نشریه جغرافیا و مخاطرات محیطی
پیاپی 10 (تابستان 1393)

Air pollution is one of the most important environmental issues in Megacities which is seriously threatening human health. High concentration of air pollution is frequently seen over large cities of Iran in recent years. It is difficult to estimate the exact loss of lives and properties resulting by air pollution because of the lack of data، however there are reports that show the vast destructive effects of this phenomenon over the polluted cities. Air quality over the cities is determined with respect to both the total air pollution in a given area as it interacts with meteorological conditions such as humidity، temperature، and wind characteristics to produce an overall atmospheric condition. Air quality is determined by emission sources and weather situations; however، serious pollution episodes in the urban environment mainly result from certain weather conditions which pose difficulty for pollutant dispersion. Air pollution is influenced by meteorological factors through transport، chemical transformations، and removal via wet and dry processes. In this research، the role of regional atmospheric circulation on the occurrence of critical air pollution episodes in the Mashhad metropolitan is investigated. Also the synoptic and thermodynamic mechanisms which are dominated during the most polluted days over the city is identified. Study Area: The study area is located in the valley of Kashaf-Rood River between two mountain ranges of Binalood and Hezar-masjed. Its geographical coordinates are 59º، 27''، 0«E to 59º، 40''، 30'' E and 36º، 22''، 0'' N. The city benefits from the proximity of the mountains، having cool winters، pleasant springs، rather hot summers، and beautiful autumns. It is only about 250 km (160 mi) from Ashgabat، Turkmenistan. Mashhad is 999 m higher than the sea level. According to meteorological records، the average maximum temperature for the four seasons in Mashhad are: winter 8. 3°C (52°F)، spring 21° C (88°F)، summer 33. 2°C (92°F)، and autumn 22. 2°C (72°F). The average minimum temperature for the four seasons also is: winter -3. 6°C (18. 9)، spring 7. 3°C (45. 2°F)، summer 13°C (61. 3°F)، and autumn 5. 7°C (42°F). Mashhad has a semi-arid climate with occasional rainfall in spring and autumn and light snow in the winter. The city only sees about 250 mm of precipitation per year، some of which occasionally falls in the form of snow. Mashhad also has wetter and drier periods with the bulk of the annual precipitation falling between the months of December and May. Summers are typically hot and dry، with high temperatures sometimes exceeding 35 °C (95 °F). Winters are typically cool to cold and somewhat damper، with overnight lows routinely dropping below freezing. Mashhad enjoys on average just less than 2900 hours of sunshine per year. Its population was 2،772،287 at the 2011 population census; so، the city is ranked as the second most populous city of Iran (http: //en. wikipedia. org/ wiki/Mashhad).

In this study، a combined synoptic analysis approach is employed to identify the role of regional atmospheric circulation pattern on the occurrence of high-polluted days over Mashhad. Four types of dataset including air-quality monitoring station data، reanalysis gridded data، upper air soundings data and a lograngian backward trajectory model (HYSPLIT) outputs are used to do this research. The air-quality monitoring station data is obtained from Khorasan-e-Razavi Environmental Protection Administration، while the upper air soundings data and reanalysis gridded data are obtained from National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR). and Wyoming Weather Web، respectively. Also، the Hybrid Single-Particle lograngian integrated Trajectory (HYSPLIT) model is employed to determine the main sources of air parcels by using a backward trajectory approach. Using the Pollutant Standards Index (PSI). daily، seasonal and annual variations of Mashhad air quality is investigated for a 7-year (2005-2011) time period. Using PSI index، we first detected and extracted all very high-polluted days (PSI>200) over Mashhad. Then، a combined synoptic classification approach has been applied by using a set of manual synoptic classification، lograngian backward trajectory model outputs and thermodynamic diagrams.

