نشریه جغرافیا و مخاطرات محیطی
پیاپی 19 (پاییز 1395)

Long-term climatic data are a prerequisite for hydro-meteorological studies and understanding of past climate. Iran is mostly located in semi-arid to arid climate zones, so information on the natural long-term variability of the hydroclimate is of great relevance for land use planning, agriculture, and water supply of a growing population. However, the maximum length of recorded climate data in Iran is less than 60 years, measured at less than 50 synoptic meteorological stations. Therefore, knowledge of the climate history in the distant past requires reconstruction of climate variables from proxy data. Tree-ring data are an important and precisely dated proxy to reconstruct variations in hydroclimate, especially in climates where tree growth is mainly limited by moisture availability. Juniper trees due to high survivability and high sensitivity to weather conditions are suitable tree species for the reconstruction of past climate. The present study is the first effort to reconstruct local precipitation in the northeast region of Iran from tree-ring data of Juniperus polycarpus.
Study Area: The tree-ring sampling site is located in the Hezarmasjed heights (Lain region) of Khorasan Shomali Province, northeast of Iran (37 N; 59° 21 E) at an altitude of 2100 MSL. The climate of the region is cold and semi-arid. Climatic data are prepared from meteorological stations and global data networks (NCEP-NCAR) with resolution of 2.5*2.5 deg. with the common period of 1949-2000. In order to understand regional variation rainfall, the average precipitation of six points from NCEP-NCAR network was considered as regional precipitation data. The chronology of tree ring width is developed from 16 increments of Juniper trees. To remove the biological age trend in ring width of data, a double de-trending procedure was applied to all series by using the ARSTAN program.
Material and In this study, the influence of temperature, precipitation and PDSI on tree ring width of Juniperus trees based on station and global network data was investigated and annual precipitation of northeast of Iran was reconstructed using the Juniper chronology in the period 1845-2000. A simple linear regression was employed to reconstruct precipitation. The reconstructed results were compared with recorded data of four long-term stations and also their correspondence with historical famine reports and the reconstruction results from neighboring countries (east and west) was investigated.
The results showed that tree ring widths of Juniper trees have positive correlation with temperature of pre growth December and negative correlation with temperature of May, significantly. Also precipitation in all months of growth season has positive effect on tree growth and annual rainfall has the highest correlation with tree ring widths. So average rainfall of northeast Iran from six points of global network data was calculated and using Juniperus chronology was reconstructed in 1845-2000. Correlation coefficients of calibration and evaluation periods were significant ... .

In recent years, regarding climate changes, the analysis of natural variability of climate at different time scales has attracted a lot of attention. While, the data series with short statistical period just shows a likelihood estimation of a few decades of climate variability, the data series with long period shows the fluctuations of several decades with statistical importance from climate variability with heterogeneous spatial pattern. Multiple activities occur in the sun surface such as flares, explosions, and solar wind, which result in increasing the plasma displacement and increasing radiation intensity subsequently. Oscillations and climate changes associated with these activities play a major role in the living conditions and life on the earth. The changes of output energy from the sun or its temperature oscillations can cause the changes and oscillations on the earth atmosphere. Sunspots, as an activity of the sun, is a phenomenon that in recent decades has attracted the attention of climatologists and is known as one of the options that can affect the planet's climate in different time scales and leads to the oscillations and changes in climate at last. The concept of wavelet in today's theory was proposed by Johnson Morlet, the French geophysicist. In this method, the problem of dividing the signal into different sections is solved using scaling and transferring a function. This function is transmitted during the data series and for each position the whole data series is calculated. It is repeated for functions with different scales. Studies performed in and out of the country indicated the significant effect of the sunspots on atmospheric parameters. These studies showed that by increasing the sunspots, the amount of rainfall and temperature will be increased as well and vice versa; i.e. by reducing the sunspots the amount of these parameters will also be reduced. However, wavelet theory is a topic in pure mathematics but what is discussed here, is its practical aspect. The main objective of this study is to determine the effect of sunspots on temperature changes occuring in Kerman and Shiraz stations using wavelet theory. The reason of using wavelet theory in this study is that wavelet transform needs a lower volume of calculation than Fourier transform.
