فصلنامه پژوهش های جغرافیای طبیعی
پیاپی 120 (تابستان 1401)

By studying, the geological structure, landforms topography, pattern of drainage network systems, indicators and geomorphological evidences of each region, the performance of Active tectonics can be evaluated. The Karkas Mountain is located in the east of Isfahan and the magmatic arc of Urmieh – Dokhtar between Sannandaj and Sirjan. The purpose of this study is to investigate, evaluate and estimate Neotectonic and its effect on morphology, behavior, formation and evolution of southern catchments of Karkas heights using geomorphic morphometric indices and its adaptation to geomorphological evidence in the region.

In this study, after studying and collecting library information, preparing the required data, in the ArcGIS software environment, the area of the basins south of Karkas Heights (10 catchments) was determined and their drainage network was extracted from DEM. Using Geomorphologic indexes to evaluate the amount and intensity of Active Tectonics in the area. This Geomorphologic Indicators are the Ratio of a Circle (Re), Bifurcation ratio (Rb), Basin form (FF), Geomorphic features of the Hypsometric integral (Hi), Basin Volume Area (V/A), The topographic symmetry Factor (T), River Length-Gradient (SL), River Sinuosity (S), Mountain Front Sinuosity (Smf), Basin shape ratio (Bs), Alluvial fan Area (Af), Alluvial fan Slope (Sf). Then using the relative active tectonic index (Iat), As a model and conceptual technique the amount of tectonic activity in catchments was calculated. Finally, the morphological evidence of active tectonics in the study area was examined. DEM 90-meter of the country is surveying organization, geological map 1: 100000, topographic map 1: 50000, IRS satellite images and Google inherit the data used in this study.

Each of the quantitative characteristics of catchment basins with specific values represents a form in the catchments. The relative active tectonic index (Iat) and Geomorphological Indices show that the area is very active. The Niazmargh, Soh, Safiabad were more active than other catchment. Existence of numerous faults that are part of the Qom-Zefrah fault system is one of the geomorphological evidences in the study area. Each of the catchments in the area is affected by one or more fault systems. Quaternary faults do not exist in all catchments of the region and are seen only in the catchments of Maravand, Absenjed, Robat, Panavand, niazmargh and the border between Safiabad catchment area and niazmargh and Panavand catchments. The valleys and canals of the rivers of Maravand, Niazmargh, Soh and Kalaharood are suitable with geological structure, tectonic activities, slopes and erosion processes have different shapes. Another geomorphological evidence in the study area is alluvial fan section. The old, semi-active and active alluvial fan can be seen in Soh area. In Kalahrood catchment, the traces of old alluvial fans have been largely destroyed and only a few parts of it have been left. Tilt of the alluvial fan and displacement of the main waterway on the alluvial fan are the other effects of tectonic movements in the region.The course of rivers in the mountainous part, depending on the land structure or tectonic structure, has an almost east-west or northeast-southwest trend, but after leaving the mountain, under the influence of the northern part, it turns to the south and goes north-south. Some rivers (Soh, Kalahrood and Robat) have been diverted to the east due to the more uplifted of the northwestern part.  In the northwestern part, due to more uplift, successive alluvial fans have been formed, while in the south-eastern part no evidence of it is observed. The slope of basins and rivers in the northwestern part is more than twice their slope in the southeastern part, which can be affected by tectonic movements. The average slope of the basins in the northwestern part is 25 percent and in the southeastern part is 12.7 percent and the average slope of rivers in the northwestern part is 20.75 and in the southeastern part is 8.1 percent. In the northwestern part, the erosion power of rivers has increased so that rivers have been able to create deeper valleys (Soh and Kalahrood valleys). While in the southeastern part, the width of the valleys is usually greater than their depth. Vf is 1.7 in the northwestern part and 8 in the southeastern. The heights of Karkas and its surroundings are active in terms of seismicity, so that in the last three hundred years, about six earthquakes of more than 4 Richter were recorded, the last of which occurred in 2016 in the Habibabad basin. During a four-year period (2008-2004), 1250 earthquakes have been recorded in Isfahan seismic network (Kalahrood, Zefreh, Nain, Qarneh and Pirpir stations)). The seismicity of Qom-Zefreh fault is estimated to be about seven Richter.According to the values of geomorphic indicators and seismic data it seems that the region is tectonically active and this activity has been more intense in Maravand, Niazmargh, Soh and Kalahrood basins. The intensity of tectonic activities decreases from northwest to southeast, so the region can be divided into northwestern and southeastern in terms of activity intensity. 

The relative active tectonic index (Iat) and Geomorphic Indices show that the area is very active. The Niazmargh, Soh, Safiabad were more active than other catchment. The Iat index of catchments is 1.93 which varies from 1.2 to 2.6 in catchments. The deep River valleys (Soh, Kalahrood, Niazmorgh and Panavand), consecutive and fragmented alluvial fan (Soh and Kalahrood rivers), river terraces, diversion paths and riverbeds (Soh, Ka lahrood and Robat) and numerous faults are geomorphological evidence that confirm the characteristics of the basins are affected by tectonic movements in the region. The results of geomorphological indices and seismic data of the region show that the catchments are active in terms of tectonic activity, but the intensity of tectonic activity in the region is not the same and its amount decreases from northwest to southeast. The impact of tectonic activity in the northwestern basins has been greater than its impact in the southeast. These activities have deepened valleys, changed the course and bed, increased the slope of some rivers, increased the erosive power and fragmentation and sequencing of alluvial fans.

