheds in terms of flooding, erosion, runoff estimation, and sediment. (Ildoromi et al. 2019).Mohammadi Khoshoei et al. (2020) Comparing fractal dimension and geomorphological features in Aqda watershed management showed that there are significant relationships between fractal dimensions of basin shape and drainage network with geomorphological features, and the highest correlation coefficient belongs to regression relationships. Drainage network can be seen between the total length of the drainage network and the fractal dimension Dutta et al. (2014) in the study of glacial landforms in Himalia using multi-fractal analysis showed that with fractal analysis, landforms created by different processes can be separated. Hui et al. (2017) in examining the relationship between the fractal dimension of the drainage network and the evolutionary stages of erosion of the China Yellow Basin showed that the fractal values of the drainage network have a positive and linear relationship with the sediment delivery and runoff values of the basin. The purpose of this study is to find relationships for concentration of time based on the fractal dimension by producing a fractal triangular unit hydrograph under the basins of the River basin kalan Malayer in Hamadan province.

The Kalan Basin is located in the branches of Karkheh watershed.In this study, to extract the geomorphological parameters of the watershed from the GIS, DEM map, elevation difference, basin slope, flow direction layers, cumulative flow direction, flow length layers and streams categories and river chanal map, River Networks length the original was extracted and prepared for each sub-basin. In this research, the results of fractal dimension by box counting method, the results of drawing NRCS triangular unit hydrograph, the results of drawing fractal unit hydrograph, the results of comparing NRCS unit hydrograph and fractal unit hydrograph in all sub-basins kalan has been validated and the relationship between river basin concentration of time and its fractal properties has been evaluated based on computational error including peak flow error rate (CFS), peak time error percentage (Hr), and base time error percentage (Hr). The sub-basin hydrograph has been modified.

The results show that the greater the difference in basin height, the less the agreement between the NRCS unit hydrograph and the triangular unit hydrograph and shows that fractal hydrographs in all sub-basins have improved the concentration time relative to the hydrographic network .Below basin C, there is an acceptable agreement between the fractal dimension and the NRCS hydrograph, which indicates the accuracy of the results of the fractal dimension analysis of the drainage network. It can be concluded that the NRCS unit hydrograph and the fractal unit hydrograph are well matched .However, in the river basins B and E, the hydrograph of the NRCS unit of the fractal unit does not match well, which is due to the low level of the River Networks, (drainage network). The results showed that the greater the height difference, the less the agreement between the NRCS unit hydrograph and the triangular unit hydrograph. This study confirms the error percentage of fractal hydrograph and NRCS parameters related to each sub-basin.

Production of artificial unit hydrograph based on concentration time, main river networks, length, height difference and geomorphological characteristics is one of the important and accurate tools in this regard that can be used to produce artificial unit hydrograph based on fractal timec enter and corrected. The results of artificial unit hydrograph production based on fractal characteristics of the kalan basin river basin showed that the NRCS triangular unit hydrograph can be plotted and estimated only by having a morphological image of the chanals and without the need for complex calculations. Examination and comparison of fractal unit hydrograph and NRCS unit hydrograph showed that the fractal dimension hydrograph provided a relatively good agreement with NRCS.This raises the accuracy and efficiency of the fractal dimension hydrograph using geomorphological indicators in particular, the drainage network, especially in river basins without a measuring station shows. Examination and comparison of fractal unit hydrograph and NRCS unit hydrograph showed that the fractal dimension hydrograph provided a relatively good agreement with NRCS and this issue of accuracy and efficiency of fractal dimension hydrograph using geomorphological indicators, especially drainage network, in river basins without indicates the measuring station. It is suggested fractal unit hydrograph with other hydrogeomorphological parameters such as basin shape coefficient should be performed and checked with HEC-HMS hydrograph.

