فصلنامه پژوهش های جغرافیای طبیعی
پیاپی 114 (زمستان 1399)

The wind is the horizontal displacement of air that is less than one meter per second. The wind is a dynamic phenomenon and has three main characteristics: intensity, direction, and frequency. Therefore, knowledge of wind characteristics in every area of importance is remarkable. The effects of global warming on temperature and precipitation at the global level over the past decades, many studies were considered; However, relatively little attention to climate change is wind speed. Wind speed changes can affect the energy of storms, shipping industries, as well as soil moisture, evaporation, and water resources; and it may even affect the evolution of dry and semi-arid environments. Also, a lot of research on wind and meteorology has shown that the performance of wind turbines is sensitive to climate change. Possible changes to the future wind regime have been widely considered under changing weather conditions; under global warming, the intensity and frequency of wind events are expected to change at the end of this century.

The study area in this study of the eastern strip of Iran includes four provinces of Khorasan Razavi, South Khorasan, Kerman, and Sistan and Baluchestan. The study used wind speed data at a height of 10 meters, 10 synoptic stations with a daily statistical period of 2015-1985, which has 30 years of data; In choosing this station, in addition to proper distribution in the region, an attempt was made to select more stations in the station to be affected by the 120-day winds of Sistan. In this study, 10-meter daily wind speed data of the ERA-Interim version with a resolution of 0.125 × 0.125 degrees period of 1980-2015 were used; for the study area, 3772 pixels with an inter-pixel distance of about 12.5 km have been obtained. To evaluate the performance of simulated data against observational data; There are several indicators used in this study from the Root mean squared error (RMSE), Mean bias error (MBE), mean absolute error (MAE), and the coefficient of determination (R2). The non-parametric Man-Kendall method was used to investigate the trend of wind speed changes in research.

The ECMWF ERA-Interim version has a high and good performance for wind speed. The results showed that the output of the mentioned base in all the studied stations is on average between 0.722 and 0.984. RMSE, MBE and MAE characteristics in Zahedan, Khash and Saravan stations are less than m / s1; In other words, the wind speed of ECMWF base in these three stations has the highest performance of the 11 stations studied. The monthly statistical assessment of wind speed in selected stations in eastern Iran during the statistical period studied (1985-1985) showed that the average wind speed is 3.56 m / s. The relationship between wind speed with negative altitude and positive longitude is significant at the level of 0.05. Also, the relationship between latitude and wind speed showed that this relationship is negative in the cold months of the year and positive in the warm months of the year. The average wind speed fluctuates greatly during the 30-year statistical period. The average wind speed varies between 2.82 and 4.57 m / s. The minimum and maximum wind speeds were calculated in December and July, respectively. The average 30-year wind speed at selected stations in eastern Iran was calculated to be 2 m / s. The maximum wind speed in eastern Iran has many fluctuations; autumn showed the lowest statistical value in terms of maximum wind speed; In December, the maximum wind speed was calculated to be 3.98 m / s. The maximum wind speed is increasing in all the studied months; From a statistical significance level, all the studied months except January, which, despite being increasing, are; But statistically, it is not significant at the level of 0.05 and 0.01; Other studied wind speed studies have a significant incremental trend at α = 0.01. The average wind speed in the study area is negative in 7 months (January, April, May, July, August, October and December) from the negative years and in 5 months (February, March, June, September and November). The maximum wind speed is January 4.42, February 4.86 and March 5.02 m / s. The next area to be obtained in the form of a fertile area in winter; Zabol is also the center of Iran's border with Afghanistan in the border areas of South Khorasan Province. The wind speed trend is positive at the time of onset (June, 0.79), the 120-day wind is positive and negative at the time of termination (October, -0.15).

The average wind speed in the study area (Khorasan Razavi and South Khorasan, Kerman and Sistan and Baluchestan provinces) during the long-term statistical period of 30 years (2015-1985) is 3.56 m / s; The minimum and maximum wind speeds are obtained in July and December, respectively; The reason for the increase in wind speed in July is due to the 120-day wind activity in Sistan, which started in June. The average wind speed in the study area is negative in 7 months (January, April, May, July, August, October, and December) from the negative year and in 5 months (February, March, June, September, and November). Investigation of wind speed process using non-parametric Man-Kendall (M-K) test; It showed that the wind speed trend in eastern Iran in the first month of June (June) 120-day winds showed an increasing trend (Z score of the Man-Kendall test 0.795) and in the last month (October) it decreased (-0.1152). ). Also, in July, when the wind speed is maximum, the average trend in the study area with a score of Z, 0.242 - is decreasing. Pearson correlation test showed that the relationship between wind speed and topography in the study area was statistically significant at 0.05; In contrast, the relationship between longitude and wind speed is significant in all studied moles at the alpha level of 0.05. In contrast, longitude and altitude in the study area did not show a uniform relationship between latitude and wind speed; this relationship is reversed for the cold months of the year and directly for the warm months. In October alone, the relationship between wind speed and latitude is not significant.