Material and In this research, Shiraz and Kerman stations located in the southern foothills of the Zagros were use. The reason for using these stations is their temperature oscillation over the last few years, and also estimating the effect of sunspots on the temperature of the two stations through wavelet analysis. We examined the effect of sunspots on temperature changes in this study. Because of the need for the long-term data to do this, just the two stations of Shiraz and Kerman were studied. The data related to the sunspots were provided from the American Geophysical Union for a statistical period of 60 years (1950 to 2010), and the temperature data for the two mentioned stations were provided for a statistical period of 60 years (1950 to 2010). To do this study, the researcher benefited from statistical analysis and wavelet analysis using MATLAB software. Sunspots are the most important indicator of variability of the solar radiation; so that in the majority of studies the relative number of sunspots is mainly used for analyzing the sunspot changes. In the present study, the annual, seasonal, and monthly averages of the sunspots during the statistical period of 60 years (1950 to 2010) were used. The data related to the spots were provided from the American Geophysical Union. Annual, seasonal, and monthly data related to the temperature parameter for the statistical period of 60 years (1950 to 2010) were provided from Fars and Kerman Meteorological Bureaus, and for examining the relationship between temperature and sunspots wavelet analysis and statistical analysis were used. MATLAB software was used for programming. Then wavelet of Morlet was chosen as the mother wavelet.
Based on the wavelet analysis, it was obvious that during all months of the year sunspots activity left behind an 11-year-old cycle. Of course, in different months, extremes of activities and fluctuations period are different. Observing plotted wavelets for different months of the year, we can see during the statistical period of 60 years there are 4 cycles in the sunspot activity that the intensity of activity differs in each of the cycles, so that as seen in most months the first and fourth cycles have the least activity. Of course, there are also expectations such as December in which regular fluctuation is seen in different cycles. In terms of duration, the longest cycle of sunspot activity is the first cycle that lasts for 12 years. However, in the third cycle, which the intensity of the sunspot activity reaches a peak, the sunspot activity lasts for 10-years. Between the sunspots and the average temperature of Shiraz there is an inverse relationship in most months of the year and this relationship is significant only in February. These results show that the relationship between temperature and sunspots is mostly significant in South East and East of the country. With an increase in sunspots, the temperature of the mentioned months decreases. And there is not a significant relationship between the temperature of Shiraz and sunspots in most months of the year during the seasonal and annual time periods other than fall. In the other time periods the relationship between temperature and sunspots is inverse and this relationship is also significant in winter. It means that with increasing the sunspots activity the temperature of Shiraz station will be decreased and vice versa. The results gained from Kerman and Shiraz can be compared, so that in Kerman station during December, January, and April a direct relationship is observed between the raising of temperature and sunspots activity.
Sunspots are the most important indicator of variability of the solar radiation; so that in the majority of studies the relative number of sunspots is mainly used for analyzing the sunspot changes. In the present study, annual, seasonal, and monthly averages of the sunspots during the statistical period of 60 years (1950 to 2010) derived from the American Geophysical Union was used and annual, seasonal, and monthly data related to the temperature parameter for the statistical period of 60 years (1950 to 2010) provided from Fars and Kerman Meteorological Bureaus. In order to examine the data, wavelet analysis and statistical analysis were used. Monthly, seasonal, and annual correlations of temperature with sunspots in Kerman and Shiraz stations indicates that in most months and in the studied timescales there is not a significant correlation between temperature and sunspot activity, and coefficients gained from Pearson's analysis were mostly negative and reflect an inverse relationship between the two variables. Means, with increasing the sun activity temperature will be decreased. Only in February a significant and inverse relationship is visible between the two parameters. Observing plotted wavelets for different months of the year, we can see during the statistical period of 60 years there are 4 cycles in the sunspot activity that the intensity of activity differs in each of the cycles. Most cycles observed in different months of the year are 5 and 7 years, and it is in March and June that the scope of the cycle reaches to 15 years, and in February which a significant inverse relationship is observed with sunspots activity including the maximum cycle with a 20-year period.

Since precipitation and its changes in each geographical area and also east coasts of the Caspian Sea make changes in human life and human activities directly or indirectly, this study wants to determine synoptic and dynamic patterns during precipitations and also appoint the resource of extreme and widespread precipitations in east coasts of Caspian. In this line, much research has been done in Iran and around the world. In the case of research done outside Iran, one can mention Lana&Borghino (2000), Huos et al (2008), Federico et al (2008), Keables (1989), and Lorenz et al (2008). In Iran, we can nameLashkary (1996), NajarSaligheh (2001), Khoshhal (1997), Mohammadi (2012), Bagheri (1993), Hosseini (2009), Azizi and Samadi (2007), Mofidiet, Zarrin and Janbaz Ghobadi (2008), and RezaiBanafshehet, Najafi, Naghizadeh and Abkharabat (2015).