Among the various types of water erosion, gully erosion is one of the most important events affecting soil destruction, landscape change, loss of water resources and land regression (Poison et al., 2003) that occurs under certain environmental conditions. This type of erosion is an evolved form of furrow erosion that forms at the beginning of valleys or on slopes and plains and cut sections (roads and canals) (Tucker, 2005). This type of erosion occurs widely in arid and semi-arid regions (Frankl, 2012). There are various methods for determining areas prone to gully erosion, that the Multiple-criteria decision-making (MCDM) method is one of the most recently used methods. Arabameri et al. (2020) used MCEM to determine areas prone to gully erosion in the Dasjard River watershed in Iran. The results showed that machine learning (ML) method in GIS environment is a suitable method for determining erosion sensitive areas. Hembram and Saha (2020) used the fuzzy-AHP and compound factor (CF) methods to determine areas prone to gully erosion in the Jainti River basin in India. The results showed that both methods have good accuracy for predicting erosion. Choubin et al. (2019) used the fuzzy analytical network process (Fuzzy ANP) method to determine areas prone to gully erosion in Kashkan-Poldokhtar Basin, Iran. The results showed that drainage density, soil texture and lithology are the most important factors of watershed erosion in the study area. Couple hybrid algorithms of a commonly used base classifier (reduced pruning error tree, REPTree) with AdaBoost (AB), bagging (Bag), and random subspace (RS) were used to determine areas prone to ditch erosion by Nhu et al. (2020). The results showed that the RS-REPTree hybrid model has high accuracy in determining erosion in Shoor River watershed in Iran. One of the areas in Iran that has undergone land use changes in recent decades is the city of Mohr in the south of Fars province.This area is located on erosion-sensitive soils, which has recently led to large gully in the area. Due to the importance of the subject in this study, areas prone to erosion have been identified using the fuzzy method and AHP and the necessary solutions to prevent the progression of this erosion have been presented.

In order to prepare the areas prone map to gully erosion were used aspect data, CL, Dd, elevation, TPI, geology, land use, LS, curvature plan, TRI, profile curvature, rainfall, distance to river, distance to road, TWI, slope, soil , SPI, NDVI as input data. After preparing zoning maps for each of the parameters, the fuzzy membership function was used to prepare fuzzy maps for each of the parameters. In this study to prepare a fuzzy map of slope, distance to road, TRI, soil, altitude, TWI, LU, SPI, LS, direction, distance to river from incremental linear membership function. For other parameters, the decremental linear membership function was used (Arabamari et al., 2020). Then, to prepare the final map of areas prone to gully erosion, using AHP method, a two-by-two comparison of each parameter was performed based on the degree of importance of each of them.Then, using Expert choices software, the qualitative results became quantitative and finally the weight of each parameter was determined.

The results of AHP method showed that lithology has the highest impact (weight 0.2) and LS has the lowest impact (weight .002) in mapping areas prone to gully erosion. The results of fuzzy and AHP methods showed that the areas located in the center (about 15%) of the study area are more sensitive to erosion. The results also showed that large gully erosion have been seen in the areas that are prone to gully erosion. Therefore, the AUC values were close to 85%, which indicates the high accuracy of the model for predicting areas prone to gully erosion. Gully erosion created in the region is a serious threat to rural and agricultural lands in this region. In fact, with human interventions in erosion-sensitive areas, it leads to the progression of erosion and loss of satisfaction (Arabameri et al., 2019). Land use as a variable is very effective in spreading gully erosion. Rijsdijk et al. (2006) in a study of Java ditches in Indonesia concluded that changes in land use and improper plowing were the cause of the increase in ditches in this area.

The results showed that the areas located in the center of the study area are more prone to gully erosion than other sections. In this study, it was found that land use changes have led to intensification of erosion in the region. So that with the increase of agricultural and residential lands in the study area, the rate of gully erosion has increased. Therefore, it is important to use soil protection operations to control and prevent the progression of gully erosion in this area.

Gully erosion as one of the common forms of erosion causes deformation of the land surface and its spread is one of the main reasons for the destruction of agricultural lands, communication roads and irrigation system of the basin, especially the plains on the slopes east of the basin to Chaho village. The area is eroded and made inaccessible through the creation and development of ditches and the agricultural productivity of the area is reduced. Therefore, by studing the physical and chemical properties of the soil and also determining the topographic threshold, an attempt has been made to identify the factors affecting gully erosion and to prevent the damages caused by it as much as possible with a more accurate prediction.