Landforms and their response to environmental changes is one of the most interested topics among geomorphologists. One of the landforms that is most affected by tectonic and erosion processes is the rivers. Rivers respond to tectonic processes that increase the height of landscapes and erosion processes that try to reduce the height of landforms. This reaction can be well studied by analyzing the longitudinal profile of the rivers. One of the effective parameters in the study of tectonic and erosional status of regions is steepness and concavity. These parameters can be examined in the form of Stream Power Law (SPL). This function is related to incision power of streams.This relationship in the form of the linkage between slope and drainage area of the river in a logarithmic plot based on power regression, extracts the values of two parameters, the steepness and the concavity of the channel. In fact experimental studies by other researchers have shown that there is a direct relationship between rivers steepness and concavity with tectonic – erosive processes in the regions. It generally accepted that steep landscape are associated with areas of high uplift rate and active tectonic. Rivers system are well adopted to tectonic processes to provide useful information about the rate of uplift in landforms. The steepness of rivers which depends on the declivity of channels is fraction of uplift rate. So we expect that if the amount of the steepness in the longitudinal profile of the river is low, the uplift rate is slight too and if the steepness is high, the uplift rate is intense too. Concavity index usually depends on bed material. But erosion efficiency has direct connection with incision power law and its steepness. But weakness of bed material especially alluvial can increase rate of erosion efficiency in channels. Erosion efficiency is the volume of sediment that is completely removed from the environment after erosion. Erosion efficiency is a function of sedimentary flux. This parameter can be directly related to the tectonic processes and characteristics of the bedrock. If tectonic processes lead to an increase in the height of the landforms, it can increase orographic precipitation in mountainous areas, and it can lead to increasing sedimentary flux, then erosion efficiency also increases. The main purpose of this study is to analysis the effect of active tectonic and erosion on equilibrium profile of the main rivers of the Damghan Mountain based on the Stream Power Law. These steepness and concavity parameters are influenced by set of lithological, geological, topographic and erosion factors. All of these factors are effective in location of knick points of rivers and are able to provide useful information about the geological and erosion status of the area

In order to investigate the power incision law, the DEM map in 30m resolution was used to extract the channels. For extracting the rivers, the D8 algorithm method was used to calculate the flow direction. In this method, the flow path of each pixel that fall on the lower pixel with a lower slope was calculated and the flow directions was determined. In this regard, we first need to create a DEM map with the least inconsistency. This method focuses on extracting central flows in valleys and reducing parallel flows. After extracting the channels, their slope-area logarithmic diagram were plotted. The regression line considered for the logarithmic plot is the power regression, which is the relation of the river incision power. In this regression, the slope of the regression line is concavity and the intercept of line is steepness. To obtain information about lithological features of the area that are effective in analyzing the concavity and steepness parameters, the geological map of Damghan and Shahrud was used. The study area is part of the mountain structure of Eastern Alborz and has several active faults. North Damghan Mountain is located on the southern side of eastern Alborz between 36。14'0.3" to 36。18' 82" and 55。00' 26" to 53。59' 56" in north of Iran plateau. There are different outcrops of lithostratigraphic formations from Precambrian to Quaternary in this area. Geologically speaking, the study area is composed of set of over thrust blocks and nappes. The thrust faults and nappes within piggy back style have pushed eastern Alborz stratigraphy sequences on each other. The folds in the region have a strong connection to thrust structures and nappes. These folds are of different types and sizes but most of them are inclined and recumbent because of widespread compressive component in eastern Alborz.

The three main rivers of the region, CheshmehAli, Astaneh and Tepal, were studied. All three rivers flow on the colluvium bed in the upstream and alluvial bed in the downstream. And all three affected by faults in some areas. Some such as CheshmehAli River in the southern part, has flowed into a fault valley. The activity of faults along the rivers, both in the resistance and alluvial parts has led to uplift of the rivers. These effects are seen in the high values of steepness index and low values of concavity index. The increase in the stream incision is seen in both the upper and lower section of the rivers due to the activity of faults in the region. But the steepness is higher in the upstream which is made of colluvium sediments. While in the downstream due to weakness of alluvial sediments the rate of erosion efficiency is higher. Therefore the change in the rate of steepness, concavity and erosion efficiency, in addition to active tectonic, is strongly affected by the bedrock of channels. Each rivers that is most faulted also has higher values of the steepness index. CheshmehAli River, part of which is located completely in the faulted valley, has the highest rate of steepness compared to other rivers. The Astaneh River has been affected by the Astaneh fault in several parts, and the fault has led to the uplift of the river by cutting off the Quaternary sediments. The high values of steepness parameter in this river confirm existence of active tectonic. The Tepal River in its upper part shows high values of steepness parameter, but in the downstream part where the river flows on agricultural lands, the rate of erosion efficiency has increased and in contrast the rate of steepness parameter has decreased. This is due to human activities that have caused the rate of erosion to exceed the rate of tectonic processes. Therefore, human activities are able to transform the relationships between internal and external processes that are effective in changing landforms.

The results show that reaching the equilibrium profile in each river depends on a set of factors include erosion, tectonic and lithology. Fault in the channel path leads to an increase in the height and slope of the river channel and erosion accurse in response to this change. Tectonic processes increase the incision capacity of rivers as a result of increasing the slope of the channel, which increase the volume of sediments produced in the river. Of course, like that Tepal River, we must consider the role of human activities in increasing the rate of erosion efficiency. Key Words: Eastern Alborz, Damghan, Active Tectonic, Morphotectonic, SPL Model.

Precipitable water (PW) is highly variable in space and time and is one of the most important abundant greenhouse gases that play crucial role in the study of climate change, hydrological cycle, energy budget and numerical weather prediction. The knowledge about the spatial and temporal variability of PW is important in understanding climatic processes and in order to monitor drought conditions and desertification processes (Kaufman & Gao,1992). It is therefore necessary to obtain the distribution condition of water vapor in the atmosphere and to understand the effects of spatial–temporal variation of PW on regional, meso-micro scales and on global climate change (Wang, 2013). PW has a very short life cycle in atmosphere and this rapid turnover, joined to temperature variations with altitude and geography, distance to sea, evapotranspiration and moisture advection causes an irregular PW distribution in atmosphere, both horizontally and vertically. The purpose of this study was to identify the distribution patterns of PW in Iran and relationship these patterns with elevation and distance to sea.

In the present research, MODIS Aqua data (MYD05_L2. A V06) were used. The data with spatial resolution of 1 km (Near Infrared) have been selected. The selected study period covers since 2002/07/04 to 2017/07/25 (5501 days) that was exploited from NASA web site. These data are errors in the range between 5% and 10% (Kaufman & Gao,2003). The spatial resolution of the PW data are 1 km and temporal resolution is twice per day. Then using functions, these data converted from Level_2(swath data) to Level_3(grid data) and PW values interpolated on sinusoidal grid in 1800×2700 matrix with 1 km spatial resolution and daily temporal resolution. These data have been extracted for pixels within the political boundary of Iran and obtained a matrix with 1884080 rows (locations) and 200 columns (PW classes). Then on the base this matrix, calculated frequency distribution in 1 mm intervals from 0-199 mm for each of pixels (1884040×200). Finally, Principal Component Analysis (PCA) performed and frequency distribution patterns in Iran identified. The effects of altitude and distance to sea on these patterns, analyzed. The special program was developed and employed in MATLAB software for analysis the data.