Material and In this research, for synoptic analysis of extreme and widespread precipitations in Caspian eastern coasts, we interpolated and traced the daily Isohyet maps from 1340.1.1 to 1383.11.10 (15992 days) on the 14*14 km pixels by Kriging method and by use of daily precipitation data base of this region. These data provided the information of 108 studied local points for 15992 days to calculate maximum precipitation and area percentage under precipitation for every precipitation day. On this basis, we identified the most extreme and the most widespread of region precipitations on the basis of 99th centile base index for studying and analyzing. By applying environment – circulation approach and agglomerative hierarchical cluster analysis by "ward" method on the maps of sea level pressure, maps of the atmosphere thickness at levels of 500 and 1000 hPa and maps 500 hPa circulation patterns, circulation patterns which were effective and important for creating the extreme and widespread precipitations of Caspian eastern coasts. In continuation, for analyzing the precipitations in every pattern, the representative day defined on the basis of correlation coefficient with 95% threshold and in these days, sea level pressure maps, atmosphere thickness in 500-1000 hPalevels, 500 hPa circulation patterns, functions of frontogenesis for 500 and 1000 hPa levels and moisture convergence flux for 925 and 1000 hPa levels were traced and analyzed.
The results of this research in the five patterns of sea level pressure indicate the presence of high pressure on the Black Sea that it’s tongue have been extended to Caspian coasts. Atmosphere thickness patterns indicate the deep trough on the Caspian Sea and Black Sea too. The analysis of frontogenesis function maps illustrate the existence of front on high latitude and Siberia that have had effect on studied area. The analysis of moisture convergence flux indicate that Caspian Sea is the most important source to providing humidity for precipitation in eastern coasts of this sea, and Aral Lake and Black Sea are in the next importance degree. Of course, mostly, the atmospheric flows importing the humidity of these two source in to the Caspian Sea that higher reinforcement results in occurring the extreme precipitation in eastern coasts of this.
The analysis of sea level pressure maps in extreme and widespread precipitations days, shows five patterns. In these patterns we can see depressure condition with high pressure dominance in the north of Iran and low pressure dominance in the south of Iran. Although frequency of the 5th pattern in more than others, the maximum of precipitation is seen in pattern number 2. The precipitations of the region begin from Ordibehesht and continue until Dey. The temporal peaks of precipitation are in Mehr, Aban, Shahryvar, and Azar. The patterns that are drawn, show high pressure systems on east-north of Iran and the Black Sea in all patterns, which enters cold air to the Caspian Sea from Siberia and Europe, and with the humidity of the sea, enters them into east coasts of the Caspian Sea. Atmosphere thickness patterns that are drawn for representative days, indicate the deep trough on the eastern Mediterranean and north west of Caspian Sea, which makes situation for falling cold air from Europe into the area. The analysis of moisture convergence flux shows the importance of the Caspian, Black and Mediterranean Seas as resource of humidity for extreme and widespread precipitations.

Mass movements are among the most destructive natural disasters in mountainous areas which cause great damages of over millions of dollars to human being's life and infrastructures across the world. Landslide, as a type of mass movement, is a complex process that occurs under the influence of internal and external parameters. The main effective parameters in hillside instability are earthquakes, precipitation and human activities. Landslide risk assessments estimate the probability of their occurrence in a place with a return period. Most of the methods based on educational samples and assignment of a weight to each of the parameters and sub-parameters establish the relationship between effective factors in landslides and spatial analyses. Among these methods are logistic regression, multivariate statistical analysis, artificial neural network, fuzzy model, and neural fuzzy model. In this study, for optimal management in Goijabel basin, we used the logistic regression method, as a statistical method which creates a mutual relationship between the dependent parameter and independent parameters, as well as artificial neural networks with perceptron multilayer algorithm, which allocates a weight to each of the factors in landslide using educational-testing and training data based on non-linear functions.
Study area: The study area is located 10 km from the south west of Ahar, in East Azerbaijan Province. The application site lies between the latitudes 38° 21′ 42″ N to 38° 27′ 39″ N, and the longitudes 46° 47′ 21″ E to 46° 56′ 53″ E, and covers an area of 74.62km2.
Material and To implement the methods used in this study, firstly, the maps of effective factors in landslide occurrence were provided and extracted, including lithology static factors, distance from fault, elevation, slope and aspect and dynamic factors of distance from road, distance from river, land use and land cover.
Fuzzification of effective factors, logistic regression, parameters such as Chi Square, Pseudo R Squared and ROC are used for validation of the logistic regression model. The other method used in this research is perceptron neural network. Accordingly, effective factors in landslide occurrence in the area under study were prepared as the model's input. In the next step, each extracted layer was sectioned with the landslides layers, and based on the histogram and the area of landslides in each of the layers, a reclassification was done in all of the layers.
Validation of the models used was by ROC method. The results of this model are based on statistical classification analyses. This method indicates higher area under the curve in the neural network model. In other words, the neural network model with the numerical average of 0.91% is introduced as a more efficient model compared to the logistic regression model with the numerical average of 0.89%. Using educational data and hidden nodes and other indexes such as coefficient of acceleration, this model can provide better modeling of the areas sensitive to landslides occurrence.