The study area is the Shoor River watershed in the East and Northeast of Mohr city, which is located in the south of Fars province with an area of 101350 hectares. This watershed is located between 27 degrees, 27 minutes and 22 seconds to 27 degrees, 49 minutes and 41 seconds North latitude and 52 degrees, 24 minutes and 58 seconds to 52 degrees, 59 minutes and 14 seconds East longitude. According to the divisions of the country's catchments, the study area is part of the catchments of the Shoor and Mehran rivers, which eventually enters the Persian Gulf.In order to initially identify the natural features of the basin and collect theoretical topics, basic topographic maps (scale 1: 25000) of the National Mapping Organization and geological map (scale 1: 100000), Geological Survey and Mineral Exploration Organization were used. ArcMap version 10.3 software was used to draw the maps. Then 15 ditches were randomly selected. To select the topographic threshold, all selected ditches in the relation were used. While to study the physical and chemical properties of soil (sand, clay, silt, PH, EC, TNV, Mg, Ca, K, Ca, SAR, Na) and geometric measurements, gullys based on cluster analysis It was classified in which geometric measurements were considered as dependent variables and soil physical and chemical properties were considered as independent variables. Tests were performed on the data in SPSS software.

The results of clustering analysis showed that the gullys were classified into three groups. Since more than 53% of gullys are in group one, they have been used for statistical analysis. Correlation and multiple regression models were performed to analyze the relationship between dependent and independent variables. The results of Pearson correlation showed that the length and width of gullys had a very strong relationship with the variable of sodium (/ 866) and SAR (/ 826) while it had a negative relationship with the variable of soil PH (-258). Then, using multivariate regression, the relationship between the independent variables and the gully length and gully cross section was determined. The results showed that the amount of sand, SAR, TNV and sodium had the greatest role in the longitudinal and cross-sectional area of the gullys , respectively. However, the presence of OC and K prevents the spread of moat erosion in the region. According to the results of the topographic threshold formula of the region (S=6759.756A^(-.556) ), the surface runoff process was recognized as the dominant hydrological process affecting the spread of gully erosion.

gully erosion plays a major role in soil degradation. Rapid progression of moat erosion at the eastern end of the basin In addition to the destruction of a large area of agricultural land and rangeland of the basin, are a serious threat to several villages, especially the villages of Qala-e-Seyed and Chahoo and even part of the city of Mohr. The results of the longitudinal expansion and cross-sectional area of the gullys show the high impact of SAR, TNV and sodium in the soil in creating and spreading the gully erosion. However, OC and K prevent the formation and spread of gully erosion. the soil texture is mainly sandy and loamy and sand has the highest percentage in all samples. Sand particles weaken the soil structure and in spite of water, they lose their cohesion and the underlying layers dissolve and then the upper surface of the gully collapses and causes the development of the gully. The results of topographic threshold showed that surface runoff causes gully erosion so that the lower the slope of the area, the more upstream area and more runoff is produced and easily washed with aggregates with low stability and creating valleys along the route. It causes gully erosion. Based on the results of the research, it is suggested that due to the high amount of sodium, chemical modification should be done first and then the vegetation in the area should be modified and created. Due to the high production of surface runoff, mechanical runoff can be collected through temporary methods including creating temporary dams, rock dams, and soil dams at the end of gullys. It is suggested that combined methods such as CF statistical methods and ME algorithm for modeling be used to more fully investigate the gully erosion of the area.

The identification and analysis of the active tectonic or denudation processes through the analysis of the deformation and landform changes consist one of the fundamental objectives of the tectonic geomorphological studies. Rivers are among the groups of geomorphologic elements that flow on a wide range of different landforms and can reveal the critical relationships among uplift, lithology, and denudation of heights. With regard to the evolution of landforms, this group of information and the relations between them are preserved by the bedrock properties. River Incision is the primary mechanism by which landscapes adapt to climate change and tectonic forces. Among the many factors that affect the Incision rate, the distribution of slope and steepness of water channels can be systematically effective. The main purpose of this study is to investigate the sequence of mountainous and foothills landforms in Damghan region using slope changes and erosion-incision reaction of rivers on the surface of these landforms as one of the key factors in landscape evolution.

