فصلنامه پژوهش های ژئومورفولوژی کمی
سال نهم شماره 2 (پیاپی 34، پاییز 1399)

Coastal management needs to be organized at scales which are fully representative of the dynamics of the coastal system. A littoral cell is a coastal compartment that contains a complete cycle of sedimentation including sources, transport paths, and sinks. The cell boundaries delineate the geographical area within which the budget of sediment is balanced, providing the framework for the quantitative analysis of coastal erosion and accretion. The sediment sources are commonly streams, sea cliff erosion, onshore migration of sandbanks, and material of biological origins such as shells, coral fragments, and skeletons of small marine organisms. The coast of the Hormozgan province is marginal sea type and geomorphologically, it has coastal complexities of this type. It is difficult to determine a steady approach to sedimentation processes due to the diversity of coastal structures and the complexity of the coastal processes. Therefore, using the concept of sediment cell as well as the source and sink determining, reduce the complexity of Hormozgan coasts study. Hence, the uncertainty in the results can be greatly reduced by determining the boundaries of sediment cells and their geomorphologic explanation.

The present research framework is based on the geomorphological inductive analysis research method. The stages of the study were conducted in this way: The first step is library and documentary studies, reviewing existing data and collecting data using field measurement, the second step is computer processing and the third step is the conclusion. The tools used for data collection include field observations, geological map 1: 100,000, topography map 1: 25000 and Landsat5 satellite imagery. Other analyzes are based on data such as wind statistical data, river sedimentation, hydrodynamics (wave rose, tides, high waves, and tsunami), large ports dredging data and sea level.

The coasts of the Hormozgan province are classified according to the combination of two models of Valentin's classification (1952) and geomorphologic classification of Inman and Nordstrom (1971). These beaches include Mountainous beaches, Delta beaches (Inman and Nordstrom) and Submergent beaches (Valentine). Therefore, sediment cells 1 and 2 are located on the Mountainous beaches, sediment cells 3 and 4 are located Submergent beaches, and sediment cells 5 and 6 are located on the Delta beaches. Generally, the sedimentation volume in sediment cells 1 and 2 respectively is 261000 and 174000 m3/yr.And the sediment volume stored in the sinks of these cells respectively is estimated at 102000 and 223000 m3/yr. Sediment cells 3 and 4 are Submergent beaches. Sedimentation volume in sediment cells 3 and 4 respectively is about 10920000 and 1813000 m3/yr., and the sediment volume stored in the sinks of cell 3 respectively is about 57,000 m3/yr. In sediment cell 4, due to the complexity and instability of the bay and estuaries behavior, the stored sediment volume has not been calculated. The sediment pathway direction in sediment cell 3 is from east to west and in sediment cell 4 under the influence of the Hormuz Island is bidirectional. Sediment cells 5 and 6 are located in the eastern plain of Hormuz Strait and are classified as delta beaches. Sedimentation volume in these cells respectively is about 1553000 and 8818000 m3/yr.And the sediment volume stored in the sinks of cells 5 and 6 respectively is about 379000 and 780000 m3/yr. The sediment pathway direction in sediment cell 5 under the influence of alongshore is from south to north and in the sediment cell 6 is from east to west. Sediment budget of subcell 5-1: The values obtained from the estimation subcell 5-1 sources and sinks are included in the sediment budget equation. The summary of the obtained results is shown in Table 1. Table 1: Values of factors in the subcell 5-1 sediment budget (Ports and Maritime Organization, 1396) Residual (thousand  m3/yr.) Entrance littoral drift (thousand  m3/yr.) Changes (thousand  m3/yr.) Sinks (thousand  m3/yr.) Sources (thousand  m3/yr.) 41 21 -26 270 264   As we can see, this sub-cell contains about 41,000 m3/yr. of sediment surplus that is likely to precipitate in spits and deltas existing along the shoreline.

In order to determine the coastal management strategies and policies, the coast should be divided into specific and limited intervals according to dominant dynamic processes and landform characteristics. Thus, after determining the coastal area in a study and collecting required information on the behavior of natural phenomena in this area, the length of the coastline is divided into a series of cells and subcells. The tectonic and sea level rise is one of the key issues that are the basis of long-term changes in the coast. The uplift coasts are one of the most important geomorphologic landforms of the study area. These forms are influenced by the plate tectonics and the oceanic plate of the Oman Sea subduction under the continental crust of the Makren. Over the next 50 years by comparing the coastal uplift (about 100 mm) and sea level rising (24 cm/yr.), the beaches will be exposed to the sea progress. This will have a significant effect on the cell boundaries changes. So that all the parameters that were studied and measured to determine the littoral cell boundaries are affected, and consequently the littoral cell boundaries will also be displaced. The results show that on the Hormozgan province coasts, like the boundaries introduced in international studies, the boundary of sediment cells consists of headlands and estuaries. The sediment produced by the rivers is the main source of sediment in all littoral cells. Just in sediment cell 1, the main source of sediment is the coastal erosion. Sinks identified on the coasts of the Hormozgan province include estuaries, spits, lagoons, and beaches on the one side of small gulfs. This research is based on the international scientific and practical methods used to determine the sediment cell boundaries, sources, and sinks. The difference is that the point of view of geomorphology (considering scale, form, and processes with the holistic approach) used as methods for explaining the problem.

Quantitative evaluation of the relationship between vegetation and environmental factors is an essential tool in the modern researches on vegetation ecology. The establishment of a plant community, changes in canopy cover percentage and plant density are influenced by soil, climatic, geomorphological and biological factors. Studying the above factors causes the distribution, density and variations of vegetation cover and habitat potential. Much of Iran has the arid, semi-arid or extremely arid climate. In most of these areas, vegetation is little and establishment of vegetation in these areas are associated with numerous restrictions. In addition, the distribution and density of vegetation on the land surface was not accidental, but rather the presence of different plant species in one habitat due to environmental factors (climate, soil, topography, etc.), ecological needs of each plant and tolerance range of each species. Relative to the environmental factors important in each habitat. In fact, by studying environmental characteristics using different statistical methods, the causes of plant community distribution are identified, the most important environmental factors affecting community distribution and the habitat's ability to adapt to other communities. Classification techniques are one of the multivariate statistical methods used in ecological knowledge in the last three decades. Ordering reveals the hidden in the collected data and also reduces the volume. Methodology Study area The area under study has been located in the northeast of Semnan province, north of Shahroud city. The study area includes three alluvial fans including Saran, Moghatelan and Hot-Sokhteh.

Impact alluvial fans are always one of the most prominent geomorphologic landforms with new, old, and even fossilized surfaces. Separation of old and new alluvial fans can be done based on indicators such as weathering, morphology, surface of alluvial fans, drainage patterns, color tone in satellite images. Vegetation sampling Field operations were carried out in early June 2019 with the aim of familiarizing with the area, collecting and identifying plants. In fact, at each site (P1 to P6) 1 transect of 200 m and along each transect 8 plots of 8 * 8 m were deployed on Interfluves, Swales, channels, Bar on toe and apex of all three alluvial fans. Therefore, 43 vegetation sampling plots were laid. Then, within each plot, plants were identified and list of plant species, percentage and canopy density of each species were recorded in the plot. Soil sampling In order to investigate physical and chemical characteristics of soil and their effects on the density and type of vegetation on alluvial fans; 48 soil samples from soil depths of 0-20 cm were collected from different landforms of old and young surfaces of alluvial fans, including bars, swales, channels, and interfluves. Also the amount of PH, EC, phosphorus (P), absorbable potassium (K) and sodium (Na), calcium carbonate (CaCO3), Saturation percentage (Sp), water retention capacity in the soil (WHC), soil texture, and total organic carbon (OCT) were measured. Vegetation analysis In this study, based on 13 physical and chemical properties of 44 quadrates, cluster analysis was performed and vegetation classification was performed by using PAST software. Classification of environmental factors and vegetation Multivariate analysis of principal components (PCA) was performed using by PAST software. Principal components analysis was performed on 13 environmental factors including soil texture (sand, silt and clay content), acidity (pH), electrical conductivity (EC), organic matter content, saturation moisture content, soil water retention capacity in the soil, calcium carbonate, phosphorus, Potassium, sodium and percent of gravel or pebbles were determined.