Investigating the temporal variations of five air pollutants over Mashhad، it is seen that Carbon monoxide is apparently shown a decreasing trend among all air pollutants. While Ozone and Sulfur dioxide experience an increasing trend during the study period. Also، it’s seen that the PM10 shows the most monthly، seasonal and annual values among the others. Moreover، it is revealed that those pollutants with low concentration are showing more seasonal variations in Mashhad. Using combined synoptic classification approach it is indicated that the days with highest level of air pollution in Mashhad can be classified into four main atmospheric circulation patterns including: combined Siberian high-subtropical high، migrating anticyclone، subtropical high and extra-tropical cyclone patterns. In combined Siberian high-subtropical high pattern، a simultaneous domination of Siberian high in lower atmosphere and subtropical high in middle troposphere has been caused an atmospheric stability and high levels of air pollution during cold period of the year. In this pattern، formation and coexistence of a shallow inversion layer in the lower atmosphere and another upper inversion layer in mid-troposphere show coincident roles of Siberian high and subtropical high in increasing the concentration of air pollution to higher level. In mitigating anticyclone pattern، by crossing a Rossby wave over the area، a strong mid-tropospheric ridge over the Oral Mountains and the Caspian Sea will dominate. The eastward inclination of this ridge has been caused an anticylonic circulation in a region from Caspian Sea to northern Khorasan in lower atmosphere. In this pattern، a few thin inversion layers form at the same time below 400hPa level. Rapid temperature drop between the inversion layers indicate the strength and weakness of air subsidence in this pattern. The subtropical high pattern has caused a high level of air pollution over Mashhad only in warm period of the year and it shows a distinct pattern of subsidence inversion type in the vertical profile of atmosphere. The Low-pressure pattern has identified by passing of a rather deep trough over the northern Iran in mid-troposphere and the formation and eastward movement of a cyclone in the lower atmosphere. In general، this pattern is not associated with a distinct and strong inversion layer in vertical profile of the atmosphere، while the thermodynamic diagrams show baroclinic instability through the atmosphere. In this pattern the days with very high levels of air pollution have been caused by lifting، transportation and distribution of dust and particles to the study area due to instability and vast ascend of air as well as lack of suitable moisture feeding into the low pressure.

The results indicate that the middle atmospheric circulations play the most important role in creating extremely high air pollution episodes in Mashhad. The results also demonstrate that the importance of each atmospheric circulation pattern differs from one season to another season. In other words، while in cold period of the year the occurrence of extremely high air pollution episodes has strongly related to extra-tropical atmospheric circulation patterns (i. e. mitigating anticyclone and low-pressure patterns). in warm period، all of high polluted days have mainly related to subtropical atmospheric circulation pattern. However، the subtropical ridge is the most important and also the most frequent pattern which should be consider among 4 main atmospheric circulation patterns. Implication of a combined synoptic classification approach by combining manual synoptic classification، backward trajectory analysis and investigating atmospheric thermodynamic conditions provide a better understanding of dominant mechanisms in extreme air pollution episodes over northeast of Iran. This approach was successful and effective and it has created reasonable and reliable results.