Introduction:

 The phenomenon of land subsidence involves collapse or sinking of the earth's surface, which can also have a slight horizontal displacement vector. This movement is not limited in terms of intensity, extent, and measure of the involved areas. Subsidence in cities leads to costly and serious damage to urban infrastructure such as buildings, roads and railway tracks. Land subsidence can occur for a variety of reasons: groundwater abstraction, Subsidence due to oil extraction in oil fields, Displacement due to landslides and collapse of internal walls of mines.Numerous techniques and methods have been implemented to study the extent, action and land expansion and behavioral measurement in relation to land subsidence. One of the most recent and the most effective methods is the radar image interference technique. Interferometric Synthetic Aperture Radar (InSAR) is a powerful technique for measuring the topography of a surface and its changes over time. Due to its broad spatial coverage and high accuracy, InSAR has become a preferred geodetic method for the study of land deformation in developed groundwater basins and provides insight into the geological and hydrological parameters that characterize the underlying aquifer systems.Varamin plain is one of the areas affected by subsidence in Iran, which is located in the alluvial fan of Jajrud river and its development and prosperity is due to the quality and fertility of the soil in this region. Irregular and over pumping of groundwater has caused many subsidence cases in the study area. This study investigates the subsidence of Jajrud alluvial fan with emphasis on Javadabad Varamin from 2016 to 2019, using permanent scatter radar interferometry method.

Materials and Methods:

 In this study, 41 images of Sentinel (2016-2019) were used to determine the rate and amplitude of land subsidence using the method of permanent dispersants. Permanent scattering points (PS) were selected based on the domain scattering index. The amplitude scattering index, according to the threshold limit is usually considered to be 0.4 or 0.42 in various studies, which means that all selected points are not located in the set of PS points and only those points to be selected that the amplitude scattering index value is exceeding the threshold. Then, at this stage, points network (PS) was prepared in order to evaluate the processing performed. The prepared spatial network in this section is derived from the Delaunay model. Due to this fact that the amount of displacement is relative in this method, therefore, one of the points in the area is selected where the amount of displacement is relatively zero in compare to other points and other PS points are applied to it. Because of seasonal temperature changes and its effect on buildings that cause elevation changes (the effect of temperature on the structure of buildings), selected point must be located on the ground. SNAP software was selected for radar interferometry processing.. In order to find the cause of subsidence, the information of piezometric wells (1996-2016) in the study area and its temporal changes were investigated.

Results and discussion:

 research findings یافته های پژوهش:The findings یافته ها:Can't load full results Try again Retrying… Retrying… Can't load full results Try again Retrying… Retrying… In general, land subsidence has occurred in two large areas. The northern region is located in the Jajrud alluvial fan. The length of this zone is 44 km and its width is 7 km, which covers an area more than 300 square kilometers. In general, we have land subsidence in two broad areas. به طور کلی ، در دو منطقه وسیع فرونشست زمین داریم. In general, the vast expanse of land subsidence have occurred. به طور کلی ، پهنه وسیع فرونشست زمین رخ داده است. Can't load full results Try again Retrying… Retrying… Its northern region is located in the Jajrud alluvial fan. منطقه شمالی آن در مخروط افکنه جاجرود واقع شده است. North Zone is located in the fan MkhrvtAfknh Jajrood. منطقه شمال در فن MkhrvtAfknh Jajrood واقع شده است. Can't load full results Try again Retrying… Retrying… The length of this zone is 44 km and its width is 7 km, which covers an area of 300 square kilometers. طول این منطقه 44 کیلومتر و عرض آن 7 کیلومتر است که مساحت آن 300 کیلومتر مربع است. Over the span of 44 km and a width of 7 meters, which is the area of over 300 square kilometers in the lie. بیش از 44 کیلومتر و عرض 7 متر ، که مساحت بیش از 300 کیلومتر مربع در دروغ است. Can't load full results Try again Retrying… Retrying… The highest amount of subsidence in this area is related to Golabbas area, which is about 120 mm per year. The presence of Jajrud alluvial fan and agricultural lands in this area is considerable.The second region is related to the southern zone. The northern part of this zone is bounded by the city of Pishva, Qala-e-Sin and the east of Varamin city. In these areas, the annual subsidence rate reaches to maximum 6 cm. The southern part of this zone is surrounded by Hesargol and Jahanabad areas. The second area is related to the southern zone. The northern part of this zone is limited to the city of Pishva, Qala-e-Sin and the east of Varamin city. منطقه دوم مربوط به منطقه جنوبی است. قسمت شمالی این منطقه محدود به شهر پیشوا ، قلعه سین و شرق شهرستان ورامین است. The second extension of the South zone is an area in the north of the city limits Rector, Xinjiang and East fort city of Varamin is limited. گسترش دوم منطقه جنوبی منطقه ای در شمال محدوده شهر رکتور ، سین کیانگ و شهر قلعه شرقی ورامین محدود است. Can't load full results Try again Retrying… Retrying… In these areas, the annual subsidence rate reaches a maximum of 6 cm. در این مناطق ، میزان فرونشست سالانه به حداکثر 6 سانتی متر می رسد. In these areas the annual subsidence reaches up to 6 cm. در این مناطق فرونشست سالانه تا 6 سانتی متر می رسد. Can't load full results Try again Retrying… Retrying… The southern part of this zone is limited to Hesargol and Jahanabad areas. قسمت جنوبی این منطقه به مناطق حصارگل و جهان آباد محدود می شود. The southern part of the zone in MntqhHay hesar goli and JhanBad is limited. قسمت جنوبی منطقه در MntqhHay hesar goli و JhanBad محدود است. Can't load full results Try again Retrying… Retrying… In these areas, the rate of land subsidence is lower compare to the central areas and it is about 20 to 40 millimeter per year. In the northern part of Jahanabad region, the maximum land subsidence is 60 mm per year. The southern zone in which the study area is located has circular shape and the amount of land subsidence increases from the periphery to the center of the region. The highest rate of land subsidence in the study area is occurred in Salman-Abad, Khaveh, Javadabad, Hesar-e-Sorkh and Zavarehvar areas, with the amount of between 160 to 200 mm per year. Areas such as Tajreh, Rostamabad and Hesar Kouchak also show significant land subsidence, that is about 120 to 160 mm per year.The result of radar interferometry studies has demonstrated that subsidence has occurred in the main parts of the Jajrud alluvial fan's surface. Javadabad region which is located in Varamin is one of the areas with significant subsidence that subsidence occurs at a rate of 20 cm per year - Javadabad region of Varamin is one of the areas with significant subsidence that occurs at a rate of 20 cm per year of land subsidence. - منطقه جوادآباد ورامین یکی از مناطقی با فرونشست قابل توجه است که با سرعت 20 سانتی متر در سال از فرونشست زمین رخ می دهد. - Regional Branch of MhdvdhHay JvadBad with significant subsidence zone at a rate of 20 cm annual event that there is land subsidence. - شعبه منطقه ای MhdvdhHay JvadBad با منطقه فرونشست قابل توجه با نرخ سالانه 20 سانتی متر که فرونشست زمین وجود دارد. Can't load full results Try again Retrying… Retrying… Studies conducted in the study area depicted that the decreases in groundwater level in the study area is linear and this is acceptable in justifying land subsidence. Studies conducted from the study area showed that the drop in groundwater level in the area is linear and this is acceptable in justifying land subsidence. مطالعات انجام شده از منطقه مورد مطالعه نشان داد که افت سطح آب زیرزمینی در منطقه خطی است و این در توجیه فرونشست زمین قابل قبول است. Studies of the area showed a decline in groundwater levels in the region is linear in this case is the justification acceptable land subsidence. مطالعات منطقه نشان داد که کاهش سطح آبهای زیرزمینی در منطقه خطی است در این مورد توجیه فرونشست زمین قابل قبول است. Can't load full results Try again Retrying… Retrying… So that the patterns obtained using the radar interferometry method in order to find the pattern of land subsidence and groundwater were consistent and somewhat uniform. In this regard, one of the main causes of land subsidence in the region in Javadabad due to the increasing depth of piezometric wells in the study period can be attributed to the high pumping of groundwater resources. The results of radar interferometry studies have shown that subsidence has occurred at most of the surface of the Jajrud alluvial fan. نتایج مطالعات تداخل سنجی راداری نشان داده است که فرونشست در بیشتر سطح مخروط افکنه جاجرود رخ داده است. As a result of TdakhlSnjy radar studies show most MkhrvtAfknh level Jajrood land subsidence occurred. در نتیجه مطالعات راداری TdakhlSnjy نشان داده شده است که بیشتر سطح مخروتافنکنه فرونشست زمین جاجرود رخ داده است. Can't load full results Try again Retrying… Retrying… According to the physiographic shape of the region and the pattern of land subsidence, the highest rate of land subsidence was observed in areas consist of low slope, including Javadabad and Varamin. In terms of risk, population, housing, roads and buildings, rail roads and important roads are involved in the phenomenon of land subsidence in this region. The railroads of Tehran, Mashhad, Garmsar and Qom are the connecting roads in this region. The occurrence of land subsidence has caused change in the local surface slope and this has caused disturbance in the drainage network and the flow path of surface water, which has ultimately result the occurrence of various types of erosion.

The evapotranspiration, as one of the important meteorological variables and the relation between the land surface and the atmosphere, is important to the study of drought and the allocation of water resources. The relationship of this climatic variable with land indices as well as water supply planning reveals its importance. Due to the high relationship between this variable and air temperature, changes in air temperature patterns in global warming and climate change will have a high impact on its behavior and distribution. The relationship and entanglement of this hydro-climatic variable with climate change, especially temperature, has caused that with any fluctuation and change in the behavior of temperature patterns, its value and distribution will also change. Iran as a country located in the arid areas of the planet earth; is currently heavily involved in water stress. This water stress will be exacerbated by climate change, rising temperatures and increased evapotranspiration. Examining the impacts of climate change can be a roadmap for environmental management in this area. The aim of the present study is to reveal the behavior of this climatic parameter in the future period compared to the historical period and its spatial distribution based on the data network.