Plant species of study area Overall, 32 families, 44 genuses, and 46 species were identified by field works in study area. classification of Area vegetation Using cluster analysis with Wards method and Euclidean distance index in PAST software showed that 44 plots in the study area belonged to 4 plant communities. Results of Principal Component Analysis (PCA) In order to determine the most important factors affecting the distribution of plant species, Principal Component Analysis (PCA) was performed on the data. Principal component analysis on 13 variables (soil properties) in 44 habitat (landforms) showed that the first, second, third, fourth and fifth axes were 47.66, 38.91, 7.72, 2.33 and 1.4 percentage of variance justifies the vegetation changes.

In the vegetation data analysis of the study area, using cluster analysis, four ecological groups of vegetation were separated which each ecological group represents a unique homogeneous unit of vegetation. Therefore, identification of plant groups and their location is very important in describing the variability of environmental conditions and can be an appropriate model in fitness management. Most of the active and inactive parts of the alluvial fan are located and in the parts where the amount of fine sediment is higher. In fact, soil saturation moisture and soil water retention capacity are the most important environmental limiting factors affecting plant residues in arid and semiarid regions. In the Miami due to chattels grazing, tractor movement to change land use and heavy machinery due to the presence of several factories in the study area, as well as unnecessary harvesting of medicinal and medicinal plants, in some parts of alluvial fans, especially alluvial fans of soil texture. It is being degraded and these are a serious threat to valuable and rare plant species in the region. Keywords: Cluster analysis, Environmental factors, Ordination, Alluvial fan, Landform, Miami.

Channel location changes of the river is an important process in the river ecosystems and is a threat for human activities in flood plains. Exploring the how and why of these changes has an important role in predicting the process of future changes and channel migration order to manage the flood plain. On the other hand, human interventions such as sand removal from river bed, land use changes, river engineering projects, etc. cause changes in the pattern and direction of the river channel. Exploring the how and why of these changes has an important role in predicting the process of future changes and channel migration order to manage the flood plain. Each year, several significant and insignificant floods happen in Lavij River, which has led it face several lateral channel migration. The effects of this migration can be significant in the form of root exposure and Falling trees on canal margins, road demolition, agricultural land, stand bridges, etc.Lavage River basin area is 93 square kilometers of North Alborz independent basin located on the northern slopes of Alborz Range south of the city of Chamestan. This basin has a north-south direction and after leaving the mountainous area and crossing the agricultural lands and forest park Noor to the Caspian Sea. The Lavage Basin is bounded on the west and south by the Glendrud Basin and on the east by the Waz Basin. In this research, the evolution and lateral channel migration of Lavij River has been studied with the Dandrogeomorphology Technique.This study is a combination of field and laboratory methods that include field surveys and sampling, sample preparation and macroscopic measurements. After collecting baseline data from the study area, 4 intervals for field sampling Selected at each interval, were first mapped using river cross-sectional mapping and positioning of river channel geomorphic forms including active canal, abandoned canal, flood plain, point bars and terraces. In this method, the age of the trees in the flood plain, abandoned channels, terraces, point bars, and the location of surfaces in relation to each other are calculated; the lateral channel changes have been Reconstruction from the past until this day. Comparing the hydrology and chronology data of the present trees in different layers show that the channel migration occurred in the reach No 1 1374 and 1375, in the reach No 2 1 in almost at 1345 and 1346, and in the reach No 3 in almost at 1380. In the reach No 4, a significant incision occurred in the river bed and the major channel migration in the flood plain surface was in the left direction of the current. Basic channel migration is mainly related to flows that are less likely to occur, with longer return periods. study of the trees chronology data in the study area showed that the year of migration or abandonment at all intervals was not consistent with large floods with a long return period, but even in floods with a return period of less than 4 years. In the study area out of the 4 intervals studied in three intervals, the diversion of the river channel was caused by flood currents of less than 20 m3 / s,therefore flows with a return period of less than 4 years. But when such currents occur alongside transverse currents, the probability of shear and bank erosion is very high. That is, in subsequent years, larger discharges will manipulate the channel created in these floods until another severe flood occurs and lead to major migration in the stream and channel. In fact, exceptional discharges along with rare floods at the time of occurrence temporarily cause shorter and wider canals because geomorphic processes can respond to severe floods of several decades, river measurements (channel morphometry) will be reflecting stream history. The study of channel migration, with the chronology of alder trees in the study areas, showed that the major floods of the years 1345, 1346, 1374, 1375, 1376 and 1380 have extremely affected channel changes and the age of establishment of alder trees illustrates this.The floods of 1996 and 1997 have been recognized as an important event in the interval changes over the past few decades. These floods have led to the straight and narrowing of the channel (interval 1). These processes deepen the channel and bring the floodplain to a higher level. The geomorphic changes that occur will increase the amount of flow required to exit the channel and extend to the surface of the floodplain .

The study of the spatial scale of river geomorphic units, along with their hydraulic elements, is suitable for assessing the relationship between ecology and river physics. In the present study, the classification of geomorphic units of Taleghan river and the comparison of different reaches of the river has been considered in order to analysis the condition of riparian physical habitats of the river. The results of this research can be applied for processes management of river considering the riparian ecologic situation of the river.

Taleghan river is located between 36°23′and 36°06′ N latitude and 51°10′ to 50°20′ E longitude. In this research, 7 reaches were investigated based on the difference of slope and elevation (Fig. 1). Methodology Recently, new approaches for river management have been developed in the REFORM project (REstoring rivers for effective catchment Management) funded by the European Commission within the FP7. In this project, a set of hydrogeomorphological assessment methods is defined by the stages used to assess the river conditions (Rinaldi et al, 2015 and 2016). The geomorphic unit classification and evaluation system (GUS) integrates these methods and utilizes it to classification, analysis and monitoring the set of geomorphic units at reach scale in the 3 space scale of the macro unit, unit, and subunit (Belletti et al, 2017). In the GUS method, the indices of geomorphic unit density (GUSI-R) and geomorphic unit richness are calculated. The designed sub-indices in GUS metho are the richness sub-indices of bankfull channel geomorphic units (GUSI-RBC), floodplain geomorphic units (GUSI-RFP), density sub-indices of baseflow channel geomorphic units (GUSI-DC), emergent sediment geomorphic units (GUSI-DE), in-channel vegetation geomorphic units (GUSI-DV), riparian zone geomorphic units (GUSI-DF) and floodplain aquatic zones geomorphic units (GUSI-DW). The definition of geomorphic units is based on the 3 levels of broad, basic and detail. The characteristic of macro units and units (in broad and basic level) were calculated using ArcGIS software and remote sensing data by Ultracam 10 cm satellite images. The detailed level was also studied by a combination of field studies and remote sensing.