The spatial distribution of atmospheric humidity in Iran is controlled by the height above the sea level, distance to sea and moisture advection. Based on the results, the mean annual PW of the country is about 12 mm. PW is maximum near the southern and northern coasts of the country. The highest and lowest amount of PW near the Oman sea coast (31 mm) and the peak of Damavand (3 mm), respectively. The results of PCA showed that 95% of spatial variation of PW can be explained through 4 components. Based on the results, local factors like distance to sea and altitude are the most important in spatial distribution of PW. The study of the relationship between distance from the sea and frequency distribution patterns of PW shows the effect of distance and proximity to the sea in the frequency distribution patterns. This fact is more evident in the first and second components. Up to the distance of approximately 250 kilometers in the first component and 150 kilometers in the second component, as expected, the amount of PW will gradually decrease. From now on, the spatial pattern of PW is affected by altitude and morphology rather than by distance from sea and sealand breeze. In the third component, due to the formation of a moisture convergence belt at approximately 11 and 4 km, respectively, on the south and north coasts, the amount of atmospheric moisture is maximum. Then from 11 to 66 kilometers due to the Alborz Range, which is a short distance from the Caspian Sea, the amount of PW is minimal. Minimal atmospheric humidity on the southern coast occurs approximately at 250 kilometers away from the sea. In the South Coast, moisture penetrates the country further away from the coast, as it is smoother than the North Coast; so that sea moisture enters through the straits of Kahnouj area into the Jazmourian plain and distinguishes this area from its surrounding areas in terms of moisture. Moisture in the Caspian Sea enters the Tarom Valley through the Manjil Strait. The spatial distribution of moisture in the western, middle and eastern Persian Gulf coasts does not have a similar pattern; this difference is due to factors such as the dominance of the sea-land breeze in the eastern areas of Bushehr and the presence of small firth and bays in the area that increase the atmospheric moisture of these areas. than the environment around them. The amount of moisture in the coast of the Oman Sea is clearly different from PW of the Persian Gulf; PW MODIS is also overestimated in places such as near beaches with high temperatures and humidity.In addition to the height above the sea level and distance to sea, the role of moisture advection should not be ignored. In the coastal region the variability caused by the high temperature and moisture advection and in areas far from coastline, height above the sea level causes many spatial differences in moisture distribution.

Although Iran is bounded from the north and south to the sea, atmospheric moisture is very low in the country. Based on the result, minimum and maximum difference of PW is about 27 mm, so that, in the region with more than 3000 m elevation PW is less than 6 mm, and the coast of the Oman Sea 60% of the time is above 26 mm. This result means, in spite of the great source of water in south and north, atmosphere of Iran suffers from poor moisture. Topography is a barrier to the entry of moisture north and south seas to the inland. In the inland region, altitude and in the coastal region, moisture advection and temperature, play crucial role in frequency distribution of PW. In this way, moisture advection is the important factor that well justified spatiotemporal variations of PW in Iran and through this, affected on water budget.

The impact of the dust phenomenon in Iran is so great that it has involved more than half of the country's provinces in some way with the problems and limitations of this natural phenomenon, which in addition to environmental impacts, has disrupted the implementation of sustainable national development plans and so far it has had and will have many negative consequences. The increase in dust storms in recent years in the east and southeast of the country, especially in Sistan and Baluchestan province, and consequently the decrease in air quality in these areas, has doubled the importance of Forecasting this phenomenon. On the other hand, most domestic studies in this field are related to the process of small-scale dust phenomena, synoptic studies, and its satellites. Therefore, considering that this phenomenon has had adverse effects and negative consequences in the social, economic, and health fields of the people, it is necessary to study, forecast, and measure its relationship with climate variations.

This study aimed to compare the performance of SARIMA and Holt-Winters time series models with artificial intelligence methods including neural networks based on radial base functions (RBF) and adaptive neural-fuzzy inference system (ANFIS) to forecast the frequency of dust storm days (FDSD) in the next season. For this purpose, hourly dust data and codes of the World Meteorological Organization were used in five synoptic stations in Sistan and Baluchestan province with a statistical period of 25 years (1990-2014). The observations of meteorological phenomena are recorded once every three hours, a total of eight times a day. In these observations, the visual phenomena of climate are defined according to the guidelines of the World Meteorological Organization in 100 codes (00-99), in which 11 codes are used to record and report the phenomenon of dust in different meteorological stations. Following the time series of days with dust storms, the FDSD index was forecasted using four methods SARIMA, Holt-Winters, RBF, and ANFIS.