In this study, for an optimized management in the region and avoidance of potential damages caused by mass movements, especially landslides, the zoning of the areas sensitive to these movements was performed using logistic regression models and artificial neural network with perceptron multilayer algorithm. For the modeling, 9 independent parameters were used including precipitation, Lithology, land use and land cover, elevation, slope, aspect, distance from drainage network, distance from fault and distance from road. After standardization of each of the parameters, 9 factors were introduced as the independent variable, the landslides as binary layer for logic model, and standardized factors as input neurons and landslide layer as training of artificial neural network model with perceptron multilayer algorithm. The result of ROC validation shows that the area under the curve in the artificial neural network model has been higher than that of the logistic regression model, indicating a precision of 0.91% compared to logistic regression with a precision of 0.89%. Therefore, an area of over 9% is in high and very high -risk zones and 9/5% of the area is in medium-risk zones. Medium-risk zones can be affected by mismanagement and human constructions such as roads and be changed into high and very high risk zones, considering the fact that in this modeling, the areas close to man-made effects in both models are zoned as areas sensitive to landslide risk.

Not only have clouds and precipitation (snow, rain and hail) made up an important part of the subsystem atmospheric phenomena of terrestrial climate, but are also considered as the main components of the water cycle. Aerosols play an important role in cloudiness and precipitation. In warm clouds with the same liquid water path, increase in aerosols concentration results in the reduction of effective radius of cloud droplets and increase of cloud albedo, which is referred to as “first indirect effect” or “Twomey effects” (Twomey, 1977;Twomey et al., 1984). Variation in concentration of aerosols causes variation in the thickness, life period and precipitation rate of the clouds, referred to as “second indirect effect” or “Albrecht effect”, (Albrecht, 1989; Hansen et al. 1997; Ackerman et al. 2000).
The city of Tehran, the capital of I. R. of Iran, is a mega-polis with a population of more than 10 million. The city is located in the central part of the Alborz Mountain Range and characterized by its complex topography and diverse climate in an area of about 700 Km2. The city's long term annual average precipitation is 300mm. The growth of the city during the last 30 years has turned the city to one of the most polluted cities in the country, particularly during autumn and winter. The geographical conditions of the city are the other most important factors affecting the city's environmental condition and the nature of the particulate matters that may be found in its atmosphere.
In this paper, the influence of aerosols on microphysics of clouds over Tehran during the years 2003 to 2012 has been investigated.
Material and In this paper, the influence of aerosols on microphysics of clouds over Tehran throughout the years 2003 to 2012 was studied. Correlations between microphysics of clouds and aerosols from the Moderate Resolution Imaging Spectroradiometer (MODIS) were examined over Tehran. These are both from the collection 5.1 level 3 daily data, at 10×10 resolution. Daily AOD, CER, COT, CWP, CTT and CTP observed by MODIS on board the Aqua satellite from 2003 to 2012 on 10×10 grids are used in this work. In this study, Aerosol Index (AI) and Aerosol Optical Depth (AOD) were used as a proxy for the cloud condensation nuclei (CCN). To reduce errors, water phase cloud is defined as having a cloud top pressure greater than 800hPa.
Pearson and Spearman correlation coefficients were calculated and written for all cloud microphysical quantities with AOD as well as AI by software SPSS-V13. For the study, scatter plot diagrams between CER, CWP, CF, CTT, CTP and COT with AI and AOD were drawn. Furthermore, scatter plot diagrams between cloud microphysics quantities were drawn. We used the AI and AOD as our aerosol products, as AI includes size dependence and has been shown to correlate better with CCN. Pearson and Spearman correlation coefficients and scatter plot diagrams showed that there are positive correlation coefficients between the aerosol index and cloud top temperature and cloud top pressure. However, there are negative correlation coefficients between aerosol index and cloud fraction, cloud optical thickness and cloud water path. There are no significant negative correlation coefficients between cloud effective radius and AI over Tehran. These correlations suggest the increase of aerosols in Tehran in the last 10 years, because of over seeding. In these 10 years, there was reduced cloudiness over Tehran. The correlations between quantities of cloud microphysics fully match with theoretical studies.
At first step the scatter plots of CER, CWP, CF (cloud fraction), CTT, CTP and COT versus AI and AOD, which were considered as the representative of aerosols in our study, were created to provide an early picture of the possible interrelationship between those cloud microphysics and aerosols characteristics. The same diagrams were plotted to provide a picture of the way microphysical characteristics of clouds vary with each other. Study on the relationship between the AOD and AI with CCN showed that AI is a better representative of CCN .Then, correlations between clouds microphysical properties and both AOD and AI were examined by means of Pearson and Spearman correlation coefficients which were calculated usingSPSS-V13. The results showed that there are positive correlation between the AI and CTT and CTP. However, there are negative correlation between aerosol index and CF, COT and CWP. Negative but insignificant correlation was observed between CER and AI over Tehran. The correlations suggest the increase in aerosols concentration over Tehran during the duration of study might be regarded as one of the main reasons for the reduced cloudiness and precipitation over Tehran. The correlations between quantities of cloud microphysics fully match the theoretical studies.