The total number of geomorphic units and their density in the A and B reach are lower than the probable units in other reaches. At A and B reaches, the lowest area is observed in the "emergent sediment units". In the upstream part of the river, the process of riverbank erosion is dominated, therefore sediment deposition around the bed or across the river channel is much less. The density of biogeomorphic units in the middle channel (C and D) reaches and any opportunity for the creation of cumulative biogeomorphic landforms at the macro scale is limited. In the case of biogeomorphic cumulative landforms establishment, these units are not stable due to the hydraulic stress gradient. Most of the richness of bankfull and floodplain geomorphic units are observed in the D and E reaches. The density of in-channel vegetation unit in F reach is lower than C, D and F reach. The highest rate of the richness of geomorphic units is observed in D, E and F reaches. The width of the river bed in these reaches is greater than A and B reaches. The highest rate of the density of in-channel vegetation unit was observed in the H reach. The number of vegetation islands in this reach is 30, which is greater than all the reaches. Suitable conditions for the creation of biogeomorphic cumulative landforms in this reach is more than other reaches. The aquatic vegetation unit is only visible at C reach.

There is a variety of geomorphic units and physical habitats in the downstream of the river as well as in the midstream compared to the upstream of the river. Although environmental aspects have not been studied in this research, these reaches have a habitat diversity due to decrease of the hydraulic stress gradient and increase of ecological flexibility. Although the mentioned diversity may not be important for macro-fauna and flora because the habitats have a small scale in most cases but they are significant for diatoms, algae, and smaller fauna and flora. The impact of anthropogenic interference, landuse change, and sand removal from the river bed, especially in downstream of the Taleqan River, reduced the density of the floodplain unit, and this has a negative impact on the formation of sedimentary islands and riparian vegetation (F reach). Anthropogenic factors have a negative impact on riverbed deposition and disturbed natural evolution of riparian and in-channel vegetation. Excessive deposition by sand removal destroys opportunity windows for plant anchorages and, in some cases, buries in channel physical habitats.

Floods are one of the most destructive and most frequent natural disasters. In this regard, flood risk zoning is one of the most effective methods for managing and mitigating the effects of floods. In this study, the spatial and risk assessment of flood events at the surface of Ghorichai watershed in Ardabil province was investigated. In this regard, 10 measures affecting the flood event were applied. These criteria include elevation, slope, slope orientation, convexity, geological formations, drainage density, curve number (CN), waterway distance, land use and vegetation. In the meantime, the ground slope variable with a weight of 0.26 (excluding network analysis process model) plays a major role in identifying high risk flood zones. Two fuzzy logic models and a network analysis process (GIS) were used to integrate and overlap the aforementioned subject layers in order to prepare a flood risk zoning map. Flood hazard zoning of the Ghorichai watershed showed that about 18% of the studied watershed area was located in high and very high risk classes. Flood risk in the basins of the main valleys and downstream lands of the study basin due to Geomorphometric reasons such as formation and development of flood plains, low relative elevation, concave terrain, and rapid upstream runoff of the event potential. It is high. In addition, relocation of residential areas downstream of the basin has increased the risk of flooding in these areas. Flooding is called the dangerous increase in the flow of a river or a flood. This phenomenon has a long history in human history and is one of the most damaging and destructive natural events. Old towns are usually formed alongside rivers due to easier access to water; they are therefore affected by floods, causing casualties. Floods occur when water flows out of rivers, streams and canals, in other words leaving its natural channel. We see an event when the canal or river is completely filled with water and enters the floodplains and areas where people live. In the present study, the risk of flooding in the Ghorichai watershed is investigated. Due to the large extent of the semi-arid climate and the presence of numerous settlements in the region, it is important to assess the importance of flood risk assessment and zoning in the Ghorichai catchment area. This is especially important in the presence of large human settlements, extensive agricultural lands and conservation of water and soil resources. Therefore, flood risk zoning at the basin level of the study is one of the essential steps in the management of flood risk mitigation and management measures.

The present study investigates the risk of flooding in the Ghorichai watershed. This basin is located in Ardebil province within the administrative districts of Nair, Ardebil and Kosar. Much of this basin is located in the Nair area. The study area is located at 48 degrees 2 minutes to 48 degrees 31 minutes east longitude and 37 degrees 46 minutes 38 degrees 11 minutes north latitude in mathematical position. The basin has an area of about 824 km2 and an area of about 240 km. In this study, the following data and tools were used to analyzed flood risk in the Ghorichai catchment: 1: 50000 area topographic maps, 1 scale geological maps : 100000 including Ardebil and Givi Sheets, 1: 250000 Scale Soil Map, Digital Elevation Model (DEM) for ALOS - PALSAR Satellite Area with 12.5 m Resolution, Sentinel2 Satellite Images with 10 m spatial resolution and meteorological and climatic data including Ardabil synoptic station data and rain gauge station data located within the watershed. Two models of fuzzy logic and network analysis process (ANP) in the framework of Geographic Information System (GIS) were used to model flood risk in the Ghorichai catchment area.

The final layer resulting from the composition and overlap of the subject layer indicates the potential for flood risk at the Ghorichai watershed. The resulting map was classified into five classes of very low, low, medium, high and very high flood risk. According to the flood risk zoning map of the Ghorichai catchment, it can be stated that approximately 49 km2 of the catchment area is in a very high flood risk class, covering about 5.9% of the catchment area. In addition, more than 101 km2 or about 12% of the study area is in high risk class. Most of these high-risk areas are adjacent to either side of the basin's main waterways or floodplains adjacent to them. This can be attributed to a number of reasons, such as the smoothness or slowness of these areas (and thus the possibility of easier spreading and spreading floods), the existence of a valley extended by the flood plain below it. , Counts the crossing of the Ghorichai River through these zones and the low altitude of these zones.

In this study, in order to map the flood hazard in the Ghorichai catchment area, 10 factors influencing flood event were applied. These criteria can be divided into three main categories: geomorphological criteria including altitude, slope, slope direction, ground convexity and geological formations; hydrological criteria including drainage density variables, curve number (CN) and distance from the waterway. And land cover criteria including land use and vegetation (NDVI). To integrate and overlap the research thematic layers with the aim of mapping flood risk zoning at the Ghorichai watershed, we use two models of fuzzy logic and ANP in the form of GIS. There was action. In this regard, all subject layers affecting flood occurrence were applied with different fuzzy functions, in the range between 0 and 1 standard and having the same units. Then all relevant subject layers were combined with the weights obtained from the ANP model. Flood hazard zoning of the Quriichai watershed showed that about 18% of the studied watershed area was located in high and very high risk classes.

Qeshm Island is located in the southeastern Zagros salt domes and salt domes in the Persian Gulf and near the Strait of Hormuz. Relative to the tectonic structure on the Arabian-Iranian border, the region has caused the tectonic dynamics of this region. In addition, salt tectonics has had a significant impact on the morphology of the folds of the island. In the present study, for the purpose of analyzing and recognizing the tectonic effects on morphotectonics of Anticline, 4 Anticline Salakh (in the west), Kavarzin (in the north), Souza (center and south), and Giahdan (in the east) of Qeshm Island, were selected based on geomorphologic and Morphotectonics has been investigated. Geologically, the outcropped formations in Qeshm Island include the evaporative series of Hormuz as salt domes or diopters and marl, sandstone and limestone deposits. The oldest known earthquake in the area near Qeshm is 1336 AD and then the earthquake of 1361 AD with a magnitude of 5.3 magnitudes, the destruction of which was reported on Qeshm Island.