According to the results of the time series, the FDSD index in Saravan, Khash, Iranshahr, and Zahedan stations has relatively small variations that are scattered throughout the time series, but with the increase in the number of dust days in Zabol station, the scattering of the variations has decreased and its intensity has increased. Also, the peak values of dust are concentrated next to each other, which indicates the occurrence of successive dust storms in this station from 2000 onwards. As can be seen in the ACF and PACF diagrams of the studied stations, significant time intervals indicate the correlation between the time values that make it possible to modeling and forecasting future values (next season) of the FDSD index for all five stations studied. According to the functions of partial autocorrelation and autocorrelation, the range of change of attraction and the moving average was determined, and using the appropriate evaluation criteria, the best time series model was extracted for each station. In the Dickey-Fuller test, the significance level was considered to be P-Value < 0.05. According to the test, only the time series of Zabol stations is unstable, which confirms the results of the ACF and PACF diagrams of the studied stations. The results showed that the ANFIS method performed better than other methods in all study stations; So that in this method, the evaluation criteria of R, RMSE, MAE, and NS are varied from 0.72, 0.57, 0.42 and 0.71 to 0.95, 0.51, 0.40 and 0.96, respectively. Also, the average frequency of days with dust storm on a seasonal scale in the studied stations varied from 1.06 to 7.11, respectively, so that with increasing FDSD index in the stations, the forecasting accuracy of all methods increased. In the SARIMA time series model, the correlation coefficient (R) between the observed and forecasted values of the FDSD index was increased from 0.64 to 0.79. For Holt-Winters, RBF, and ANFIS methods, the R-value also varied from 0.70 to 0.87, 0.69 to 0.92, and 0.72 to 0.95, respectively. Also, based on the results of the observed and forecasted values, with the increase of FDSD index in the studied stations (progress from Saravan station to Zabol station), the relationship between observed and forecasted values in all methods (time series models and artificial intelligence methods) find more compatibility with the Semi-constructor of the first quarter. The results of the Z test also showed that the assumption of zero-based on the mean equal of the time series of observed and forecasted values of the FDSD index, in none of the studied stations based on ANFIS and RBF methods at 1% error level and based on SARIMA and Holt-Winters time series models are not rejected at the 5% error level.

The results showed that with the decrease in the frequency of days with dust storms in Saravan and Khash stations, the Holt-Winters time series model showed almost the same and higher performance than the RBF method, which indicated the high capability of this model to forecast low values FDSD index. The results also showed that the SARIMA time series model compared to other forecasting methods did not have a high ability in forecasting the FDSD index in any of the studied stations. Also, despite the low frequency of days with dust storms in Iranshahr station compared to Zahedan station, all FDSD index forecasting methods have better performance and more accurately than Zahedan station based on evaluation criteria, which can be searched due to the presence of a complete series without FDSD index termination at Iranshahr station. The results of this study can be useful in forecasting and managing the consequences of dust storms in the study areas. On the other hand, in forecasting the FDSD index in Sistan and Baluchestan province, the optimal predictor model has been complex. For all of the stations studied, the model that used three or four steps of the predictive delay was recognized as the best predictor model. Therefore, particles leftover from previous storms could be an important reason for the impact of the last few seasons’ storms on the formation of dust storms in future seasons.

One of the most important planning tools for timely supply of crops, especially the strategic wheat product, is to predict the performance of this product before harvest, which can be very important in planning for itself. Combining the results of observations and ground measurements with remote sensing techniques can be widely applied in all agricultural sectors and facilitate the access to precision farming. Agricultural products have always been associated with the risk of fluctuations in the climate and changes in international markets, although this risk is never completely eliminated, but it can be understood by identifying the various parameters affecting plant growth and estimating the amount of the product Before harvesting, they minimize them. The forecast of rainfed wheat yields as a strategic product, with the Earth's population reaching 7 billion now.

Field data includes biomass and net weight of wheat produced per farm in kilograms. These data are obtained by direct field surveys during harvesting. The GPS was used to determine the total area of the land, and considering the time zone of the crop, the Landsat-8 satellite time series was used from mid-February to late May in the studied years. After performing the necessary pre-processing on the images, the images were classified using a multi-timed classification. Initially, both NDVI and LAI indexes were obtained for all images in each ENVI environment every 5 years. Finally, the phenolic curves of both indices for each plot of land were fitted for each year from the studied years, which cultivated the wheat field, and the time of each phonological step was obtained for the studied area.

In order to evaluate the overall accuracy of the classification, the Kappa coefficient and overall accuracy for the classes defined separately were calculated using the classification error matrix. According to the phenological diagrams, the parameters of the area under the charts of both indicators were calculated for all lands. According to the phenological diagrams, the parameters of the area under the charts of both indicators were calculated for all lands. For this reason regression relations and determination coefficients (R2) between indices and wheat and biomass were created. For this reason regression relations and determination coefficients (R2) between indices and wheat and biomass were created. In this study, both indicators were affected by the multivariable regression of the product estimation, and the highest coefficient of determination was obtained for each of the indices alone. From the 5 phonological stages, the inflorescence stage with R2=0.65 has the highest correlation coefficient.

From the obtained coefficients, we conclude that GLAI or green leaf area index (absorption) has a higher coefficient than NDVI. GLAI, which represents the main part of the photosynthesis of the plant (leaf), which is the main factor in the production process in the plant, certainly has a greater impact on the plant's production process. This leads to the preference of this index for the NDVI for estimation, but since the main goal of the paper is to obtain a multivariate regression relationship, we can do this in addition to the effect of both the desired index, the coefficient of determination and continuity For each of the indicators, we increase individually and make estimates in the region more accurately. With the involvement of both indicators in our relationship, we obtained a significant coefficient, especially for biomass with R2=0.865, which ensures that our prediction values are close to real values and that the program On the basis of this estimate, the probability of success will be high. From the study of phonological stages with wheat yield, we also conclude that, firstly, the entire phonological stages have less regurgitation coefficients than the phonological graphs of the two vegetation indexes, which means the whole diagram of wheat growth stages relative to the phenological periods on these graphs Have more ability to estimate the yield of wheat. Two of the five phonological stages studied, the inflorescence formation stage with R2=0.65 the highest correlation coefficient. This step in time is about the peak of the graph or the maximum value of the phonological graph.