Urmia is one of the important historical cities of Iran which in recent years has been associated with physical-spatial rapid expansion. One of the necessities of spatial planning of Urmia is controlling the rapid expansion of the city in marginal areas that are unbalanced fertile land and industrial and mineral soils are under construction and this problem has presented numerous hazards in the fields of economy and environment. Excessive physical development in the surrounding areas is now one of the major challenges in managing urban spatial development. Recognizing these challenges in identifying the pattern formation and urban structure is important in the context of place and passing of time. The application of this identification helps proper diagnosis and urban land use and appropriate physical development of the city.
Urmia, in West Azarbaijan Province, is one of the ancient cities of Iran. In terms of the geographical coordinate system, it is located in between44 degree and 3 minute to 47 degree and 23 minute east longitude and between 35 degree and 58 minute to 39 degree and 46 minute north latitude, at an altitude of 1332 meters above sea level. The area is 10 thousand and 548 hectares. The city has been located in the vast and verdure plain in length of 70 km and a width of 30 km. Average of monthly minimum and maximum temperature is 6.4 and 17.5, respectively. The average of relative humidity is 60% and the average of monthly precipitation is 341 mm. Most of the existing deposits in the region are sedimentary deposits, yet highly dynamic structural changes such as orogenic and faulting may be created by dynamic metamorphosis in some parts of the region. More outcrop of sedimentary units of Urmia region is related to Mesozoic Era (Jurassic) and Quaternary (Quaternary).
Material and In this study, documents in the library were used for literature review. Next, using climate data and digital elevation model and field surveys, base maps were prepared for zonation spatial planning. Then, the indicators: elevation, slope, soil, land use, climate, and geomorphology, distance from the rural, distance from the city, distance from the roads and distance from the river were used. The selection of criteria was based on field surveys which were performed on the study area. After that, criteria were turned fuzzy using fuzzy membership function and fuzzy gamma 0.9 operator was provided for spatial planning zonation.
Fuzzy model for the first time was provided by Lotfi Zadeh (1965). Fuzzy theory concluded that by creating the membership function in a range of real numbers, new methods develop. Using fuzzy logic in analysis, geographical processes are described more realistically than by Boolean logic.Fuzzy analysis is performed using GIS software.
Urmia has had rapid and inharmonious growth in recent years and due to natural population growth, immigration, expansion of services, the granting of political – official identity to the city as the provincial capital, assignment by various government agencies in the city, country development programs, socio-economic and political changes and finally favorable physical conditions, It has never seen such a large body of demographic and physical changes. Urmia has had high population and area growth in 20 years (1986-2006) t. The present study makes clear that following the land reform in 1964, in the process of physical development from 1966 to 2011 in Urmia, the influx of migrant population in the city of Urmia intensified. Development of marginalization in north and northeast parts of the city, in the communication path to the Salmas town in the north-western edge of Urmia Lake has had its consequences. Since 1987up to now the highest growth has been in urban areas mostly in the west, North West, east and southern parts of Urmia, which caused the annexation of the surrounding lands to city, settlement cooperation and development and the establishment of inappropriate settlements and marginalization. The issue of ownership had of rapid population and area growth. The growth was fragmented. Given that Urmia is at a distance of approximately 15 kilometers from the east of Lake Urmia, this issue has been an important obstacle for physical development. In addition, in the east, northeast and southeast of the city there are agricultural lands and horticultural products. City development in these areas has been in contrast with these lands and is causing hazards and limitations for these lands. Thus, the development of the city stopped in this direction and development trends in the west, north, south west and south of the city are spreading. These directions which have followed the development process are the acceptable level of suitability. Overall, based on the assessments done in this study, the west, north, south west and south areas of the city are appropriate for development and consist of high and very high zones. Actually, the city has a single central structure – radial. With regard to the recognition and implementation of aerial photographs and maps available of physical development, the results are largely acceptable. Obviously, the increased standards and assessment in lesser extent will bring more precision. So, with proper selection of base maps and merge and their detailed analysis, fuzzy logic allows more accurate assessments and provides more accurate locations and can be used for planning urban development.
The results showed that zones with high suitability for the growth and development of the city are located in the west and southwest of Urmia and also in the south and northeast, in a scattered manner. In coastal areas of Urmia Lake and its immediate zones we see alluvial terraces deposits and very low, low and moderate areas. These areas have low ability in terms of physical development. Moreover, areas with low suitability can be seen in the northeast to southeast in a scattered manner.