There are many models for calculating the river incision rate, but the most widely used is the SPIM model, which is presented in the form of the following equation:I=K*A^m*S^nThe SPIM model is based on simple geometric parameters, such as the slope and area of the drainage basin extracted from the DEM elevation map. Some parameters are related to energy considerations, such as the rate of energy consumption in the channel bed and ridges, in which case; m: 0.5 and n: 1 are used as experimental constants in the formula.In order to calculate the values of this index and prepare a river incision map, first the whole study area was divided into 64 sub-basins so that the resulting section values are suitable for surface interpolation. In the next step, the values of effective indicators in the SPIM formula including river slope, drainage surface area and erosion efficiency were calculated for each of the sub-basins. To calculate the erosion efficiency index, first the steepness values of the rivers of each basin were calculated from the formula of stream power incision, based on power regression, in the form of the following equation.S=K_s A^(-θ)In the above formula Ɵ is the amount of concavity and KSN is the amount of steepness.After obtaining the steepness values of rivers in each of the 64 catchments, the erosion efficiency relationship was used as follows:U=〖ksn〗^n*KU is actually the rate of elevation or change in altitude of the area relative to the base level, which was calculated using the radar interfrometry method to determine the amount of vertical displacements in the area.In order to prepare and analyze the slope and incision rate of rivers in Damghan region, and to convert point values into raster levels containing value, the inverse distance weighted interpolation method or IDW was used.

Comparison of longitudinal profiles taken from the slope map and incision rate of Damghan region shows the close relationship between these two parameters; Both of these parameters together play an important role in analyzing the tectonic status of the areas. In such a way that in examining the condition of the longitudinal profiles of the region from north to south, there are prominent features such as mountain belts or foreberg shapes; The slope rate and incision rate of the river increase and in front of where there are depression constructions such aspull apart basins or the end parts of longitudinal profiles that are based on alluvial plains, the slope rate and the following incision rate of the river decreases.Therefore, the analysis of longitudinal profiles taken from the slope map and incision rate of rivers in Damghan region can be effective in identifying and analyzing the effect of active fault mechanisms on the sequence of landforms in the region. the areas that have mainly high slope and incision rate of the river and are shown prominently in the longitudinal profile, represent the performance of faults in the form of transpressional, which leads to the formation of elevated landforms. In contrast, the concave areas in the longitudinal profile of the slope and incision of the rivers in the region are mainly representative of the areas where the gentle slope has led to a reduction in the slope of river systems and thus reduced river incision capacity.these areas are either mainly based on flat lands which are in the southern part of mountain structure in form of alluvial sediments or they are collapsed structures due to transtentional motion of faults such as Astaneh pull-apart basin.

The activity of faults with different mechanisms causes the uplift or subsidence of landforms to form a series of successive landforms in an active tectonic environment. The rise and fall of these structures have led to an increase or decrease in their slope which will effect on the waterway systems that flow on these landforms. Wherever the fault mechanism leads to an increase in the height and elevation of the landforms, the slope of the river increases and as a result the incision power of the river increases. From the analysis of longitudinal profiles taken from the slope map and the incision of the river, it can be concluded that this method is very useful in identifying the sequence of landforms affected by tectonic processes. In a way, by examining the process of changing these longitudinal profiles, we can understand how active faults function in shaping landforms in compressive or tensile form. Wherever the slope of the waterway is high and the incision rate of the river is high, it indicates the existence of a elevated axis. This landform can be a mountain ridge or even elevated forms among alluvial sediments.wherever the slope and incision rate of channel show low values, it can indicate the existence of a concave tectonic basin.

Landslides are one of the most important land hazards in the world that occur from falling or moving in an integrated and often rapid volume of sedimentary material along the slopes (Sharafi et al., 1399: 128). Instability of natural slopes is one of the geomorphological and geological phenomena that has an effective role in changing the shape of the earth's surface (Saraskanrood et al., 1399: 2). Landslide studies indicate that landslides are a hazard that often occurs frequently, and is present on all continents and is a global threat to humans, infrastructure and the environment (Brooke et al., 2018: 125).