The data used in this research include geological maps of the area in order to identify faults and altitudes, digital elevation data (30m DEM of the area) for preparing the location map and information map Google Earth images to measure indices and evaluate tectonic evidence of the region. With the help of the data mentioned and the GIS and Google Earth software, the morphotectonic indices of the Anticline, which include six indices, have been calculated.Also, for better visual perception, the topographic view of the study area, the presence of valleys and plains leading to the Gulf Coast, and the role of faults and lines in the prominences, the longitudinal profile of each of the 4 Anticline studied with a 3D model Each range of Anticline was drawn. To do this, the Global Mapper software has been used.

In Traingular facets surfaces used for the two Anticline of Salakh and Kavarzin, the two parameters, the mean of the area and the length of the base were higher in the kavarzin Anticline, due to the presence and superiority of the limestone in this alder, which has not been able to erosion The range of these rocks (east and south east of the anticline) is much affected, but for the average slope, which is more than 3 percent (kavarzin 17 salakh 20), there is more of the faults and parallel to the rise and rise of the earth In this area, the existence of Qeshm salt dome in the alder area and west of it is more tectonic activity and in Also confirms that effective outcome on the slope. The cause of the highest erosion in the souza Anticline is due to the loose formations (Marl and Gyps) and the presence of low faults in this area and the reason of the least erosion in the kavarzin altogether, on the contrary, is the presence of many faults and the existence of a hard limestone formation in the range To make In the case of the parameter O, which is related to the width of the valley output, the following points can be made: Any amount of this parameter is less, indicating tectonic activity and less erosion. Accordingly, the highest activity level respectively are related to the Anticline kavarzin (100), salakh (106), Giahdan (146) and Sousa (190). In the study of the index Stream Spacing ratio, the higher the R value, the more tectonic activity is observed. In areas with higher erosion, the waterways are wider and the main drains in the sub-basins are more spacious. However, in areas where tectonics are active, young and new areas with less erosion, and parallel and near-parallel drains in the sub-basins. Based on this, the highest tectonic activity among the Anticlines is based Stream Spacing ratio index Anticline kavarzin (3.62), Salakh (2.76), souza (2.26), and Giahdan (2.13). The results show that, based on each of the six indices, each of the 4 Anticline of Salakh, kavarzin, Souza and Giahdan is active in terms of tectonics, and it is important that wherever the density of the fault is greater, the rising of the snowfall is overcome, such as Anticline Salah and kavarzin, and Wherever the density of the fault is reduced, the erosion of the plain creates a uniformity, such as souza and Giahdan. Finally, on the basis of each of the 6 indicators, two Anticline Salakh and kavarzin are tectonically active in terms of tectonic activity and the dangers of Giahdan and Souza due to their tropical and erosion.

Land subsidence caused by excessive extraction of groundwater resources is a worldwide problem in many arid or semiarid countries such as Iran, which depend on groundwater resources. One of the most important consequences of groundwater table drawdown is profound changes in the soil physical properties due to soil compaction associated with land subsidence that has critical role in the acceleration of desertification and intensification of water erosion because of lack of water infiltration into soil. As over time, the over-exploitation of groundwater resources may lead to a declining water table and the associated enhanced loss of water within soil layers. This in turn reduces soil porosity volume and causes soil inelastic compaction in the aquifer system. These conditions promote land subsidence and result in horizontal land deformation and the associated soil compaction. Land subsidence is due to compaction of clay beds within the aquifer systems. When groundwater level is considerably high, the gravel and sands are buoyant. As water table reduces resulting from over extraction, the rate of coarse fractions buoyancy is decreased and therefore additional weight from the gravel and sand stimulates descending pressure on clay beds that are between the sand and gravel strata from which water has been extracted. When the water held in the clays can no longer withstand the pressure from the increased weight of the gravel and sands above, the clays are compressed and water is squeezed from them. These clays will never absorb again the water that has been expelled from them. The aim of this study was to examine how fluctuation in groundwater level drawdown and subsequently land horizontal deformation associated with land subsidence can impact on soil erodibility level via changes in soil physical and biochemical attributes.

The study sites were located in Neyshabur County, Khorasan-Razavi province, northeastern Iran. Statistic of the piezometric wells taken from Regional Water Organization of Khorasan-Razavi province demonstrate that the selected sites exhibit statistically significant differences (P < 0.05) in the rates of groundwater level drawdown. At each the site 8 earth fissures were selected. Soil samples were collected from 20 replicate 1 × 1‐m quadrats. Soil physical properties are recognizes as indices of soil compaction i.e., bulk density, total soil porosity, macro pores volume, micro pores volume, soil moisture, and infiltration capacity also the associated some biochemical attributes were measured.

The statistical results of the measured indicators of soil compaction illustrated the appearance of different degrees of soil erodibility along fluctuation of the groundwater level drawdown. It is noteworthy that different soil compaction levels associated with land subsidence were considered as an index for assessing erodibility level. The bulk density significantly (P < 0.05) increased in the site A that had the greatest value of the drawdown compared with the site B with decreased values of the drawdown. Macro porosity volume significantly decreased in the site A that had the greatest value of the drawdown compared with the site B. Microporosity volume and soil moisture significantly increased in the site A with the light rates of the drawdown in comparison with site B. Also, infiltration capacity significantly (P < 0.05) increased in the sites that had light drawdown of groundwater level compared with the deep drawdown. These findings illustrated the impacts of land subsidence related to fluctuations of groundwater level drawdown in the occurrence of different rates of soil erodibility as changes in the level of soil compaction. Although, there is no dedicated study regarding impacts of fluctuations in groundwater level drawdown on the soil compaction degrees (as an index of soil erodibility level), other studied in relation to soil compaction resulting from agricultural field traffic can confirm these findings. Our findings is in agreement with the mentioned studies that soil compaction can strongly affects the level of total porosity and volume of macro and micro porosity within soil profile. Further, the statistical results of the biochemical indicators from soils belonging to earth fissures in the sites with different rates of the drawdown explain that how changes in soil compaction degree due to variation in the rate of groundwater level drawdown can affect soil productivity indicators. Microbial biomass carbon and microbial biomass nitrogen showed the lowest values in the deep groundwater level (site A), demonstrating the critical impacts of sever soil compaction resulting from deep of groundwater level on reducing microbial activities and microbial nitrogen immobilization. There is a significant relationship between the continuous drawdown of groundwater level with soil erodibility indicators related to soil compaction and biochemical attributes. This means that total porosity and macro porosity volume decreased as groundwater level has decreased more and more.

Fluctuation in groundwater level over time can critically affect soil erodibility level via increasing soil compaction. At the site A that had more severe drawdown of groundwater level in comparison with the site B with the decreased rates of the drawdown during different years, it was seen that total porosity, macro porosity volume, and infiltration capacity significantly decreased, causing reduction in microbial activity level as significant decreasing MBC and MBN. The findings explain the critical role of land subsidence related to groundwater level drawdown and the associated fluctuation in increasing erodibility level of dryland soils that are vulnerable to environmental harshness.