Climate events behave as stochastic phenomena، which mostly could be predicted by using probability rule and stochastic process. The terms of «stochastic» and «probability» refer to uncertainty about the occurrence of phenomena (Asakereh 2011:239). Accordingly، the climate events follow uncertainty in their behavior. Therefore، using probability rule in climatology could justify a lot of climate phenomena which semblance of unpredictable events. Due to this kind of usage of probability rules in climatology، the environmental management will be more successful based on climatic information. Because the probability rules، in fact، can help experts through extract constant rules from semblance of disorder or abnormal phenomena. One of the stochastic models categories which are widely used in climatology is Markov Chain technique. For instance Grigorten (1966) used this technique to estimate the frequency and persistence of weather types during vast and different time interval. Feyerherm and Dean (1967) used Markov Chain technique to analyze the wet and dry spells in the Northern United States. Todorovic and Woolhiser (1974) applied Markov Chain model to investigate the possibility of rain in a sequence of days. Steam (1980) used this model in order to study the probability of rainfall occurrences in India and Nigeria. In the current paper، the dry days were evaluated based on probability rules، stochastic process، and Markov Chain. Accordingly the ability of Markov model was validated. Study Area: Iran is located in southwest of Asia with high mountains on its four sides، and borders the seas in south and north. Due to its location، besides intra-annual variations of precipitation، spatial differences also occur. In addition، the vast area of the country (approximately 1600000)، its wide latitudinal extent (25 to 40 N)، and its pronounced relief lead to the complex structure of the precipitation distribution over Iran. The wide latitudinal extent of Iran causes it to be in many systems paths، which can activate its precipitation in a tempo- spatial fashion. Under given conditions، there are systems causing different precipitation; each operates on different space and time scales. These systems come not only from outside of the country (e. g. Mediterranean Sea) but from inside (high mountain systems) (Alijani، 1994). The two highest mountain systems، Zagros and Alborz- Talish، which rise up to 4،557m and 5،670m above sea level، respectively، strikingly affect the temporal and spatial patterns of precipitation. Zagros، in the western part of Iran، is the most elevated mountain range، extending from north-west to southeast، while the northern highlands (Talish and Alburz) are extending from west-to-east along southern Caspian Sea. The data network of daily precipitation of Iran employed in current study، was obtained by interpolating the daily observations from 1961-2010 and 1436 (synoptic and climatological) stations which are recently achieved from Islamic Republic of Iran Meteorological Organization (IRIMO). Due to deprivation of station coverage in time and space and in order to have a complete coverage over Iran، the interpolation was carried out by the Kriging method (Asakereh 1387) that had the lowest root mean square errors when compared to other spatial interpolation methods. The Spatial data resolution was 15 15 km and the country was covered by 7187 pixels. Accordingly، Iran''s precipitation had 18218× 7187 dimension and S-Mode matrix (time on the rows and location on columns). Dry days analyses by using Markov model carried out on aforementioned database. Accordingly، precipitation estate was distinct based on precipitation amounts، thus، the day without any precipitation، considered as a dry day، and the days with any given values of precipitation indicated as a rainy day. The frequency matrix is formed and the probability matrix of rainy – dry days is created accordingly based on maximum likelihood method. This procedure is used for all 7187 pixels. Then the frequency of calculated dry days، and the frequency of observed dry days was compared in order to find the estimation error for each pixel. In the next step، the classification process took place by using hierarchical cluster analyses. In this process، the pixels with similar characters of dry days probability and similarity in error of Markov model estimator were put in the same class. The monthly maps output of dry days based on Markov chain model were prepared. In order to validate this model، the number of observed dry days maps also were illustrated. To sum up، four months (January، April، July، and October) were analyzed as representative of four seasons. As can be seen from Figures in current paper، there are many places (e. g. along Alborz an Zagros Mountains، Caspian sea coast، and in the western provinces) in January، the error of Markov model is pronounced. The deprivation of Markov model output during April is more distinguishable in southern parts of the country، while the minimum errors took place in northern coast، northwest of Iran، and in western parts of the country. The dry days during summer season (July) estimated by Markov model is the best estimation in compare to other seasons in which Markov model suggested. There are only small overestimated errors that did not exceed one day only. During September، the same result as the summer result took place except for the western parts، northwest، and some parts in Caspian Sea coasts. According to probability of dry days based on Markov model and based on the model validity، pigeonhole of pixels took place. As it mentioned before، the process is taken place by using Cluster Analyses model. Therefore six zones، which are in agreement with geographical factors (e. g. Topography، Latitude and Longitude)، were diagnosed over Iran: The first zone coincidence with highest parts of Zagros Mountains، which covers only 9. 2% of Iran territory. The second zone covered approximately 13. 2% of the country، and dominant in northeast، northwest of Iran، and the southern part of Alborz Mountain. The third zone covered 19% of the country among some parts of northeast، Lalezar and Hezar mountain in Kerman province، and some parts in south of Iran. About half of Iran territory including central، eastern، and parts of south of the country، is covered by the forth class. The least coverage is the fifth class qualification. This class covered 2. 3% of the country among center parts and the west of Caspian Sea coast. The sixth class including 5. 8% of Iran territory is among east of Caspian Sea، and northwest of Iran. Precipitation is one of the most important climatic elements that can characterize some main aspects of the climate of a region. One of more important aspect in precipitation changes is alteration in its occurrence and non- occurrence. Stochastic approaches، such as Markov chain model، are one of the appropriate approaches with which we can simulate precipitation estate. Accordingly the frequency matrix is formed and the probability matrix of rainy – dry days is created for each pixel over Iran، based on maximum likelihood method. Therefore the probably and frequency of Dry days were estimated based on persistence probability calculated based on succeed power on probability matrix. This value for each pixel was compared with the observed values for each pixel. The dry days of summer months showed more agreement with the estimate of Markov model in compare with other months. There was an attempt to pigeonhole Iran based on dry days probability، and its accurate values. Therefore، six classes were discovered. These classes are in agreement with geographical factors e. g. Topography، Latitude and Longitude.