In this study, first the effective factors in landslide occurrence include altitude, slope direction, slope, distance from fault, waterway density, distance from river, soil, land use, distance from road, NDVI vegetation index, geology, slope curvature, Land type, slope transverse profile, slope longitudinal profile, canal power index (SPI) and topographic moisture index (TWI) were identified. In the next step, information layers related to each factor were prepared in the GIS environment. Information layers of curve lines, communication paths, waterway network and drainage density were obtained by digitization from a topographic map with a scale of 1: 50000 and slope and slope direction layers were prepared using DEM digital elevation model with 10 m spatial resolution. Took. Geological and fault layers were prepared by digitization from a 1: 100000 geological map. A 1: 50000 land use map was used to prepare the land use information layer. To prepare a soil map, a soil map of 1: 50,000 has been used.Resul In the weighted evidence model and the definitive evidence function, the western direction (1.03) had the most impact and the northern directions (-1.22) and flat (0.03) had the least impact on the occurrence of landslides. In both models, a slope of 20 degrees (2.17) had the most impact and less than 10 degrees (0.0) had the least impact on the occurrence of landslides. The highest number of landslides in both models was observed at an altitude of 2000 meters (1.44) and the lowest amount of landslides at an altitude of less than 1000 meters (0.0). The soil type of alpha sol has the most effect (1.28) and Inseptol has the least effect (0.0). In the weighted evidence model and the definitive evidence function, medium drainage density (1.6) and (1.12) have the most effect and low drainage density (0.2) has the least effect, respectively. As can be seen in the map, the distance from the fault in both models is 0-200 meters with the highest impact (2.19) and the lowest impact at a distance of more than 1000 meters (-1.16). Regarding the parameter of distance from the road in the weighted evidence model and the definitive evidence function, distance of 0-500 meters with (1.18) and (1.33) have the most impact and distance of 1500 meters have the least impact (1-6), respectively. is. Examination of the geological map showed that in both models, Sarcheshmeh Formation had the greatest impact (2.28) and Neogene sediments had the least impact (0.16) on landslides. In the parameter of distance from waterway in both models, distance is 0-300 m with the highest (2.22) and lowest (0.11), land use has the highest impact of rangeland use with the highest (1.33) and the lowest forest lands (0.33). ), Vegetation index has the most impact (1.81), in the slope curvature of flat surfaces with the most impact (1.77) and the lowest concave surfaces (0.2), waterway strength index with the most impact (1.88) and the lowest ( 0.27), topographic moisture index with the most impact (1.66) and the least impact (0.11), mountainous land type with the most impact (1.99) and the least impact (0.15) and longitudinal profile and land profile Domain has the highest impact (1.85), (1.63) and the lowest impact (-1.1) and (-1.3), respectively.

The combination of landslides in the distance layer from the waterway also indicates that the highest distribution of landslides is in the floor with a distance of 200-400 meters. Regarding the vegetation index, it can be concluded that the lower the vegetation density, the more landslides occur. Because a large part of the study area is mountainous with high walls and deep valleys. Therefore, the reason that the sensitivity of landslides increases in the study area with increasing slope can be attributed to the high amount of rock falls and overturning in the area. In general, regarding the shape of the slope in various forms, it should be said that flat slopes have less strength than convex and concave slopes. Waterway power index, topographic moisture index, longitudinal profile index and slope transverse profile index also have a great impact on landslide occurrence. The results show higher accuracy of the definitive evidence function (EBF) model than the support vector machine and weighted evidence function models. The reason for the high accuracy of the EBF method compared to the other two methods is that this method is a combination of other methods. Also, the higher accuracy of statistical methods than decision-making methods is another result of this research. Finally, by preparing a landslide risk zoning map, it is possible to help planners and managers in order to reduce potential damages and find safer places to develop construction and road construction.