In the present study, using the output of downscaled dynamic models of the CORDEX-MNA project for North Africa and the Middle -East under (RCP8.5 and RCP4.5) scenarios. For the historical period (1980 – 2005), reference evapotranspiration was estimated by the Penman- Monteith, FAO method. The NOAA-GFDL-GFDL-ESM2M regional climate models (RCMs) as the dynamic model output projection was used for the future to mid century (2025-2050).In this study, RCP4.5 & RCP8.5 representative concentration pathway scenarios were selected, as these two scenarios are used to further investigate climate change vulnerabilities and subsequent climate change responses. The CORDEX-MNA data with 0.22 spatial resolution, RCA4 model for RCM, were used. For the future period, the ETo value is obtained directly from the output of the CORDEX-MNA coordinated project models. In fact, the reference evapotranspiration value is part of the simulation of these models. Statistical criteria are used for the correction of the models to show the similarity between the observed and modeled data in the form of statistical values.

The results showed that in the future period, based on CORDEX-MNA coordinated project simulations for North Africa and the Middle-East, downscaled dynamics models; the amount of reference evapotranspiration as one of the most important components of the hydrological cycle will increase compared to the historical period (1980-2005). In terms of temporal variation, the highest changes will occur in mid-winter to early autumn. Under the RCP scenario, the ETo will increase to 34 mm in the hot months such as August. Under the mid-term scenario, the ETo value will increase compared to the historical period, but this increasing will be less than the upper limit scenario. Spatially, the main foci of high reference evapotranspiration are located in the central areas around Kavir and Lut plains, Jazmourian areas and the southern half of the Iran. The results showed that in the context of climate change and based on the downscaled data of the CORDEX -MNA project; the range of high potential evapotranspiration in the Iran will increase. In fact, high latitudes will experience an increase in the amount of ETo due to changes in air temperature and precipitation patterns and increasing air temperature trends. These conditions will be an alarm for Iran with arid and semi-arid conditions. Any change in the amount of evapotranspiration causes drought in the environment, followed by water needs and irrigation frequency for the agricultural sector as the most important water consuming sector in Iran. Therefore, it is important to pay serious attention to water resources management programs.

 Among the models used, the output of the regional model; NOAA-GFDL-GFDL-ESM2M has more optimal conditions in simulating the effects of climate change in Iran. The ETo spatial pattern is a function of location components throughout the year. These conditions are well evident in the distribution of potential evapotranspiration. The amount of ETo will increase from west to east and from north to south of the country based on the spatial pattern obtained in the historical (1980-2005) and the future period from 2025 until 2050. The southern and central regions of the Iran are the focus of areas with high ETo. The role of altitude and latitude factor in determining this spatial pattern is obvious. Comparison of ETo historical-observational period with the future decads to 2050, shows a significant increasing in the amount of potential evapotranspiration in Iran. Under RCP8.5 from March - September ETo will reach the highest level. In areas with high ETo in Iran, the average amount of ETo will increase by an average of 11 mm from April to June and in the warm months by an average of 17 mm. Under RCP4.5 scenario, these conditions are also observed to be incremental with a lower value. In the cool and cold months, in the high regions, the amount of minor and small changes and in some areas without change is observed. Significant increasing in reference evapotranspiration in August as one of the hottest months of the year in Iran is significant; because at this time of year, the demand for water consumption in all sectors; in particular, the agricultural sector is reaching its highest level, which necessitates attention to water resources management. In general, reference evapotranspiration as one of the hydro-climatic components, with any change in air temperature, will face increasing conditions that result in this increase, imposing more drought on the environment and thus increasing the water demand. Especially in the agricultural sector. These conditions are important for the geography of Iran with its fragile climate. Therefore, the land of Iran is currently facing tensions and instability in the situation of water resources, these conditions will intensify in the coming decades under the conditions of climate change. The need to pay attention to risk management and increase resilience in the face of climate change due to global warming can be considered a roadmap in this area.

Wind energy offers many advantages, which explains why it's one of the fastest-growing energy sources in the world. Many researches efforts are aimed at addressing the challenges to greater use of wind energy. Wind energy doesn't pollute the air like power plants that rely on combustion of fossil fuels, such as coal or natural gas. On the other hands, the world is fast becoming a global village due to the increasing daily requirement of energy by all population across the world while the earth in its form cannot change. The need for energy and its related services to satisfy human social and economic development, welfare and health is increasing. Returning to renewables to help mitigate climate change is an excellent approach which needs to be sustainable in order to meet energy demand of future generations. Recently, Mazandaran Province has needed more energy. Considering the capabilities of this province in generating renewable energy, recognizing the potentials of clean energy generation and consumption, especially wind energy, should be a priority in the plans of managers and researchers.

Current study has been done with the aim of spatial capability of wind energy in Mazandaran Province with emphasis on its environmental factors. A descriptive, analytical and field approach is used in this study. The spatial capability of wind energy in Mazandaran Province was evaluated using spatial and quantitative data. In order to initially estimate the energy that can be obtained from wind flow in the province, the necessary calculations were performed on wind direction and velocity information over a period of 12 years. Statistics of 15 synoptic meteorological stations in the province at a height of 10 meters were used to collect daily wind speed and direction data. After calculating the average wind speed, wind speed continuity and wind power density in the meteorological stations, layers of each were prepared at heights of 10, 30 and 50 m using interpolation in ArcGIS software environment. Using AHP and ANP models, layers of 4 technical (climatic), environmental-social, topographic and economic criteria including 21 sub-criteria were prepared then overlapped to determine suitable locations for construction of power plants or installation of wind turbines in Mazandaran Province. Finally, wind potential spatial measurement was performed using spatial, cellular and zoning analyzes in ArcMap software environment.