Over the last decades, urbanization developmenting and weakness in accurate and comprehensive planning to develop and rapid population growth have caused many challenges for cities. Urban sprawl beginning in the developed countries around 1950 is currently experienced in almost all countries. Many studies on the effects of urban sprawl indicate the emergence of harmful effects of this phenomenon. One of the most important environmental effects is the changes in climate. Most urban settlements are prone to future shocks and tensions due to climate changes, lack of energy and global population growth. Urban managers and planners’ responses to these shocks and what cities should do to adapt to accidents and dangers are now discussed in “resilient cities” topic. Many cities have not yet addressed climate risks due to lack of relevant city policies and action plans, outmoded regulations on urban planning, lack of capacity to respond to climate disasters, and lack of public awareness. The Urban Climate Resilience practice area represents the intersection between WRI Ross Center for Sustainable Cities and World Resources Institute’s Climate Resilience Practice. The urbanization trends in Iran during last decades had been accelerated by high rate of rural-urban migration along with rapid socio-economic and political changes that formed unbalanced urban growth in Iran. Since resilience refers to the ability of a system to return to its natural conditions after an accident, the purpose of the present study is to test and evaluate the level of resilience of Varamin City in the face of climate changes from its citizens’ viewpoint. Materials and

In the present research, two types of data have been used. The first type of data includes the climate components gathering the Varamin weather station (annual average rainfall, temperature, etc.). The second set corresponds to components relevant to urban sprawl, among which, urban area, population density and urban population. These parameters were obtained by questionnaires which have been filled out by varamin citizens. This descriptive analytical study was conducted with the participation of 393 citizens of Varamin City. The research tool used for data collection was a 35-item researcher-made questionnaire based on previous studies containing the appropriate items to test each of the components. To conform to the research population, the questionnaire was investigated and reviewed by professors and experts in multiple steps and its face validity and content validity were confirmed. In order to assess the reliability of the questionnaires, first, 30 copies of the questionnaire were completed by the citizens of Varamin in a preliminary research. The obtained information entered SPSS 21 and each response was assigned a score of 0-5. After the analysis, the reliability of the questionnaire was estimated by Cronbach’s alpha to be 0.89 that was designed based on the environmental, socio-economic, infrastructure, and institutional components. Analysis and prioritization of the descriptive and inferential analytical statistics the resilience of each of the components and their indices were calculated by SPSS 21 using the one sample T-test and then they were prioritized by Friedman test.

Today, the relationships between human societies and their natural environment has been strongly affected by urbanization and urban development. Cities can be considered as ecological units and studied within the framework of a data-retrieval system. That is, to meet various needs of citizens, the city needs inevitable to provide massive data in key inputs, the most important of which are energy, food and water. Results of measuring resilience of Varamin City with an emphasis on climatic aspects showed that from the citizens’ viewpoint, the resilience was 2.15, which was lower than the desirable average level. It indicates that the citizens consider Varamin vulnerable to climate hazards. Results of investigating resilience components of Varamin City showed that the environmental component and its indices were lower than the average level and according to the citizens intensified drought and changes in temperature have the most negative effects on the environmental condition of resilience in Varamin City. Moreover, according to the citizens, Varamin City is vulnerable to the increase in temperature and drought and these two indices need to be taken into consideration to increase the urban resilience. Although, they believed that the socio-economic and infrastructure components had higher resilience levels compared to the environmental and institutional ones. The socioeconomic component and most of its indices were above the average level and according to the citizens, helping the citizens in case of critical situations and kinship are most significant in the socioeconomic resilience of Varamin City when faced with climate changes. Results of investigating the infrastructural component showed that this component and most of its indices were lower than the average level. Therefore, it can be stated that this city is not in a good condition in infrastructural aspect and is vulnerable in this regard. Furthermore, according to the citizens, the index of “access to health centers” was the most significant infrastructural index. Investigation of the resilience level of the institutional component, it was found that all the indices of the institutional component were lower than the average and the scores of Friedman Test showed that from the citizens’ viewpoint, the municipal services in creating green space and satisfaction from the performance of the organizations in charge of informing to face hazards had the highest significance in the institutional resilience of Varamin City. Although apart from the socioeconomic components, other components in the present study were lower than the average level, since the environmental and institutional components were the least resilient components, respectively, strengthening them should be placed in the priorities of the urban development plans of Varamin City.

Since climate change and its effects are increasing more than before in human societies, especially in urban communities, investigation of the indices ad components of resilience and evaluating them when urban communities face future climate crises and preventive measures are very effective and essential. Furthermore, the increase of the general knowledge regarding the climate changes motivates people to investigate the effects of this issue even more. Therefore, the serious cooperation of the government, local entities, educational organizations, municipal and media in increasing the citizens’ awareness will make the citizens respond significantly to reduce and adapt with the consequences of climate changes through citizen participation.

Roads are part of the development of civilization and support economic activities and the foundation of new life, but unfortunately in the last decade due to low driving culture, non-standard vehicles and roads, environmental factors and increasing traffic volume, number of road accidents increased dramatically. Four human factors, vehicle, road and environmental factors, are always involved in the occurrence of accidents, among which environmental, climatic and climatic factors that occur due to the special geographical conditions of Iran and its mountainous nature, along with other factors play a significant role in accidents. Major road meteorological tasks include continuous preparation of statistics and information, Changes and evolution of meteorological elements in the area of roads covered by the relevant station, Issuance of specific meteorological forecasts along the route in relation to wind intensity and speed, Various storms with lightning and the occurrence of destructive phenomena, Publication of notices and warnings in the event of dangerous weather phenomena on the way, Wind intensity on various stairs and phenomena that are effective in reducing vision, Land and rail transportation is one of the most important issues at the national level. The aim of this study is to locate the meteorological stations of the Alborz mountain axes (Chalous and Haraz) using the Location-Allocation method.

The present study is conducted in the mountainous roads of Alborz (Chalous axis and Haraz axis). Criteria used to locate road meteorological stations include climatic (rainfall of more than 30 mm, avalanche, snow cover, fog, minimum and maximum temperature of -10 and 30 degrees Celsius), geomorphological (rock fall, Landslides and active faults), traffic (accidental points and environmental criteria) and economic-security (traffic). Then, using the Analytical Hierarchy Process (AHP) method, based on the determination of the variable comparison matrix and weighting of each criterion, the final prioritization map is prepared according to the final weight. In the following, based on the Location-Allocation analysis, the proposed meteorological stations on the mountainous axes of Alborz will be determined.