One of the most important strategies for building low-carbon cities and increased environmental sustainability in cities is the development of low-carbon transport systems (Banister, 2008). Statistics shows that approximately 19% of energy consumption in the world and more than one fourth of carbon dioxide released in the world are due to transportation. This amount is increasing more in the transportation section compared to other parts (Knörr & Reuter, 2011, p. 4). Based on the predictions, fuel consumption in transportation sector will increase up to 50% from 2005 to 2030 and 80% by the year 2050, respectively (IEA, 2011,p.113). According to the announcement of the International Energy Agency (IEA), the transport sector will be the biggest consumer of energy by the year of 2020.
Iran also has a significant share in this sector. The total carbon dioxide emission was 560.3 million mt in 2012 in Iran and increased as much as 179% from 1990 to 2008 and its growing trend has intensified up to the year of 2012. The transport sector, compared to the others in Iran, is responsible for 23% and 96% of Co2 and greenhouse gasses emissions, respectively, of which 95% is due to ground transport ( ITF, 2010:88). No doubt the need for low-carbon transportation planning is essential not only to improve the current situation but also on a long-term vision. In recent years, numerous scientific studies have been conducted with different methodologies, one of the most common methods of transportation planning is the scenario based planning.
The ecological footprint is the one of the best methods for environmental evaluation of cities and its combination with the strategic scenario-based methods could increase its efficiency and effectiveness in a specified time interval. In this regard, this paper also presents three scenarios until the year 2025 in order to compare the effects of each of them on the city's ecological footprint. The aim of scenario making is finding the best solutions to achieve optimal vision in low carbon transportation in Mashhad and present the scenario that has the greatest impact in reducing the ecological footprint.
The Study Area: Mashhad, the second most populous city of Iran, has an area of 350 km2 (35000 ha) and population of 3009295 (Mashhad's City Fact Book, 2012). Based on the study of Mehrazan Consulting Engineering, the number of pilgrims and tourists of Mashhad was estimated approximately 25 million. The number of urban travelers of Mashhad citizens per day increased from 3893632 travels in 2006 to 5876313 travels in 2011, a growth equivalent to 33.7%. In addition, the coefficient of rush hours of daily travelling doubled from 5.11% to 10.94% (Mashhad's 8th Transport Fact book, 2012) and had 19.6% increase just in the first 8 months of 2013. These numbers and figures indicate the harmful and destructive effects of city machination and irreparable damages on the urban environment and citizen's health (Transport and Traffic Organization of Mashhad Municipality, 2005).
Material and Ecological footprint is the method that covers the ecological concept of Carrying Capacity (Chi and Stone, 2011). In fact, "Appropriated Carrying Capacity" in other parts of the world is interpreted by "area unit" so that the greater the area, the greater burden will be placed on the environment, which in turns reduces the sustainability of other parts of the world (Chambers & Lewis, 2001).
The first stage: The carbon footprint of daily personal travel
EF: The amount of carbon emission from each vehicle- per kilometer
UF: Energy required for manufacturing and maintenance of each vehicle- per kilometer
CS : Each ton carbon per hectare per year
The second stage: The ecological footprint
ARI: The land required for transportation or area of the road infrastructure (hectare)
EF: The number obtained from calculation of ecological footprint for land and transportation infrastructure
VRS: The rate of car ownership by percentage
TDT: The total distance of trip (Vehicle – kilometer).
The first scenario: Continuation of the existing trend and common business With the current trend the total energy consumed in transportation increases to 54 million GJ and the amount of carbon produced reaches to 773 973 tons. The ecological footprint in Mashhad by the year 2025 will increase to 0.14 hectares per person. This means that any person who lives in Mashhad needs 0.14 hectares of land to refine the all the carbon produced in transportation in one year and reduce it to zero. At present, this figure is equal to an area of about 10-times larger than the current area and by continues the current trend till the year 2025 it will increase to 16 times larger the current area of the city.
The second scenario: Replacement of Euro 2 fuel by Euro 4 for all vehicles by the year of 2025. Studies show that upgrading the fuel standard from Euro 2 to Euro 4 leads to the reduction of pollutant level from 2.7 g to 1.18 g per vehicle. Considering the traffic of 1400000 vehicles which will be manufactured in Mashhad by the year 2025, if the fuel standard level in all vehicles upgrade from Euro 2 to Euro 4, we could reduce 19824 ton pollutants. Based on this scenario, energy consumption annually will be 33 million Gj, equal to 8.25 Gj per person and ecological footprint based on each 100 Gj per hectare will be 0.08 ha. This means that Mashhad needs the area 7 times larger than the current area for purification and nutralization of carbon from the transportation sector per year.