According to the calculations, it is clear that the price of fuel consumed by power plants in the current situation and based on the use of gas will make gas power plants still more cost-effective. In this case, it can be seen that even the cost of pollution cannot make the wind power plant more economical; Because the wind power plant is highly sensitive to exchange rate which this sensitivity is due to the high cost of imported equipment. But if the price of fuel used by power plants is calculated on the basis of the real price, wind farms will be justified. Therefore, with the resistance economy approach, replacing thermal power plants with wind power plants will be economical and cost-effective in the medium and long term. In this way, in addition to using the potential of renewable and clean energy in electricity generation (according to the environmental potential of Mazandaran Province), much lower environmental damage compared to fossil fuels and greater durability of non-renewable fuels for transmission to future generations, the economic costs of power generation and power plant networks maintenance will also be reduced. The relative weights obtained from the network analysis process model (AHP) in the process of selection of the suitable location of wind power plants in the province showed that the effect of climatic criterion with a relative weight of 0.543 is greater than other three criteria in preparing the zoning map. Topographic criteria with a relative weight of 0.26, economic with a relative weight of 0.111 and environmental-social criteria with a relative weight of 0.086 are in the second to fourth categories of influencing the preparation of optimal zoning maps for wind power plants in Mazandaran Province. According to the zoning map obtained from ANP model such as AHP map, the western parts of Noor township, the northern parts of Savadkuh, Sari, Neka and Behshahr townships, the central zone of Babol township along with the central zone and the northern parts of Amol township are more suitable than other parts of the province to establish or build wind power plants.

Energy sector strategies should be developed and planned with the approach of optimizing energy consumption and planning in renewable energy development. This study was done with the aim of spatial measurement of wind energy in Mazandaran Province. The most favorable conditions for the installation of wind turbines can be observed in the mountainous and high parts of Noor Township.

What is known as a cloud is actually the accumulation of water vapor particles in the atmosphere around the nuclei of their density and cooling (Ghasemi, 2012). In this study, we will study and identify the clouds that are formed in terms of spatial distribution between the southern coast of the Caspian Sea to the Alborz Mountains and in terms of temporal distribution in all seasons, especially in summer. It seems that these clouds were different in terms of atmospheric formation mechanism and are formed under special environmental conditions of the Caspian coast. Therefore, the main purpose of this study will be to identify and study these clouds. For this purpose, 279 cloud days were selected for study.

This study uses type, amount and height of low, medium clouds, including hourly data (00, 03, 06, 09, 12, 15, 18 and 21 UTC) and daily precipitation of 13 meteorological stations in the study area, for selected samples, were received from the Iran Meteorological Organization (IMO). The characteristics of the physical parameters of the cloud Included CTT, CTH, CER, COT and CWP were obtained from level 2 MODIS (MOD06 TERRA and MYD06 Aqua) with a resolution of 1 km. Upper atmosphere data were obtained from ERA5 at a resolution of 0.25° × 0.25 °. Which includes geopotential height, u- wind, v- wind, specific humidity and omega levels of 1000 to 500 hPa isobaric. Ground surface data (SLP, U-wind and V-wind 10m) were obtained from the NCEP/NCAR database and its circulation patterns were drawn in GRADS. HYSPLIT model and the backward method was used to identify the source of moisture. In this study, Global Data AssimilationSystem (GDAS 1°) meteorological data provided by NOAA HYSPLIT model were used to calculate the backward paths for altitudes of 50, 500 and 1000 m above the ground. First, the frequency percentage of the type and height of different layers of clouds were calculated. The average seasonal and monthly occurrence of Caspian clouds were calculated. The average seasonal and annual rainfall of Caspian clouds were calculated. The relationship between precipitation and cloud parameters was investigated by multivariate regression

 During the 10-year statistical period (2020-2010), 279 cases (days) of the occurrence of Caspian clouds were identified. The research findings showed that the highest average monthly frequency of Caspian clouds occurs in August until its lowest occurrence in November to April. The maximum seasonal frequency of days with Caspian clouds occurs in summer with 16.1 days. These clouds are mainly in the form of low- and middle-level clouds in the region with their most common types being Stratus and Altocumulus. The analysis of rainfall rainfall from Caspian clouds indicates the annual rainfall of Caspian clouds in the region and in most stations more than 80 mm, and its highest amount occurs in summer and autumn chapters, respectively. Spatial distribution the average rainfall derived from Caspian clouds showed that its maximum is on the annual scale and summer and autumn seasons in the southwest and west of the region; but in the spring, it is placed in limited parts of the south. By applying the multivariate regression model, it was found that cloud parameters may predict 57% of the rainfall changes in Caspian clouds. Examination of the synoptic patterns shows that high-pressure settlement in the north of the Caspian Sea provides favorable conditions for wind flow and moisture transfer of the Caspian Sea to its southern coast. So that with the encounter of the humid air mass to the Alborz mountain range, it leads to orographic lift and formation of clouds and rain in the region. The HYSPLIT model indicates that the source of moisture for the formation of Caspian clouds is largely from the Caspian Sea.