The Earth's solid crust has not been fixed throughout the history of geology but is constantly changing under the influence of internal and external factors. These elevation changes in the form of subsidence and elevation significantly increase the trend of environmental hazards that affect of these hazards causes severe damage to the natural environment and human effects (Zare Kamali et al., 2017).According to the US Geological Survey, the phenomenon of subsidence involves the collapse or subsidence of the earth's surface, which can have a small displacement vector, which is said to occur gradually and instantly on a large scale (Geological Survey, 2011). The most important cause of subsidence of surface areas in sedimentary basins of arid and semi-arid regions is the compaction and compaction of sediments due to improper extraction of groundwater aquifers (Zhou et al., 2015). If wet clay layers are located between the sand layers, this phenomenon will be observed more widely and acutely (Liu et al., 2006). Land subsidence usually occurs with a time delay after prolonged abstraction of groundwater resources (Scott, 1979). The amount of subsidence depends on the thickness and compressibility of the layers, the duration of loading, the degree and type of stress (Signa et al., 2014).Research dataThe purpose of this study is to monitor land surface changes and identify areas with subsidence and uplift and identify the rate of these changes in the area and finally to investigate the causes and factors affecting the occurrence or exacerbation. For this purpose, first the Sentinel-1 radar image series with suitable time and place difference (maximum 150 meters) including 25 images (Table 1) in the period 2014 to 2021 with Ascending direction and also 12.5 meters Dem related to ALOS PALSAR sensor from the space agency site. Europe (Vertex) was prepared.In addition to radar data, information about the trend of changes in the level of piezometric wells in the region and also the average monthly precipitation of the region to compare and investigate the causes of subsidence in the study area were provided by the Water Resources Management Company and the Meteorological Organization, respectively.

In the present study, using the SBAS time series method in the period 2014 to 2021 in the metropolitan area of Karaj by selecting 25 Sentinel-1 images with appropriate time and place distance, the average subsidence velocity, and land subsidence in the study area was estimated.To determine the main factors of this event, the study area was examined in more detail in terms of mining, tectonic activity, land use in terms of construction of massive structures, and finally changes in groundwater level. Then to investigate the causes and factors. The decreasing trend of groundwater level and precipitation in the region during the last 6 years was also examined.

The results of time series analysis of interferometric images show that in Karaj metropolis the number of land surface changes was between -145 to +15 mm and the areas with subsidence in the northwestern part of the study area are Mehrshahr which recorded subsidence between 100 and 145 mm. To determine the main factors of this event, the Mehrshahr region was examined more precisely in terms of mining, tectonic activity, land use in terms of construction of buildings and massive structures, and finally changes in groundwater level, which showed that only water level changes. Underground in the region has a trend corresponding to subsidence in the Mehrshahr area. To investigate the causes and factors of the declining trend of groundwater level, rainfall in the region during the last 6 years was examined. On groundwater recharge and eventually subsidence.

The importance and increasing monitoring of land status, especially in order to identify the occurrence of subsidence that has occurred in recent years and following the drought and over-exploitation of groundwater resources have caused more attention by researchers in this regard. In the present study, due to the importance of the subject and the study area, the rate of subsidence and its relationship with groundwater level changes were evaluated. The results showed that in the metropolis of Karaj in the period of 6 years 2014 to 2021, the highest rate of land movement was between -145.27 to +15 mm.Therefore, according to the results of the present study and the direct relationship between subsidence in Karaj metropolis with groundwater decline, it seems necessary to monitor the use of groundwater in the region, especially in agriculture, because the current trend in the use of groundwater Recent droughts will lead to irreparable risks of subsidence in the region.