The three meteorological stations of Karaj (from Karaj to km 43), Siah Bisheh (km 43 to 110) and Nowshahr (110 km onwards) reflect the climatic conditions of each section. The number of days recorded for the occurrence of fog at Siah Bisheh station is approximately 844 days in 10-year statistics. Nowshahr and Karaj stations had 70 and 50 foggy days, respectively, in the study of available statistics and information. Therefore, the approximate kilometer of 43 to 110 km in terms of the phenomenon of fog, according to the statistics of Siah Bishe station, has the highest probability of fog days. 60 to 100 km from the beginning of Karaj (middle part of the axis) has a high risk of frost. From the beginning of the axis to 60 km and the approximate area between Vali-Abad and Marzanabad, the risk of frost is moderate. In other parts of the axis, the intensity of frost in the classroom is low and very low. Chalous axis in Mazandaran province from the approximate area of Vali-Abad village to Chalous city includes high and very high risk classes in rainfall of more than 30 mm and Chalous axis in Alborz province experiences low rainfall risk conditions.Due to the minimum threshold temperature in the middle part of Chalous axis, which includes two provinces of Alborz and Mazandaran, it is in moderate danger. This part of the axis includes the range of Nesa, Gachsar, Siah Bisheh and Harijan. Other parts of the axis are in the low risk class. Also, due to the maximum threshold temperature in Chalous axis, the hazardous conditions of the axis in Alborz province are low and in Mazandaran province it is very low.Examining the average of snow cover by the desired months in this study, it can be seen that the middle parts of the Chalus axis experience the highest frequency of snowfall. As we approach the warmer months of the year, a gradual trend of snowmelt is observed. In avalanche risk, the area of Asara village has a moderate risk. The central sections range from Garmab village to Zangoleh bridge in high and very high classes. From the Black Forest area to the end of the Chalous axis, the avalanche falls to the low-lying class.Ranks 74, 78, 82, 84-85, 88-89 have been reported to be affected by the landslide phenomenon. In terms of point density, 78 km to Chalous in Mazandaran province have the highest amount.In sunny weather, km 20-17 and 41, in cloudy weather, km 62, during rainfall, km 40 and 70, in snowy weather, km 40, 60 and 62, and during foggy weather, km 60, 62 and 65 have been the maximum number of accidents.The importance of each of the criteria andsub-criteria was determined according to library studies, installation guidelines for road meteorological stations and expert opinions. The uncertainty coefficient was also 0.6, which is less than the defined 0.1, andaccording to this result, the weighting process is approved. According to global standards and studies conducted, the distance between meteorological stations on the road varies between 30 and 50 square kilometers. In general, each meteorological station can cover an area of about 30 km.Then, using AHP method, the final weight of climatic, geomorphological, traffic and economic-security criteria and sub-criteria in Haraz and Chalous axis were determined. After prioritizing the new stations in terms of need, in the last step, by analyzing LocationAllocation and examining the optimal distances of the axis from the highway, fuel stations, surveillance cameras and villages around the axis, the final stations in priority-oriented are introduced.

Due to the importance of optimal development of the road meteorological network, which reduces road damages and losses and destroys the surrounding environment and economic savings, the optimal location on the Chalous and Haraz axis was examined. The results showed that the required stations on Chalus Road are in the area of Kiasar, Marzan abad, Khargoosh Darreh and Vali abad and Haraz road are in the Polur, Abali, Rahdari and Rineh.

Heavy metals in dust particles play an important role in the contamination of agricultural soils. Heavy metals are one of the most dangerous pollutants in the environment due to their bioaccumulation power. That is, they are able to accumulate in the body system of living organisms and increase their concentration with greater exposure to pollutants. Heavy metals are generally referred to as a group of elements that having a specific greater than 6 g/cm3 gravity and greater than 50 g an atomic weight. The most important heavy metals that are important for environmental protection include cadmium, arsenic, cobalt, vanadium, zinc, mercury, iron, manganese, nickel, lead, chromium and copper which for non-biodegradability in nature and their long life span, they are important pollutants of the environment. Also pollution of agricultural lands with metals by chemical action such as sewage sludge, chemical fertilizers and industrial wastewater application, but deposition of dry and wet dust particles caused by the dust storm phenomenon is one of the most important sources of pollutants for wheat agronomic ecosystems to heavy metals. Pollutant of dust storm with heavy metals is considered a serious problem due to toxicity, degradability and cumulatively. Deposition of dust particles contaminated with heavy metals on crops land leads to combine with soil solution, and plants absorb the heavy metals, paving the main route of transfer of metals to the food chain. Deposition of dust particles with heavy metals in the soil of wheat agro ecosystems can endanger human health; then identification of heavy metals content in wheat fields is the first step in reducing the health risk that this research is trying to this goal.

In this study, the dust storm in the 16 year period (2000-2015) related to stations of Larestan, Jahrom, Darab and Fasa was obtained from the Meteorological Organization and analyzed frequency of dust storm in the seasonal and annual scales. Next, the dust particle entry pathway to the study area in the May 12, 2018 was performed using by HYSPLIT model. Subsequently, soil samples were taken from wheat fields of Larestan, Fasa, Darab and Jahrom. Four wheat ecosystems were identified in each study area and soil sampling was performed from a depth of 1 cm at 400 cm2 area in each wheat ecosystem. The soil sampling was divided two stages before and after the dust storm. Sampling was done before the dust storm in the months of December and March and after the dust storm in May and June. Soil samples were transferred to the laboratory and concentrations of lead, cadmium, and nickel were measured by flame atomic absorption spectrometry. Finally, the amounts of heavy metals in the soil samples were evaluated by the Igeo index.