Numerous Classification Schemes According to Geomorphic River from the late Nineteenth Century has been done that reflects the diversity of Environmental Situations. The aim of this study is investigate in Vulnerable Areas this Kashkan River for a reach length of 5000 m using Channel Stream Classification in level one and two as Rosgen. In Level I, Classification using Satellite images and field visits and investigation Maps and at level II, for morphological parameters of the digital map with scale of 1:150, Rider HEC-geo-RAS and HEC-RAS Model Measured and calculated parameters required. The results show that interval between the primary arterial patterns of DA6, the center of a single branch pattern of A4 And the final section of the D3 range and is also the arterial pattern that the flow rate increases sediment and changes in flow designing has very high sensitivity and Most of the sediment fed with high sensitivity and caused severe morphological changes that are unsustainable pattern of River Reorganization measures in this sector must be carried out according to morphological variables.  Rivers influenced by different variables in terms of size, shape, direction and pattern change. Rivers based on historical factors, tectonics, lithology, climatic and human divided into types is dumped. Several factors including time, discharge, sediment load and on the level its influence and for digging river, sedimentation, changing patterns of deformation and conduit, responds to it. Rivers flow conditions or with respect to their geometrical characteristics that are natural or synthetic (human intervention) is applied sensitivity and react. By knowing the rules governing the river, we can recognize and change its behavior, it is qualitatively and quantitatively predicted. Kashkan watershed with area of 9300 km2 is located in southwest of Iran in longitude of 47° 48' E and latitude of 33° 43' N. Annual mean discharge of this watershed at outlet point is 33 m3/s with specific discharge of 9 lit/s.km2. Annual mean precipitation of this watershed is 550 mm. The maximum precipitation in the watershed is occur in February, whereas the maximum discharge of this river has occur by two months lags in April. This denotes to dominance of snowmelt runoff in river discharge. From viewpoints of geomorphologic indices, the streams of this watershed has low potential of erosivity and low tectonic activity.  

In this study Classification as Rosgen in level II, First, scrolling along the study area, part the Section thre upstream, intermediate and downstream the interval was set up. The maximum instantaneous flow rate statistics related to 24-year period Kashkan Bridge station is used to determine the flood return periods. The cross sectional geometry data and topographic maps of 1: 150 on the river Satellite images to determine the grain size distributions and calculating the Manning roughness coefficient As well as field visits were made to increase the accuracy of information. The following software needed to evaluate the river was used: Google Earth software to identify the exact area, HEC-RAS hydraulic calculation software for morphological parameters and the extension HEC-geo-RAS to transfer data from GIS to RAS and vice versa. Easy fit software to perform frequency analysis on data up to discharge and Finally Rosgen model for morphological classification channel is used.  

Determine of river plans in level I, Rosgen classification that based on the appearance of the river, the study Section was divided into three parts. With the help of satellite images and field visits to the site, and Google Earth images were obtained necessary information about the type of Plan Rivers. In the first part of the arterial channel model, in the second place and the third part of the rivers of arterial was found. In addition, field visits it was found that the wide and shallow channel in the first and third sectors, and in the second part narrow and relatively deep. Channel slope is calculated using longitudinal profile. To determine the required parameters for the level II, by extracting the geometric characteristics of the cross sections in different parts and Run of the hydraulic models HEC-RAS All parameters required Including Width to depth ratio, The ratio of hole, The curvature coefficient, Channel slope and Bedding materials for classification and identification of conduit geometry, respectively. After calculating the required parameters of this section, the results they were averaged and based on the results of River pattern was determined in accordance with the Rosgen classification.  According to the results, it was found that interval between the primary arterial patterns of DA6, the center of a single branch pattern of A4 And the final section of the D3 range. The last two sections of river sediments is high in nutrition and the potential erosion is also very high and the potential for recovery is poor in these sectors River that these sectors are vulnerable areas range. The final section of stream rate increases sediment and changes in flow designing has very high sensitivity and Most of the sediment fed with high sensitivity and caused severe morphological changes that are unsustainable pattern of River Reorganization measures in this sector must be carried out according to morphological variables.

In recent years, with the growing population, industrial development of groundwater resources has more than doubled, with groundwater levels continuing to fall and eventually reaching a point where there will be no more water to extract. Therefore identifying these resources, making optimum use of them means a permanent and permanent harvest of this natural gods wealth. 

In this first phase, field studies and data collection were done. Wells map was prepared first and then effective parameters were identified: elevation layer, slope, slope direction, surface curvature, topographic moisture index, land use, soil, geology, river distance, drainage density, fault distance, fault density specified. And their plan was made. Satellite images of ENVI and eCognation software were used for mapping the land and the images were classified with basic pixel and object crosshairs and fuzzy logic and artificial neural network methods were used. Based on fuzzy logic, baseline maps are first ranked based on their impact and importance on groundwater resource potential, and then determined using a fuzzy method for each specific class rating factor. In the neural network method, these agents, along with a number of wells, enter the network as the input layer. In this way, the pattern is trained by the network between the input parameters (network input) and the areas where potential water resources exist (network output), then for The input parameters of the catchment to the trained neural network are predicted corresponding outputs which are potential areas of groundwater potential. Then the results of both models are tested and finally by comparing the results of the neural network model with the fuzzy logic model an appropriate method for groundwater resource potential in the catchment is obtained and the most important factors in resource potential in the area are identified.

Evaluation of effective layers in the potential of groundwater resources: The results of the elevation factor showed that the highest percentage (33%) of the area with high potential is located at an altitude of 1700-2000 m, which is the average altitude of the region, and the results of the slope factor study show that the highest percentage of high and medium potential areas is on the slope 0-1 is located and the highest percentage of areas with low potential is on the slope of 60- 173 and the highest percentage of areas with high and medium potential to the northeast direction and the highest percentage of areas with low potential is in the southern direction. The results of the study of lithology class (formation) show that the highest percentage of areas with high and medium potential. The weak are in the class (reserves of old and new mountaineering terraces and conifers). And the highest percentage of soil in the region is in areas with high potential and weak in the group (rocky / intulse outlets) and the highest percentage of areas with medium potential in the group (rocky direction outlets / input solo).The results of the study of the distance from the river show that the highest percentage of areas with high potential is located in the nearest distance from the river 200 meters and the highest percentage of areas with medium and weak potential is in a range far from the river. The results of the fault gap survey show that the highest percentage of areas with high and medium potential is located in the closest distance from the fault (0-0.032) and the highest percentage of areas with low potential (0.115-0.170). Precipitation and temperature estimates show that the highest percentage of areas with high, medium and weak potential is in the range of 756-844 and the highest percentage of areas with high, medium and weak potential is in the range of 13-15. And the highest percentage of areas with high and low potential is in the use of medium rangeland and the highest percentage of areas with medium potential is in forest use. The results of the groundwater map show that the highest percentage (36.85) of areas with high potential is in the class of 10.12-6.74. Evaluation of the classification maps of the results shows that the accuracy of kappa in object-class classification is 96% and in base pixel 85%. Neural network results also show that about 39% of the area has high potential of groundwater, while fuzzy logic map shows about 87% of the area with low potential.

Using the descriptions needed for basic pixels and taps, we can provide you with faster access to various sites, loops, content and technical and engineering information in a variety of areas, in the entertainment and leisure markets. Read yourself below. From this research it can be concluded that your neural network can control the energy potential of water Underground is more practical than the appropriate fuzzy logic method because its results are closer to the ground. Factors such as slope factor can be considered as an important factor in the potential of groundwater resources because of the high percentage of potential areas in the range of 0-10%.