The third scenario: Public transport fleet renewal and removal of 60% of old private vehicles by the year 2025. Our calculations show that by implementation of this scenario the ecological footprint of Mashhad transportation will have a very significant reduction equal to 0.004 hectares per person which is equivalent to 16,000 hectares backup land for carbon absorption and desorption. Now old cars in Mashhad according to fuel type (Euro 2) produce the amount of 4.248 million tons of emissions per year.
According to this scenario, the complete removal of old cars from the fleet public transport and removal of 60 percent of personal old cars will reduce 2.5488 million tons of pollutants per year. So the most influential and the most important scenario for reduction of ecological footprint in Mashhad city transportation is related to the reduction and elimination of old cars.

East Azerbaijan province is one of disaster-prone provinces of the country and each year the occurrence of potential risks of atmospheric phenomena is not unexpected. However, the lack of sufficient information and knowledge of farmers in the field of risk management strategies in agricultural production process has multiplied the losses incurred to farmers. Thus, the existence of a wide range of production risk and the importance of the agricultural sector in East Azerbaijan Province and the necessity of paying attention to the capacities and psychological capabilities of farmers in this context, made this study to seek to answer the following fundamental questions: How much is the extent of using crop production risk management strategies in wheat production among wheat farmers of Bonab County and what factors are affecting it?
What are the suggested strategies to enhance risk management approach among wheat farmers?
The Study Area: Bonab County is one of the poles of wheat farming in East Azerbaijan Province with one district, three sub districts and 29 inhabited villages with a total population of 49902.
Method and Materials: The research method was descriptive, correlational, analytic and casual. Data collection was done using a questionnaire that was developed according to the objectives of the study. The statistical population of this research was 5695 wheat farmer, and 400 od them were chosen as the sample population according to the Krejcie and Morgan table using the simple sampling method. The face validity of the questionnaire was confirmed by a panel of experts. The pilot study was done with 50 questionnaires and using the data obtained and Cronbach alpha, the reliability of the questionnaire varies between 0.87 to 0.89. The application of crop production risk management strategies among wheat farmers of Bonab County is considered as the dependent variable in this research. In order to investigate the strategies of agricultural production, multiple-choice answers were used (none, very low, low, medium, high and very high) and the answers were weighted from zero to five and finally, the results were investigated using Spearman correlation test and Nord diagnostic analysis.
To classify the wheat farmers on the basis of the level of implementing crop production risk management strategies, the sum of responses was calculated and according to the number of questions and the value of responses, the range of people’s scores was determined from 0 to 55. The subjects with score of 0 to 12 were placed in group of very low application, 12 to 24 in group of low application, 24 to 36 in group of medium application, 36 to 48 in group of high application and 48 to 60 in group of very high application.
In order to determine the relationship between the dependent variables of the research and the variable of the crop production risk management strategies, Spearman's correlation coefficient was used. According to the results, there is a significant relationship between the variables of ingenuity and creativity, optimism and certainty in job, effect, meaningfulness, resilience, hopefulness, optimism, the ability to make decisions, self-efficacy, self-determination, competency, ability to solve problems, responsibility, flexibility to adapt to changing environment and taking risk with the variable of the level of application of crop production risk management strategies with confidence level of 99 percent. Also the results of analytical detection showed that the independent variables of self-reliance, influence, meaningfulness, resilience, hopefulness, the use of opportunities, self-efficacy, self-determination and competency are the most important independent variables, affecting the level of implementing risk management strategies by wheat farmers. The remaining independent variables are excluded from the model.
One of the most important challenges facing agricultural production is the fragile nature of these products, which has led to great losses for farmers and villagers. In this regard, farmers and agricultural producers are faced with a kind of disbelief and uncertainty in production that disclaims the motivation of trying from them.
According to the results of the research, training courses should be held in rural areas to enhance the index of life quality by promotion of psychological capital.
Also it is recommended that the government support smallholders by taking economic, educational and technological policies to promote the use of financial risk management strategies and their marketing besides increasing motivation among them.
Finally, it is recommended for the planners and authorities to consider the necessity and importance of education as a main approach to increase the skills of wheat farmers for risk management by considering their educational needs and demands

Wood is the long-term memory of the history of a tree which is records the environmental changes by anatomic and formic changes. denderocronology uses the trees as natural evidences or "silent witnesses" to reconstructing the past environmental characteristics. ‘dendrogeomorphology’ is one of the subfields of dendroecology which has been widely used for study of past geomorphic processes. dendrogeomorphology is detected of spatial and temporal aspects of the surface processes by analyzing of annual growth tree rings and disturbances in tree forms. Also dendrogeomorphology enables to precise the event occurrences in annual and even seasonal time scales. Based on the principle of dendrogeomorphology affected trees by geomorphic processes react to the events as disturbances in their ring and forms, in other words these reactions recorded in the series of their rings. Trees in temperate climates generate one growth ring in each year and Flood as a river geomorphic process influences on the trees morphology in margins and river bed, and lead to different growth responses in the series of tree ring. Tilted and scared trees thought the river bed and banks are the most common types of dendrogeomorphological evidences created by paleoflood events. These tree disturbances have been used for dating and reconstruction of past geomorphic events. Stem tree scars can be used as a paleostage indicators(PSI) to help researchers for reconstruction past flood events.