Worldwide cause landslides are considered as natural disasters, which to many dead and intense damage. So, it is important to examine the impressive factors for urgent planning and presence management solutions for sensitive regions. A landslide based on geological and geomorphological factors, hydrological, and biological and human; but only the trigger or external factor is a key factor to start a landslide. Intense storm, fast snow shrinking, sudden changes in groundwater level, earthquake, and fast erosion are regarded as the most important trigger factors for landslides (Sidle & Ochiai 2006(. Rainfall is considered as the most common trigger factor in the occurrence of landslides (Crozier1999; Jacob 2003). The event of a landslide relies on various factors, for example, geological, geomorphological, hydrological, biological, and human. However, the basis in making a landslide is mainly a trigger factor where precipitation is recognized as the most common one. Therefore, recognition of natural factors and human activities, causes and intensifiers of landslides, on the other hand slope stability analysis largely experts will help determine the most appropriate way to integrate slopes slippery. Whether old or new in this region, the slopes of folded Zagros in the range of studying area are sensitive to slippery movements, proved by numerous landslides. Massive movement of materials, like a landslide, is one of the problematic slope processes in Javanrood located in the northwest of folded Zagros, for this phenomenon leads to demolition of forest lands, farms, and pastures of the region. In addition, it is considered a threat to road traffic. Current study to the threshold of critical rainfalls in the occurrence of landslides in the Javanrood basin using a physically based model set. Physical models need accurate and comprehensive information on soil characteristics and hydrology slope. Operations such as the pattern of rainfall and groundwater level changes modeled mathematically in physical models of landslides2.

Application of materials in this research was Javanrood s 1. 50000 topographic maps, 1; 100000 geological maps, 1; 55000 spatial images, Google earth satellite images, GPS, 20m altitude numerical models, Arcgis and Matlab softwares and laboratory parameters, including dry soil specific weight(γd), wet soil specific weight (γt), hydraulic conductivity, soil internal friction angle (φ), soil cohesion, and the porosity of the soil.This research was completed through the fields, and empirical methods. Search steps are summarized as following: In the present study, 12 slopes of Javanrood, including 7 unstable slopes, and 5 Stable slopes, were chosen as the samples. All the alternatives of slope stability analyses were found using field studies, experimental studies, and topographic analysis of the landslides. The model utilized as a part of this research was the model of Talebi (2008) which was indeed, an amplified model of a physically-based model, being a blend of geometry model, hydrology model (perpetual condition), and unending slope stability theory. This model is used to study shallow landslides in slopes with different topography in regards to arrange shape (concave, convex, parallel), and profile curvature (concave, convex and direct). It considers the impacts of slope morphology on saturation storage of plan shape and length profile. At the end, with a reverse method of the safety coefficient decreased on the stability of the 1 and the critical rainfall was determined for each slope.

The results showed that this model efficiently determine enough to critical precipitation. It was found that vulnerable slope slip less critically needed precipitation as the stable. According to the calculations, the amount of critical rainfalls for unstable landslides is less than 50 mm per day, although it is more than 100 mm / day for the stable. In addition, a safety factor in various periods return indicates that as the return period increases decreases the amount of stability slop. On the other hand, the return period increases for some instable slopes, will reduce their instability.

The objective of this study was to determine the critical rainfall in the occurrence of shallow landslides by the famous process-based model (Talebi 2008) in Javanrood. The results of factor values stability and critical rainfall of slopes study demonstrates that the model efficiency enough to identify critical rainfall. In accordance with the precise information about the soil and the hydrology of slope, can mathematically model the process as rainfall and water level changes on the land, and merge with penetration models and analysis of stability of slope. So, are able to assess the necessary rainfall for show landslide. According to the findings of significant rainfall in the region, it can be said that critical rainfall for the slopes of the region depend on the amount of the stability of the slope. Stability of slope is under the influence of morphological and hydrological factors and soil of them mechanical. So, the slopes with low safety factor needs less critical rainfall to define these landslides than stable ones.

Identification of landforms is one of the basic studies in the Knowledge of geomorphology. The importance of identifying landforms are due to their application in various rural and urban planning, landscaping and tourism planning.Traditional methods of identifying landforms like to Visual interpretation, are both time-consuming, boring and costly, particularly on a large scale and are not sufficiently accurate in identifying the boundaries of macro-landforms. Subjectivity and the application of personal tastes is one of the most important issues in only traditional methods. Because it does not have enough accuracy in determining the boundaries of landforms and sometimes the type of landforms. The solution of this problem can be investigated in digital images context analysis. In this research the study area is Yazd-Ardakan basin.It is located almost in the center of Iran. This basin is geomorphologically limited to Ardakan Playa from the north and from the south direction is limited to Shirkuh heights, and from the east to Khoranagh sub-basin and finally from the west to Nodooshan sub-basin is connected. The purpose of this study is Detection of the macro geomorphological landforms in Yazd Ardakan basin using optimum composition index.