The average frequency of the occurrence of Caspian clouds in August to stamp is more than spring and winter months. The average number of summer and autumn, as well as the average rainfall of Caspian clouds in the summer and autumn, is more than other seasons. These clouds are mainly in the form of low- and middle-level clouds in the region with their most common types being Stratus and Altocumulus. By applying the multivariate regression model, it was found that cloud parameters may predict 57% of the rainfall changes in Caspian clouds. Examination of the synoptic patterns shows that high-pressure settlement in the north of the Caspian Sea provides favorable conditions for wind flow and moisture transfer of the Caspian Sea to its southern coast. So that with the encounter of the humid air mass to the Alborz mountain range, it leads to orographic lift and formation of clouds and rain in the region. The HYSPLIT model confirmed the moisture transfer from the Caspian Sea to the study area.

Alluvial fans are important geomorphic landforms due to their advantages and their hazards. Many researchers in different aspects have investigated alluvial fans. A sudden change in the topographic slope at the mountain front and a decrease in stream power are proposed as the main factors of alluvial fan formation. However, the relationship between alluvial fans and active depositional processes on the surface of alluvial fans. the relationship between the area and the slope of the alluvial fans with geomorphic and geologic characteristics of their basins and investigating the morphology of alluvial fans using quantitative characteristics have been widely studied by many researchers, few studies have focused on the topographic characteristics of alluvial fan toes. The slope is a useful morphometric indicator to distinguish alluvial fans from other depositional landforms distributed on the pediment. The aim of this study is to quantitatively investigate the morphometry and slope changes on the alluvial fan toes of an arid region in order to distinguish them from other depositional landforms on the pediments. Therefore, we analyzed the slope of 40 alluvial fans and their morphometric characteristics in central Iran.

To investigate alluvial fans' morphometric characteristics, we first selected 40 alluvial fans in central Iran using satellite images. We chose a minimum length of 2000 meter for the alluvial fan selction. Next, six morphometric parameters including the overall slope of the alluvial fan (SO), mean slope of the area above the fan toe (SA), mean slope of the area below the fan toe (SB), the ratio of SA to SB (RS), the total length of the alluvial fan (L) and the sweep angle (AF) were measured. The slope of the alluvial fans was calculated using the study area SRTM (Shuttle Radar Topography Mission) Digital Elevation Model (DEM) with a 30-meter spatial resolution. The digital elevation model was converted to the UTM (Universal Transverse Mercator) coordinate system since we used the metric measurements in this study. The overall slope of the alluvial fans, alluvial fan length, and alluvial fan sweep angle were measured using the digital elevation model and QGIS software. To calculate the slope of the area above and the area below the alluvial fan toe line, we first created a buffer with 250 meters distance from the toe line. This distance was applied to avoid unwanted errors. Each buffer has 1000 meters distance. Generally, we used Google Earth pro, ArcMap, QGIS, and the digital elevation model of the study area to measure the morphometric characteristics of the fans and SPSS to apply the statistical calculations.

To calculate the morphometric parameters and to analyze the slope changes of the alluvial fan toes, we first selected 40 alluvial fans in Central Iran. Afterward, the sweep angle, alluvial fan length, overall slope of the alluvial fan, the average slope of the area above the fan toe, and the average slope of the area below the fan toe were calculated. According to Table 1, the most considerable sweep angle equals 156.12 degrees on the alluvial fan number 31. The smallest sweep angle belongs to the alluvial fan number 1 with the value of 14.7 degrees. Among the studied alluvial fans, the alluvial fan No. 17 has the shortest length (2076.679 m), and the alluvial fan No. 26, with a length of 44569.45 m, is the most elongated alluvial fan. In terms of overall slope, fan No. 17 has the highest value in slope (3.38 degrees), and the alluvial fan No. 16 has the lowest (1.64 degrees). Most of the studied alluvial fan have a slope of 2 to 2.5 degrees in terms of the slope of the area above and below the fan toe. The mean overall slope for the studied fans is 2.27 degrees. In terms of the RS factor, most of the fans are distributed in the range of 1 to 1.5. Generally, the slope decreases from the apex to the toe in an alluvial fan. The most important factors for the slope changes on the surface of the alluvial fans include flow velocity reduction, reducing the flow power, and reducing the channel width to depth ratio. Tectonic activity is also one of the essential factors in determining and changing the slope of alluvial fans. Sometimes due to severe tectonic uplift, new sediments deposit on the young and elevated surfaces of the alluvial fan, leading to steep slopes on the surface of the alluvial fan. Based on the results, with increasing the alluvial fan length, the slope of the area above the fan toe decreases. The same correlation can be seen between the length of the fan and the overall slope. The negative correlation between alluvial fan overall slope and alluvial fan length in this study is consistent with the results of other studies.