The maximum frequency of dust storms in the southern part of Fars province is in the warm months, especially in spring, with an average of 18 dust storms per season. The minimum of this environmental phenomenon is in the cold months, especially in the autumn, which occurs less than once in the season. Also among the stations in the study area, Fasa station has the maximum of annual dust storm with 42 occurrences. Next, Jahrom, Darab and Lar stations are in the next rank with 39, 25 and 19 storms per year respectively. The path of dust particles entering the study area on 12 May 2018 was tracked using by HYSPLIT model backward method and results represented that deployment of thermal low-pressure in the Persian Gulf has led to instable of atmosphere and the shamal winds moved through the deserts of Iraq and Saudi Arabia to the Persian Gulf and it has caused a massive dust particles to be transported to the southern provinces of Iran. Also results showed that concentrations of lead and cadmium in the soil of wheat agronomic ecosystems of Fars province increased under the influence of dust storms; but the concentration of nickel remained unchanged. The highest concentrations of heavy metals were in the Darab and Lar ecosystems and the lowest were in the Jahrom and Fasa. The mean comparison test showed a significant difference between the concentrations of heavy metals in agricultural ecosystems in south of Fars province before and after the dust storm at 0.05 and 0.01 levels and dust storm led to increase the heavy metals in the soil of wheat ecosystem. Also, the land pollution standard showed that in the agricultural wheat ecosystems of Darab, the concentration of all metals was higher than the global limit and was in the moderate to severe pollution category. In this study, the effect of desert dust on heavy metal concentrations in soil ecosystems was investigated and their concentrations were measured before and after the occurrence of dust and their differences were compared with statistical tests. It showed that the concentration of lead and cadmium in the soil of wheat agronomic ecosystems increased under the influence of dust storms and nickel concentration remained unchanged.

In addition to combustion sources, industries and factories, traffic and the use of fertilizers and municipal wastewater, desert dust particles are also a contributor to air pollution and an increase in heavy metal concentrations in agricultural soil that can affect health. Damage the environmental ecosystems and organisms, especially humans, which are most consumed by agricultural soils and plants. Deposition of dust particles caused by dust storms in wheat cultivated soils results in increased concentration of heavy metals in the soil and its uptake by the roots of plants and its transfer to the crop which endangers for human health. Because wheat is one of the most consumed foods in the human body and the transfer of toxic and heavy metals through soil, roots and plants causes to accumulate in wheat. Therefore, in order to achieve world-class quality and health products, solutions must be provided to reduce the concentration of heavy metals in consumer products. The results of this study can be made available to planners and agricultural and health expert.

There are several fundamental issues in geomorphology. These include scale. There are a special relationship between landscapes and the components of their forms, which indicates a kind of scale continuity. These rules and scale relations prevail not only at the level of perspectives but also at the level of land forms, and due to the complexities of this concept in geomorphic studies, have received less attention. However, the accuracy of many geomorphic concepts is related to such concepts. Usually in scale geographic literature, a simple ratio is defined that is often used to represent the extent to which a phenomenon is reduced to its actual ratio in the maps but the reality is that scale in geomorphology involves a broad concept and any subject that expresses a ratio is in the conceptual realm of scale, and few geomorphologists have pointed to this important issue.The scale plays a vital role in geomorphology, both in the realm of performance and in the field of epistemology. For example, in the field of soil geology, the chemical processes of particles change with the reduction of dimensions to two microns, and the properties of their elements generally change and so in the geography of clays, which can only express the size of each substance (not their sex), chemical performance is doubly important many of the vital and mineral reactions in the soil depend only on the size of the elements, not the elements themselves. So in statistical analysis, relationship measurement, that is, correlation techniques, is one of the concepts of scale, because when you write a linear formula or other form of correlation, the ratio between the two variables is actually defined. Therefore, scale is one of the fundamental issues that, from a theoretical point of view, leads to the design of other concepts such as universality, fractal, river networks, geoallometry specific scale, and so on.

To achieve the advanced concept of scale in geomorphology, after a relatively extensive search of books and articles in this field, several geomorphological pioneers who used this concept in the field of scale in their work with a special theoretical innovation were selected . These seven were: John .Charles Doornkamp ، Geographer from the University of Nottingham, England
John Tilton Hack , American geologist and geomorphologist
Evans, a geomermologist from Durham University in the UK and a graduate of York University in Canada
Donald Lawson Turcotte , Geologist , Cornell university,USA
Benot Mendelobert, a French-American mathematician from Yale University
Dave Rosgon , hydrologist and geomorphologist from the Universities of Nevada, Montana and Colorado
Leila Goli Mokhtari Geomorphologist from Sabzevar University, Iran
Then, by selecting the books and writings of these researchers in this field , began to study, separate and classify their opinions then repetitive content, sometimes shared by them, was removed. In the final stage, began to extract new found writings that were specific to each of them, and their content was summarized and analyzed as an opinion.

In the first step of the research, the most important result that has been achieved in terms of time is the way of developments and the volume of work that has been done in this field. Review of the researchers' scientific papers shows that studies of the scale of the trend have increased in the last 30 years and theoretical innovation in the application of this concept has become increasingly complex. In The second step in the importance of thematic classification of the opinions of the seven researchers was a semantic difference with the subject of the scale. Although all the writings can be called scales, but the novelty of the work of these seven researchers were that they presented completely different and original interpretations and concepts. For example, the specific scale of Evans' innovation , Invariance scale of turcotte or geoallometry of Golemokhtari's theoretical innovations. With these initial achievements, the views of these seven researchers are now described and analyzed.

Scale in general is called the actual size of a phenomenon in geography which is usually shown as a deduction or as a line. Fraction in numerical scales can be expressed with a fixed face and multiple denominators Such as maps 1:50000, 1:250000 and so on. Another pattern of scale display is expressed by showing a fraction with a different face and a fixed denominator, which is called gradient, such as two in a thousand or five in a thousand …. , the ratio in geometry is expressed as an angle and is called a tangent.
In the last three decades, geomorphologists and related sciences have been able to apply some of the complex concepts of scale in their work that named with specific titles. These concepts include Universality scaling, which is due to hacking, and the concept of "specific" which is due to Evans' work. Turcotte defines the concept of Invariance scale (meta-scale) and Mendelobert's fractional scale, Rosgon, the thematic scale and Goli Mokhtari , can be considered the creators and determinants of scale in geoallometry.
Finally, it can be said that each researcher has presented different concepts in the discussion of scale but the common matter between these researchers is the deeper understanding of the importance of the earth and the phenomena of geomorpholog and it must be confessed that the depth of their understanding of geomorphology has played a leading role in their theoretical inovation.Finally, it can be said that each researcher has presented different concepts in the discussion of scale but the common matter between these researchers is the deeper understanding of the importance of the earth and the phenomena of geomorpholog and it must be confessed that the depth of their understanding of geomorphology has played a leading role in their theoretical inovation.Finally, it can be said that each researcher has presented different concepts in the discussion of scale but the common matter between these researchers is the deeper understanding of the importance of the earth and the phenomena of geomorpholog and it must be confessed that the depth of their understanding of geomorphology has played a leading role in their theoretical inovation.