Study area: With approximately 3 km length, the study area is part of the mainstream Neka River in the south of Neka city. The beginning of the study reach is located in 36˚ 37ʹ 24˝ N latitude and 53˚ 21ʹ 52˝E longitude. The end point of the study reach terminated to Abloo convert dam which is located at 36…N latitude and 7778 E. Neka basin is an oblong basin with an area over 1903km2 started from northern slopes of Albborz mountain range and drains to Caspian sea in the north side of Neka city. The main stream originated from the Shahkooh Mountain in the south of Grogan and after receiving other tributaries creates the Neka River, after passing across the Neka City flows into the Caspian Sea. The length of main stream channel is 150km measured from the upstream until basin outlet in the Ablo gage station.
Material and Research method of this study is experimental- historical. We Firstly collected the basic data including book and articles, statistical data, satellite images and digital elevation models (DEM). Then we have analyzed the frequency of peak discharge records obtained from Iran ministry of power (IMP) for Abloo gage station. As well as we prepared the base maps including contour, slop, aspect, and geomorphological maps.
Sampling method of our study was selective as we extracted 18 cores through stem tree scars using a 300mm increment borer. The sampling trees are been located in the margin of stream channel and river banks. Also we were taken 6 reference samples from the trees without growth disturbances to make a cross dating with damaged trees. We used an identification card to record the characteristics of the sampled trees, including of tree type, tree diameter, tree height and tree scar dimensions as well as we marked the tree coordinates using an Etrex Vista portable GPS. We continued the study stages after sampling as following steps: 1- the cores were fixed on wood holders, then exposed the samples for drying in the laboratory atmosphere for several days. 2- the sample surfaces were smoothed by special sand paper to produce better clearness of number and widths of the rings. 3- The number of rings and ring widths were counted and matured using digital table LINTAB attached to the stereomicroscope (Leica stereomicroscope) and TSAPWIN software program. These laboratory equipments provided a 1:100mmof measuring accuracy. 4- Tree growth curves were drawn by TSAPWIN package and then analyzed to reconstructing of the flood event times. 5- In the last stage, the results obtained by dendrogeomorpholology method are compared with stream peak discharge records of Abloo gage station for period of 111111. Also we surveyed 4 stream channel cross- sections to use them for assessing the surface, mean velocity and discharge of past large floods in the study sites.
In this study, we analyzed the biologic paleo stage indicators and stream channel flood marks to reconstruct the past large hydrological events. We dated the large floods according to the sudden decreasing in the growth trend and growth pattern of tree rings. Then the results obtained from the tree ring analysis were compared and adjusted with systematic instrument data of Abloo gage station. According to the results of dendrogeomorphological analysis, we found out that most of scars have originated from the floods of 2008 and1999 with 130m3/sec and 2000 m3/sec respectively. Most scared trees are resulted from above floods in the study reach as the flood impacts obviously recorded in the tree ring series. Also the flood of 2003 with 361 m3/sec peak discharge causes greatest impacts on tree growth trends in the margin of river bed. We reconstructed two past large flood events in the study river which is occurred before establish of Abloo gage station. Based on changes in tree ring growth trends these two floods occurred in 1941 and 1955. With 270cm height from tree base, the largest stem tree scar in the study area relevant to Flood of 1941. Moreover the reconstructed floods by tree rings method were compared and coincidence with peak discharge data of Abloo hydrometric station and obtained results show that all of cases have coincidence and conformity with recorded data in the study station. We recognized the highest stem scar in the sample number 16 which is formed by a flood in 1935. The Scar height shows the flood mark of the largest paleo flood with 4277 m3/s in the study river. Reconstructed discharge has been calculated using the geometric data of study reach. We surveyed 4 channel cross-sections regarding to tree scar heights, then the area, perimeter, slope and bed roughness coefficient parameters determined in the cross- section sites. We used the manning equation for estimation of past flood discharges.
Based on the results of this study we reconstructed two largest floods in the Neka River which they are occurred in 1941 and 1955. With discharge of 4277 m/3, It seems these floods are been the largest floods of the study river during the last hundred years. Also flooding years reconstructed by the tree scars was in concordance with the flood discharges recorded in the Abloo hydrometric station. But the amount of flood discharges obtained by denderogeomorphology method is more than the recorded discharges by Abloo gage station. Then we can suggest that the analysis of trees rings and the height of scars in tree stem, are the very useful tools in the Neka River basin for reconstruction of the year of flood events and estimating of flood discharges.