From prospective of morphology, At first glance costal geomorphology is chaotic, intricate and complex. Geometrically fractal, estuaries have an internal order, and this order is so precise that the slightest irregularity can be obtained at any scale. In this study, fractal dimension in north of Persian Gulf shore for marine estuaries (Mouse’s estuary within the borders of Iran and Abd Allah’s estuary common border Kuwait and Iraq) and River meandering (Arvand roud River and Dalaki River in Iran North of Persian gulf) calculated by box-counting method. We used Arc GIS software and Landsat 8 of satellite image May 2016. In following, we make 10 partition scales from 100 KM to 100 M in each estuary and river of images. Our goal in this research is to investigate the pattern of order in the geometric geomorphological form of costal estuaries and Rivers meandering in the north of the Persian Gulf from a fractal point of view and its relationship to processes (geology, climate, hydraulic, etc.). Results show irregularity and disarrays in Mouse’s estuary by unit dimension fractal 1.5 to compare with Abd Allah’s estuary in Kuwait and Iraq by unit dimension fractal 0.67. Dimension fractal Arvand Roud River and Dalaki River are 0.53 and 0.46 respectively. In general, in this study, it can be concluded that geomorphological phenomena of fractal, the marine estuaries in the north of the Persian Gulf (especially Musa estuary) have entered the stage of turbulent edge. Also, on the 100-meter scale, fractal dimension of the Arvand Roud River is more turbulence than the Dalaki River. Geomorphological phenomena of estuaries and meanders at a scale of 100 meters are turbulent which shows the effectiveness of coastal and marine processes such as: tidal, marine waves, water erosion and loose sediments in estuaries and meanders in North of Persian gulf costal.

The knowledge of geomorphology, which is based on the knowledge of forms (phenomena) and processes (forces), is quite complex, altering and difficult to predict. Costal and rivers are controlled by hydraulics, wind, tectonic, physical, chemical, geological, etc. Also Due to the large role of parameters in them, they usually show unknown and chaotic behavior processes. Fractal geometry provides a mathematical model for some of the more complex shapes and components in nature, such as beaches, hills, tree bark, clouds, and so on. The fractal dimension is a useful feature for examining the texture of components, classified shapes, and graphical analysis in some disciplines. Every phenomenon in the world has order. Although there may be irregularities, there is an order at the heart of each irregularity that can be accessed with special tools and methods and find the pattern and order in it. Self-similarity is one of the essential attributes of fractal in nature that may be quantified by fractal dimension. Our goal in this research is to investigate the pattern of order in the geometric geomorphological form of costal estuaries and Rivers meandering in the north of the Persian Gulf from a fractal point of view and its relationship to processes (geology, marine, geomorphology, etc.).

In this study, in order to achieve the fractal dimension of coastal and River tributaries in the northern part of the Persian Gulf, the Landsat satellite image of May 8, 2016 was used. Arc GIS software was used to create Husdoroff networks. Also the Fishnet option was used to create square networks or houses on the area. The following relationship was used to obtain the fractal dimension of the geomorphological phenomena of River and sea estuaries in the Persian Gulf: Nn=C/(R_n^D ) Nn= is the number of variables available for a phenomenon, C= is the constant coefficient, Rn= is the dimension of a special linear coefficient, and D= is the fractal dimension.

Khowr Mousa These results indicate the presence of three stages of foreground, threshold and threshold stage. The threshold and anomaly stages start from scales of 20 and 1.5 * 1, respectively, with a fractional fraction of 0.65 and 0.46. The total fractal regression for all three comprehensive backgrounds, thresholds, and anomalies is about 1.5. Also Khowr Mousa is 24% bigger than Khowr Abdullah. Khowr Abdullah Khor Abdullah is located in Kuwait and Iraq. According to Abdullah, the threshold and anomaly communities on scales 5 and 1.5 * 1 begin with a fractional fraction of 0.76 and 0.43, respectively. The total fractal for the whole population includes, foreground, threshold and anomaly of about 0.677. Dalaki River At the Dalaki River, the Astana and Anomaly communities begin at scales of 5 and 1.5 * 1 with a fractional fraction of 0.41 and 0.6, respectively. The overall fractal dimension of the Dalaki River is 0.46. Arvand Roud River The Arvand River has three main communities or stages, the anomaly of which is very small, and the background community and its threshold are endurance. The overall fractal dimension of the Arvand River is 0.5305.

The study's findings show that Mousa's marine estuary with a total fractal size of 1.5 is more disturbing than Abdullah's marine estuary with a fractal size of 0.67, which could indicate that Abdullah's marine estuary is younger than Musa's estuary. Conclusion this study shows that the estuaries north of the Persian Gulf are controlled by the operation of water power processes such as tidal, waves and sediment erosion and Tectonic forces have no role in creating and controlling estuaries directly. In general, Khor Mousa tends to be more chaotic than Khor Abdullah and Arvand roud River meanders desire to be more chaotic than Dalaki River from point of wives fractal dimension. Geometrically fractal, rivers controlled by costal and marine process and erosion sediment.

Assessing the impacts of climatic and land use changes on rates of soil erosion by water is the objective of many national and international research projects (e.g., Van Oost et al., 2000 Nearing., 2001 Vanacker et al., 2003 Chaplot et al., 2005). However, over the last decades, most of the related studies have mainly focused on sheet and rill erosion processes operating at the plot scale. Field-based evidence suggests that sheet and rill erosion as measured on runoff plots are not realistic indicators of total catchment erosion nor do they indicate satisfactorily the redistribution of eroded soil within a field. It is through gully erosion that a large fraction of soil eroded within a field or catchment is redistributed and delivered to water courses. Indeed, most sediment produced by interrill and rill erosion in uplands is often deposited at the foot of hill slopes or in depressions within the landscape and therefore does not reach the river channel. Hence, other sediment-generating processes in catchments such as gully or channel erosion must play an important role in the production of sediments which are transported by rivers and which cause reservoir infilling. Gully erosion is defined as the erosion process whereby runoff water accumulates and often recurs in narrow channels and, over short periods, removes the soil from this narrow area to considerable depths ( Poesen, 2003). Maragheh catchment is a sub-catchments of the Mazlaghan river in Markazy Province due to loose alluvial deposits, sparse vegetation and topographic conditions are severely affected by gully erosion. This penomena not only caused the loss of soil and degradation of agricultural and pasture land but also aggravated offsite effects of water erosion (e.g. flooding, pollution) with transferring runoff and sediment from uplands to valley bottoms and permanent channels. This research has been performed to investigate effective factors on gully erosion and designing gully erosion susceptibility zonation map in Maragheh catchment by using Fuzzy Multi- attribute Decision Making. Study area: Maragheh catchment, covering about 8892 ha, is located 70 Km away from west Saveh between 35˚ 19' and 35˚ 00' latitude North and between 49˚ 41' and 35˚ 00' longitude East. The study area is situated at an altitude of 1608 to 2987 meters from sea level and has a cold semi-arid climate.