Mineral dust is the aerosol mostly affecting directly and indirectly radiation budget, temperature change, cloud formation, convection, and precipitation. In two recent decade, new sensors and models became available allowing new research activities on dust. Important studies considered atmospheric optical depth (AOD) as the key parameter for remote sensing and modeling of dust. The available model, satellite and ground-station datasets have been used to detect and characterize mineral dust phenomenon in affected regions and dust sources. Nonetheless, regional classification over the entire Iran using remote sensing parameters is still lacking.

The present study aims to model and detect homogeneous areas of high dust concentration in Iran using dust AOD at 550 nm from the MODIS satellite Aqua and Terra sensors (2003-2012) with a spatial resolution 14 km2.
Among vector techniques, S-mode application as a principal component analysis (PCA) or empirical orthogonal functions (EOFs), is the most applicable and controversial method of classification for achieving the study target. The S-mode analysis is applied to the matrix made of the satellite observations at regularly spaced grid points of daily AOD values during the deacade 2003-2012. The S-mode analysis is applied to identify the geographycal distribution of high dust concentrations. PCA of the n x m matrix is applied and the scree test and North's rule were used to cut-off the statistically relevant components to be kept. Finally, in order to determine the best theoretical representation of the data, physical relationships embedded within the input matrix and localize the territory to simpler structures, specific modes of the residual components rotated by varimax. Varimax rotation means that each component has a few large loadings and many small loadings, and this assists in the process of interpretation if the results are due to the high values of explained variance. The rotated patterns, however, illustrate the simpler, more interpretable, and rational structures of mineral dust as principal modes. The identification of sub-regions and extreme dust loading was carried out using dust AOD values assuming the arbitrary thresholds of 87 percentile of and 95 percentiles, respectively. Therefore, the first threshold was used to determine sub-regions; consequently, the regions will have zero overlapping. The second threshold, used to extract the days with extreme AODs of each region. Herein, the Kolmogorov-Smirnov (K-S) test was used to infer whether the regional mean time series PCs of each different sub-region were statistically different.

The spatial map-patterns of dust, accounting 91% of AOD variability, have been divided into six subregions on Iran, which are the major centers affected by the dust. all of the sub-regions coincide with regional map-patterns depending on the distance and proximity to the dust source around the territory. Therefore, overlaping of identified dust areas related to dust extremes in each of Iran’s regions showed that the dust dominant patterns of Iran are under infuence of expansion and growth of dust extremes. The geographical location of sources areas and the special dynamic conditions over the mid-eastern atmosphere of Iran have been influenced by severe storms originating from the Karakum Desert. The northeast region is influenced by the dust plume originated from the Karakum Desert to Tabas Desert, which located in the southeast of the Kavir. These results showed that ground-based station studies, albeit long-term, have not been able to detect the northeast region as a distinctive region under infuence by southward dust plume.The same is true of the Central plateau, East and Southeast regions. In return, more focus was been on role of 120-day winds as a main cause of dust transport. Considering the mentioned reasons, previous studies have not divided borderline regions across Iran. Meanwhile, Weakness and intensity of dust-affected areas showed that the multiplicity and adjacent of dust flow to the southeast and east of the country are different and play a decisive role in the formation of east and southeast subregions. The shortcoming has also been observed for the west-northwest and southwest regions. In a case study (by horizontal visibility), were not only able to distinguish the dusty subregions because of limited observations in the interested area, but also could not analyze the identified subregions based on coressponding seasolality and extremes, which identified by 95 and 87 percentile in each of region, respectively. The detected extremes showed that identified sub-regions are function of the volume, growth and expansion of dust particles originated from the dust source regions across the Middle East and southwest Asia. Finally, the classification techniques showed that technical conversion of a dynamic phenomenon such as dust into simpler and more meaningful physical structures reveal geographically a simple and interpretable understanding of dust distribution in the territory of Iran. Morever, the use of remote sensed data utilized in the present study highligted the sub-regional distribution of dust over Iran that was neglected by previous studies providing a decription of a dynamic process that is complementary to the ground-based observation analisys. In some cases, a day event only based on ground-based observations may have had a high dust AOD with very horizontal visibility that has been ignored due to the level height of the dust layer. Therefore, the used technique integrates the knowlegde of dust based on grounded-measurement providing a large scale view of dust advection and diffusion.

The study results show that extraordinary dry conditions inside Iran combined with outside dusty sources have caused the country to be influenced by the high mineral dust aerosols. In addition to the domestic sources of dust, the study highlights that the mineral dust conditions in Iran are influenced by several arid and semi-arid sources beyonds its boundaries acting as dust sources. The subregions that form the spatial patterns of dust distribution in a six-distinct region of northeast, west-northwest, southeast, southwest, central and eastern of Iran are affected by the high dust aerosol optical depth (AOD) and are major centers of activity and high gradient areas (regions affected by dust) that follow trend distinctive seasonality. This has been able to illustrate identified sub-regions’s seasonalities and regional extremes by remote sensed data of atmospheric optical depth.The study results highlight that dust dominant spatial patterns of Iran are function of growth and expansion of dust extremes originated from source regions in the Middle East and southwest Asia. As a result, the present study showed that technical conversion of a dynamic phenomenon such as dust to simpler structures led to interpret geographically dust distribution.