In an alluvial fan system, the apex of the fan is the steepest part, and the slope decreases to the fan toe. Different factors such as tectonics, stream discharge, sediment materials, etc., affect the slope of the alluvial fan. This study showed that most of the studied alluvial fans have straight profiles. The alluvial fan's straight profile indicates that the materials from the catchments area have been transported during the catastrophic flooding events and preserved on the alluvial fan surface for an extended period. The similarity between the fan's overall slope and the slope of the area above the fan toe is a sign of inactivity of erosional processes. When SA is smaller than SO, the alluvial fan will have a concave profile. The results of this study are also consistent with other studies showing that the arid region alluvial fans have a greater slope than humid regions fans. The RS values in the studied alluvial fans reflect the effect of fluvial processes on the slope changes on fan toes. It also shows that erosional processes have been inactive for a long time in the studied fans.

Water levels in the Caspian Sea fluctuate constantly on different time scales. In recent decades, several studies have examined the causes of fluctuations, the impact of climatic and non-climatic components, and the forecasting of water levels based on different climatic models. Considering that most of the predictions regarding hydro-climatic components and Caspian water level are based on a fixed time period. Thus, in this study, we considered the time base period for downscaling the Caspian Sea's variable level and, on the other hand, for integrating the best output of different climatic models. Accordingly, the purpose of this article is to estimate the future sea level of the Caspian Sea using the sixth IPCC report under optimistic and pessimistic scenarios.

Data for this study includes two groups of Caspian Sea water levels from 1941 to 2019, as well as the output of three climate models; INM-CM4-8, MIROC-ES2L, and MPI-ESM1-2-LR. As part of the above three models, we selected the following components: percentage of cloud cover (clt), evaporation flux (evspsbl), specific humidity (huss), precipitation flux (pr), sea surface pressure (psl), air temperature (tas), and wind components including orbital and meridional components (vas & uas) and surface stress (tauu & tauv) for the base and future periods, 1941 to 2080. These models are part of the CMIP6 international model comparison project produced under the name Phase 6. The scenarios used in this study are SSP2-4.5 and SSP5-8.5, which are based on common paths identified in the sixth IPCC evaluation report. An analysis of the Caspian Sea water level was conducted using Statisca software to model it using a multivariate regression model. In order to model the Caspian Sea water level, the selected data matrix was adjusted by including a difference in level from the previous time, which can eliminate long-term trends in the Caspian Sea water level. In this study, based on long-term statistics of the Caspian Sea water level and climatic data output, in order to model the difference in the Caspian Sea water level, we considered the base periods with five time scales, which included periods 2019-1941 in order to select the best baseline variety for modeling the Caspian Sea water level. To evaluate the efficiency of Caspian Sea water level modeling based on different models, we divided the basic modeling course into two modes, training and testing. The climate models in this study were validated using various criteria, including mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2), Nash-Sutcliffe (NS) and Durbin Watson (DW) camera adaptation percentage (Ghanghermeh et al., 2019).

According to MIROC-ES2L climate model NS, R2, and DW statistics, there is a good match between the training and testing periods in all time scales of the basic period. In the two climate models INM-CM4-8 and MPI-ESM1-2-LR, the base time scale of 40 and 50 years, i.e. the training period of 2001-2009 and 1971-2009, the models do not perform well during testing, while in other scales, both in testing and training modes, good performance is seen, with the exception that DW has excellent consistency in all scales. The results suggest that, using two scenarios including SSP2-4.5 and SSP5-8.5, the water level will decrease by an average of 43 cm per decade in the INM-CM4-8 climate model between 2021 and 2080, resulting in the level of -30.38 meters. However, based on the SSP5-8.5 scenario, the level is increasing from 2021 to 2050 by 20 cm, and then it is decreasing with an average intensity of 61 cm, finally reaching -29.07 cm in 2080. As shown by the MIROC-ES2L climate model, both scenarios show a decreasing trend in water level, with the average decrease in SSP2-4.5 scenario being equal to 87 cm per decade, while in SSP5-8.5 scenario, the trend is slightly different. As a result, the water level will decrease by 26 cm per decade by 2050 and by 102 cm per decade by 2080 based on the SSP2-4.5 scenario and by -31.76 meters in the SSP5-8.5 scenario. In According to the MPI-ESM1-2-LR climate model, the Caspian Sea water level behavior is different from the above two models, so that the trend of changes in the Caspian Sea water level will continue to increase from 2021 through 2060 with an average of 48 cm per decade, and then the slope of decline of the Caspian Sea water level will become smoother. However, according to the SSP5-8.5 scenario, the water level of the Caspian Sea will increase with a gentler slope, with fluctuations around 10 cm per decade. Finally, the amplitude of water levels in 2080 will be the least different between the two scenarios. Considering the combined results of the above three models, it will be determined that the Caspian Sea water level will be decreasing based on the SSP2-4.5 scenario. In this case, we see that first there will be a smoother slope trend by 2060, which will reach -29 meters, and then the slope trend will be more intense and will reach -30.4 meters. But according to the SSP5-8.5 scenario, the sea level will remain stable at the focal level until 2050, and then the downward trend will reach -29.5 meters by 2080.