In this study, the factors of litology, slope, slope aspect, elevation, distance from road, distance from river, land use, soil, precipitation and land suitability were studied for zoning of gully erosion susceptibility. These factors were obtained by using topographic maps (scale 1:25000), geologic map (scale 1:100000), aerial photographs (scale 1: 40000), IRS image (2003), data rain gauge stations, results of laboratory analysis of soil samples, and GPS tool was also used to record field observation. For production and analysis of maps, we have used software Ilwis 3.3 and ArcGIS 9.3. In the current research, zoning of gully erosion susceptibility has been performed by using Fuzzy Multi Attribute Decision Making via Maximum-Minimum operator. In this method, decision making is done in two steps. The first step, the weights of classes of effective factors was computed by way of Frequency Ratio and its normalization. After that membership functions were defined for each class of various factors. The second step, weight of each effective factor was obtained through Analytical Hierarchy Process (AHP). Then, weights obtained through AHP were used in determination of that membership functions on gully erosion. Determination of membership functions and fuzzy analysis were performed by using the software Matlab7.1. Then, output of software computed susceptibility for each pixcel in case study map transformed to ILWIS software environment and gully erosion susceptibility zonation map was made by using fuzzy Triangular and Gaussian membership function.

The results of this study showed that very high susceptibility areas were affected by litology of loose alluvial sediments of Quaternary (Qt1), soil of sandy loam or sandy clay loam, land type Plateaus and Upper Terraces, land use of poor range as the main factors. Also, this areas were affected by other factors such as slope 15-30% , maximum daily rainfall with return of two years 23/7- 26/4mm, distance from rivers 0-200m, slope aspect of the west and south and altitude of 2000-2400m.

In this research, gully erosion susceptibility zoning of maps were obtained in four classes by using Fuzzy Multi Attribute Decision Making (MADM) and via the Maximum-Minimum operator composition. Index Quality Sum shows that type function has no much effect on results of zoning. Solving problems via Fuzzy Multi Attribute Decision Making were done in two stages. In the first step, membership function was defined for each of the classes of factors by normalized Frequency Ratio. In the second step, priority of the factors assigned by using AHP model and then membership function was determined for the factors based on AHP model. Therefore, this method has great capability of preparing gully erosion susceptibility map zonation. As in Maximum operator numbers are trending toward zero, therefore a greater numbers of pixels are locating in very sensitivity class to gully erosion. For this reason, this operator has very little sensitivity in zoning. In Minimum operator, numbers are trending toward one. Therefore, a greater number of pixels are locating in low sensitivity class to gully erosion and has low sensitivity in zoning. In this study, for adjusting of very high sensitivity of Minimum operator and low accuracy of Maximum operator, we were used the Maximum- Minimum operator composition.

Flood is a disaster that causes a lot of economic damages to farmlands, forests, gas and power transmission lines, roads, engineering structures and buildings. This study has attempted to analyze the role of hydrogeomorphic indices in flood sensitivity of Aland Chai Basin in the northwest of Iran. To achieve this aim, the study area was first divided into 15 sub-basins based on topographic and drainage characteristics using a digital elevation model (DEM) with 12.5m spatial resolution. Then, Hydrogeomorphic parameters of sub-basins have been studied from three aspects of drainage network characteristics (Such as Stream order, Streams number, Streams length, Stream frequency, Bifurcation ratio, Length of overland flow, Drainage density, Drainage texture, Texture ratio, Infiltration Number, Constant of channel maintenance, and Rho Coefficient), shape characteristics (Including Basin area, Compactness coefficient, Circulatory ratio, Elongation ratio, Form factor, and Shape Factor) and relief Properties (Relief, Relief ratio, Ruggedness number, and Gradient). Hydrogeomorphic analysis plays an important role in the analysis of hydrological behavior of the basins, especially in basins that lack information.

Aland Chai basin is located between 38, 30´ and 38, 48´ latitude and between 44, 15´ and 45, 01 longitude in the north of the West Azerbaijan province, Iran. This basin has an area of 1147.30 km2 and it is situated in the north-western part of Iran. Basin elevation variations are from 1093m in the Aland Chai River bed to 3638m above sea level in the Avrin Mountain. The main river of this basin is Aland Chai, which is one of the most important rivers of Khoy city. This basin is one of the sub basins of the Aras River basin, which surface water flows into the Aras River after joining the Qotour River. MACBETH Multi-Criteria Decision Analysis Model was used to weight the parameters and the weighting of the parameters was performed in M- MACBETH software. Bana e Costa, Vansnick, and De Corte firstly proposed MACBETH method in 1990s. The MACBETH method (Measuring Attractiveness through a Categorical Based Evaluation Technique) is based on the additive value model and aims to support interactive learning about the evaluation problem and the elaboration of recommendations to prioritize and select options in individual or group decision making processes. It helps to rank the alternatives based on aggregated value of relative weighted attractiveness of alternatives under the decision criteria. MACBETH method uses 7‐semantic scale (No, very weak, weak, moderate, strong, very strong, and extreme), which is an ordinal scale.

In the first step, the information of each sub-basin was obtained based on 22 hydrogeomorphic parameters from three aspects of drainage network characteristics, shape characteristics and relief Properties in ArcGIS software. These parameters were prepared using the geomorphological laws of Horton, Schumm, and Strahler. In the next step, all necessary weights were calculated for factors and Sub-basins using MACBETH method. The weighting results showed that among the characteristics of the drainage network four parameters of drainage texture, texture ratio, drainage density and bifurcation ratio with coefficients of 16.96, 13.84, 13.49 and 12.46 percent and three parameters, area, compactness coefficient, and Circulatory ratio with coefficients of 29.63, 27.78 and 20.37 percent among the shape parameters respectively, and two parameters of relief and slope with coefficients of 43.75 and 31.25 percent among the relief Properties were the most important parameters. On the other hand, parameters of Rho Coefficient, Shape Factor, Constant of channel maintenance, and Infiltration Number with coefficients of 0.35, 1.85, 2.42, and 3.11 had the least weight.

Floods usually start abruptly and cause irreparable damage in a short period of time. In this study, an attempt was investigated to analyze the role of hydrogeomorphic indices in flood sensitivity of Aland Chai Basin. Based on the effective parameters, flood occurrence inside of Aland Chai basin could be separated into 5 distinguished classes, from very high to very low flood susceptibility. Sub-basins ranking in terms of flood risk sensitivity based on final weights obtained from MACBETH method showed that sub-basins 1, 2, and 3 have the highest ranking and have very high sensitivity to flooding. These sub-basins comprise 286.67 km2 (24.98%) of basin area. Sub-basins 4, 9, 11, and 15 are also highly susceptible to flooding. Also sub-basins 6 and 13 have very low susceptibility toward flood occurrence. In total, about 45% of the study area has high flood sensitivity. Therefore, according to the results of the study, it is necessary to take protective measures such as watershed planning and dam construction in the sub-basins that are highly sensitive to prevent flooding or reduce potential damages in case of flooding.