In this research, the ETM+ sensor data from 7th generation Landsat satellite has been used to identify the large landforms such as Playa, pediments and, etc. The data of this sensor have many applications in the field of geomorphology such as shoreline displacement, sedimentary and erosion basin identification, mountain front identification, plains, beaches, separation of lithological structures, water networking and, etc. which in this study are geomorphological Yazd-Ardakan has been discussed. In this study, were used 9 bands of ETM + data related to 162 pass and 8th row and dated 19 August 2010, which were almost without cloud cover or cloud free. Exact time of imaging according to the information in the metadata file was nine hours, eleven minutes and thirty-nine seconds. Also, the general geomorphology map extracted from the geomorphology map of Iran related to the Institute of Geography of the University of Tehran and also Google Earth software have been used to investigate the accuracy and compatibility of the identified landforms resulting from digital processing of satellite images with terrestrial reality.In this study Geo-statistical methods were used.The Optimum Index Factor provides the best and most suitable band composition among the possible types of spectral band compositions based on the amount of total variance and correlation between band compositions.In this method, the selection of the optimal combination between the bands is done by quantitative evaluation of the effects in the image.This method avoids wasting time due to the large number of possible RGB compounds in the visual analysis process. OIF values are used to determine the most optimum bands composition, and bands are ranked according to their statistical information, which includes total variance and correlation between different bands.The best band combination of all three possible band combinations has the highest amount of information and the lowest repetition rate. In this study, the "law of composition" in statistics was used to select "r" objects (here a combination of 3 bands) from "n" objects (here 30-meters Landsat bands). This law is in the following relation:C(n,r)=n!/r!(n-r)!Where: C(n,r) is a combination of r object from n object and sign! It is called factorial and the factorial of any natural number (here 6 spectral bands of ETM + sensor) means the product of that number multiplied by all natural and integer numbers before itself In general, the product of n × (n-1) × (n-2) ×… 2 × 1Therefore, 20 bands compositions can be written for ETM+ sensor reflective bands, of which only one combination is the most optimal and desirable band composition for displaying geomorphological features of the earth surface due to having the most non-repetitive information, and it is the compound that have with the highest OIF statistical value.TIn order to calculate the OIF that shows better the surface landforms on a large scale, the correlation coefficients between the different bands must be calculated. Here, to show the degree of correlation between different ETM+ bands, a correlation matrix is used, which have always number one in his main diagonal.

First, the basic statistics (including mean, minimum, maximum, standard deviation and eigenvalues) were calculated for 30-meter bands of ETM+ sensor. The mentioned parameters are used in calculating OIF. Then the correlation matrix was calculated between ETM+ spectral bands in the ENVI software. Finally, the OIF index table was obtained for all possible three-band combinations by the basic statistics table and the correlation matrix table. The results of the recent table showed that the best and most optimal band compositions that lead to the maximum Detection of landforms are related to rows 12 and 20 of this table, because the mentioned rows had maximum OIF values. Other results of this research were the produce of a raster map and vector map of identified large landforms obtained by OIF.

This study showed that the higher the standard deviation between a three bands combination and the correlation coefficient between them be less, the OIF index have the higher value. This means that the three bands color combination is one of the most non-repetitive information items. In this study, two bands combinations of 124 and 234 of the ETM+ sensor had the highest values, and both combinations had approximately 54 OIF values. The advantage of calculating this index are 1. Finding the best three bands color combination to highlight and Detection the image, 2. It is fast and repeatable due to digital image processing so that if we want to visually determine the best three bands combination, it is very boring and time-consuming. The Results of the OIF index has shown that the best bands of twenty different combinations, is two-three-four spectral combination. Because the OIF index was greater than the other band combinations (OIF=54.01). The combination of recent spectral bands (two-three-four) led to identify the mountainous and flood spreading pediments too Sebkha landform.