As a result of merging the three climate models, it was found that in the SSP2-4.5 scenario, despite the average greenhouse gas emissions remaining at current levels by 2050 and decreasing by 2100, and of course by increasing the temperature by 2 degrees Celsius for the period 2060-2041 and by 2.7 degrees Celsius for the period 2100-2081, the water level in the Caspian Sea will consistently decrease. In the SSP8-8.5 scenario, with intense greenhouse gas emissions and a tripling of carbon dioxide level by 2075, the water level of the Caspian Sea will remain stable from the beginning to 2050, but from this year on, its decline will begin. Additionally, this study's findings are consistent with those of Algioni et al. (2006 and 2007), Korich et al. (2021), Chen et al. (2017), and Hosseini et al. (2020) concerning the decrease of the Caspian Sea water level

In studies by the World Meteorological Organization, winds with speeds of more than 15 meters per second (30 knots) and horizontal visibility below 1000 meters are known as dust storms. This is based on the Beaufort scale in the hurricane group and such storms can move particles with a length of more than 500 microns. In this case, the sandstorm settles for short distances, but the dust travels long distances in the form of suspended or fine dust.When the wind speed reaches 7 meters per second or less, it only has the power to move particles less than 20 microns long, and the rest of the storm is scattered in the air in the form of suspended particles or dust. Evidence shows that dust is increasing in the eastern regions of Iran. Consequently, on April 25, 2015, the amount of pollution in Mashhad reached 55 micrograms per cubic meter in 24 hours and, was alert. In the first six months of 2016, the cities of Tabas, Nehbandan, and Birjand had the highest number of dusty days with, 45, 29,and 27 days, respectively. The wind speed in Yazd had similar conditions, which reached 96 km / h on July 22, 2015, while it was 70 km / h in Kerman on February 20, 2015. In Zabol, the cost of respiratory diseases caused by dust from 1999 to 2004 is estimated at more than 70 million dollars. Considering the frequency of dust phenomenon in the eastern regions of Iran and the importance of spatial-temporal analysis and its prediction was suggested.

The study area is located between 52 to 64 degrees longitude and 24 to 38 degrees latitude in the east of the country, which includes the provinces of Khorasan Razavi, South Khorasan, Sistan-Baluchestan, Kerman, and Yazd. Therefore, to estimate the number of dusty days, the statistics of 57 meteorological stations and the elements of wind speed of 15 meters per second and more, horizontal visibility of less than of 1000 meters from the statistical period of 1/1/1987 to 31/3/2017 were used.It was then considered for the forming of the m × n matrix and statistical matching for years without NA statistics. In the next phase, utilizing several software packages, including gstat, spacetime, SP, raster, spdep, RgoogleMaps, tseries, maptools, plm, randtest, and R the necessary programming was done next, all marginal variogram models, including Gaussian, spherical, linear, Bessel, exponential and Mattern were fitted separately with the experimental data model

The percentage of the number of monthly dust days indicates that the range of changes rises from 1.04% in October to 3.42% in March. This means that on average, in the study area, about 4% of the days in March were dusty.This month was chosen as the critical month for estimation.The outputs revealed that the Sum-metric model, with the lowest mean squared error, has the best fit for estimating data. However, the experimental time variogram with an interval of 30 months shows that the gamma output values in the middle logs are closer, and the data are more interdependent, but their range is extended. In both variograms, the Partial Sill being more significant than the Nugget Effect has good conditions for model fit. Nevertheless, its spatial-temporalvariogram shows that the estimated time will not be extended, and the data will move towards the average faster.However, the four months were considered: March 2018, March 2019, March 2021, and March 2022.The results showed that no fundamental changes in the spatio-temporal distribution of data are seen from March 2018 onwards. Therefore, the variogram can only estimate March 2018.Accordingly, the most critical estimated points for the number of dust days that have higher values in March 2018 are in 3 provinces, including: a) Khorasan Razavi, (Mashhad, Golmakan, and Fariman stations with three days, and cities of Quchan, Khaf, and Bardaskan with two days), b) Yazd province, (Abarkooh with four days ,and cities of Lalehzar, Eghlid, Bafgh, Meybod, Bahabad, and Harat with two days), c) Kerman province(Kerman station with three days, and Anar with two days), and d) Sistan and Baluchestan ( Zahedan with four days, Zabol, Mirjaveh, and Konarak with three days, and cities of Khash and Nusratabad with two days). Estimated values for March 2018 in South Khorasan Province show that these areas have the fewest dusty days.Data analysis a 95% confidence level showed that Zahedan stations with eight days and Golmakan, Zabol, Mirjaveh, Konarak, and Abarkooh stations with seven days had the highest number of dusty days in March 2018 in the eastern regions of Iran.

The results reveal that since 1987, the number of dusty days in March starts at 47 and reaches 162 in March 2017. This means that with an average number of dust 58 dusty days, there is a positive deviation of 104 days, which is a very high figure and could indicate the severity of the air pollution crisis in the country's east in the coming years. The intrinsic structure of the data shows that the Sum-metric model can be estimatedonly in March 2018.Out of a total of 57 stations in the study area, 8 stations are in good condition, 28 stations are in normal condition, and 21 stations are in critical condition. Estimations of the probability of occurrence at the level of 95% of the number of dust days show that the lowest number of dust days in the east of the country in March 2018 is related to Kashmar, Birjand, and Boshrayieh stations with four days, while the highest number of days is related to Zahedan station with eight days, and Golmakan, Zabol, Mirjaveh, and Konarak, and Abarkooh stations with seven days the maximum probability of occurrence.