Karst is a set of geological processes and phenomena resulting from the dissolution of rocks . It is characterized by forming’s and Openings, erosion of formations and conditions of the stones, a specific type of water circulation , a certain type of local topography and the special regime of drainage network. Karst outcomes usually categorized as surface, subsurface and bathetic or internal complications.formation of Karsty phenomena such as karst pits, caves, Pole, graik and great fountains are As a result of secondary porosity.( Floria, 2005) Karst sinkholes are known as a karst erosion landforms and a proper criterion to identify Environment conditions in different periods. (pike,2011) Given the importance of Karst sinkholes, identifying and mapping distribution of karst sinkholes and their characteristics of forms are the needings of the Environmental science and geomorphology.( Van.Beynen ,,2011) Landforms are representing the processes that affect the Earth surface in the past and present and provide important informations about The characteristics and potentials of the Earth.( Bates,1987) quantitative and numerical geomorphology studies, spatial and statistical features and the correlation of spot features. also the basic principles that Geomorphomety emphasizes on that is the relationship between the form of roughness and it’s numerical parameters for explaining Processes that are involved in the formation and evolution of landforms. Kermanshah plain with an area of 5/739 km2 is located on the west side between 34 ° and 8 minutes and 32 seconds to 34° and 33 minutes and 52 seconds of north latitude and 46 degrees 22 minutes and 54 seconds to 47 degrees 00 minutes 31 seconds of East longitude from the Greenwich meridian and an average height of 1410 meters above sea level.

The basis of the identification and classification of landforms is based on Geomorphomety .Geomorphomety is about the quantity of the primary elements of morphology of the land such as slope, Slope orientation, height and relative height difference between elements, the elements relative location to each other, the condition of drainage network and Convexity or concavity of the elements.(Dehn,2001) Input data in the Geomorphomety studies is the digital model of height in Raster form and with square cells that In some cases the digital model of Earth surface could be replaced with it.( Mull,2002) In this research in order to identify the quantitative characteristics of the sinkholes in the region of Kermanshah Plain Geomorphomety indices including second grade derivatives of RTP index , indices of curvaturas parameters and finally sinkholes clustering are used. Important Curvaturas parameters including curved slope parameters (the amount of tilt in all directions), curvature profiles (at all levels) and the curvature of the plan (at all levels). Calculation of all types of curvature in digital model of raster elevation is pixel by pixel and for each cell a quartic poly-Tamyal equation is used (Equation 1 and 2)(Bishop,2000): 1) Z=Ax2y2 +Bx2y+Cxy2+Dx2+Ey2+Fxy+Hy+1 2) (SD – min D) / (max D-min D) To extract geo-morpho-metric indicators of Kermanshah Plain of digital elevation model with a resolution of 10 m, 1: 25,000 Topographic maps of mapping organization prepared and used for Geomorphometric analyzes .in order to evaluate the quantitatively landforms formation 55 units (sinkholes) were identified. Input data In the first phase are slope layer, sinkholes layer and DEM, which after entering each layer to zonal statistic as table command tables obtained. After extraction of Geomorphomety indices, average values and The maximum and minimum for each class, landforms obtained. Finally cluster analysis and output maps obtained from average data.

Kermanshah plain with elongation morphology, along the North - South, is among a collection of mountain and is limited from the north side to praw-bistoon mountains and from the south to White Mountains. In this region There are various forms of karst area from different landscapes such as sinkholes with enormous distribution. In order to existance of superelevation praw (bistoon and white mountains) in northern and southern regions of Kermanshah Plain, sinkholes affected fold and thrust belt, faults and breakage impact . based on the results we've achieved Sinkholes formations are simple, compound and complex.the role of faults is Dominant in the formation of Sinkholes in this region. The results of the rtp index represents this.the length of a small number of curvature sinkholes (11%) somewhat softened and in areas away from the fault in the lowlands has a softer morphology compared with heights which have jagged and rough morphology. Results of curvature index represents that curvature slope index,profile and plan have more performance in indicating the morphometery features of landslipy Sinkholes. based on the final clustering 89 percent of our sinkholes located on a main cluster And fault factors (tectonic) causes the formation of sinkholes on the heights and In terms of of the genesis and morphometric features they are the same (rugged and rough topography) and there is no dramatic difference between them.

The area covered by snow (SC) and land surface temperature (LST) and their fluctuations in different altitudes of a mountain unit are important in climatic, hydrological and water and ecological resources management. In this study, the relationship between SC and LST in this mountainous unit was examined in monthly, seasonal and annual intervals. For this purpose, Terra and Aqua Satellite image data which are carrying Modis sensor, used in temporal range of 2003-2018.In all time periods studied, a clear relationship between elevation and SC, was observed in the Central Alborz highlands. The relationship between these two environmental indicators are direct, although the rate of change varies on different altitudes. Two specific height thresholds were observed in Central Alborz, the first threshold being at an altitude of 1000 meters and the other at 4000 meters. So that the SC rises to a height of 1000 meters with increasing altitude. After an altitude of 4,000 meters, the slope changes again and starts to decrease. LST variations are the opposite of SC. In general, increasing the height leads to a decrease in LST, but, up to 1000m is an exception to this rule, and increasing the height will increase the LST.

The area covered by snow (SC) and land surface temperature (LST) and their fluctuations in different altitudes of a mountain unit are important in climatic, hydrological and water and ecological resources management. Snow cover and land surface tempratue distribuations on different elevational class would be important from the view point of environmental systems and ecosystems observations and management. One of the major mountainous unit in Iran, which is supplying many human population, is the Central Alborz mountain, located in the northern boundary of Iran.

In this study, the relationship between SC and LST in this mountainous unit was examined in monthly, seasonal and annual intervals. For this purpose, Terra and Aqua Satellite image data with spatial resolusion of 50m which are carrying Modis sensor, used in temporal range of 2003-2018. Digital Surface Model released by the Japan Aerospace Exploration Agency (JAXA) deployed the Advanced Land Observing Satellite (ALOS) between January 2006 and May 2011, used in this research. This data have spatial resolusion of 1 arc secound (~30m) and a vertical RMSE of 4.4 m. and now is one of the most accurate dataset with global coverage and free of charge.

In all time periods studied, a clear relationship between elevation and SC, was observed in the central Alborz highlands. The relationship between these two environmental indicators are direct, although the rate of change varies on different altitudes. Two specific height thresholds were observed in Central Alborz, the first threshold being at an altitude of 1000 meters and the other at 4000 meters. So that the SC rises to a height of 1000 meters with increasing altitude. After an altitude of 4,000 meters, the slope changes again and starts to decrease. LST changes are the opposite of SC changes, in general, increasing the height leads to a decrease in LST of course, up to 1000 meters is an exception to this rule, and increasing the height will increase the LST. This is due to the cooling effect of the Caspian Sea and high humidity at altitudes below 1000 meters and also decreasing vegatation coveabdr density up to 1000m, which mainly includes the northern slopes of Alborz. Forests, forest-steppes and grasslands, are absorbing the sunrays energy and consume it in the process of photosynthesis, and so they prevents, the land surface temperature to be increased. In the highland of central Alborz (the elevation up to almost 1000m) lower humidity and vegetation cover in addition to the rocky surfaces, leads to the higher LSTs. From an altitude of 1000 meters and above, the general trend of increasing altitude leads to a decrease in LST in Central Alborz. Another environmental indicator was defined in this study, which was called the Equilibrium Line Altitude of Land surface Temperature and Snow Cover (ELALS). ELALS is a height at which LST and SC reach equilibrium. The annual average of this environmental index is in the hight of 2,800 meters during the study period in the Central Alborz highlands. The minimum level of ELALS in winter is 1740 meters above sea level. This environmental index tends to reach low altitudes in cold seasons and months and tends to higher altitudes in warmer periods of the year.

Finally, this environmental index can be used in geomorphological studies of glaciers, climates, water resources, hydrological management of basins and ecological studies of mountainous landscapes.