The process by which the net radiation is transformed to the Atmospheric dynamical energy، occur to a large degree at the interface between the surface and the atmosphere. As the driving force for such process، an accurate estimation of the net radiation at the earth’s surface is a necessary input for surface process models. Net radiation is a key component in the surface radiation budget. Net radiation (Rn) at the Earth''s surface drives the process of evaporation، photosynthesis، and heating of soil and air. Net radiation is the difference between the down welling and upwelling radiation fluxes at the surface، including long wave and shortwave radiation. Down welling shortwave radiation، RS↓، at the surface results from scattering، emission and absorption within the entire atmospheric column; while upwelling shortwave radiation can be estimated by RS ↓ and surface albedo. Down welling long wave، RL↓، and upwelling long wave radiation، RL↑، are characterized by near-surface air temperature، air emissivity، surface temperature and emissivity. Net radiation and the overall surface energy budget are important for the development of the planetary boundary-layer. Its quantification over hetero-genous land surfaces is crucial to study land–atmosphere interactions. Solar radiation data are required in different fields of researches including architecture، active and passive solar energy systems، agriculture، meteorology and climatology. The estimation of net radiation at the earth’s surface is important for a number of applications including climate monitoring، regional solar energy availability assessment for heating and electrical power generation purposes and for the evaluation of the cloud and radiation parameterization used in weather and climate models. Measurement of solar radiation is more difficult than other meteorological variables. This is attendant with problems and errors such as technical failure and operation-related problems. Different sources of errors related to solar radiation measurement can be categorized into two classes: equipment technical failure and operation-related problems. There exists error and uncertainty with any measurement that can be systematic and/or random. The most common source of error in measuring solar radiation is systematic and resulted from the sensors and their construction. But the most important error is random and is due to operational، maintenance and reading instruments. Precise spatiotemporal distribution of net radiation component in arid/ semiarid areas such as Iran are critical information for sustainable management of natural resources as well as for a better understanding of water and heat exchange process between the land surface and the atmosphere. Such information can be achieved using interpolating measured irradiance by ground stations. But، availability of solar radiation data in Iran is limited by the sparsity of the existing networks. However the distribution of surface fluxes over large areas is difficult to obtain from ground measurement alone. Therefore، their prediction from reanalysis data is very attractive since it enables large area coverage with a high repetition frequency. The main objective of this study yields accurate estimates the spatiotemporal variability of the net radiation components over Iran using reanalysis data. Study Area: The study area for this study is whole extent of Iran، which lies approximately between 25_N and 40_N in latitude and between 44_E and 64_E in longitude. Based on the Koppen climate classification، most parts of Iran’s area are categorized as generally having arid (BW) and semi-arid (BS) climates. The important mountains of Iran are Alborz and Zagros، which play an important role in non uniform spatial and temporal distribution of radiation components in Iran.

We used daily reanalysis data over Iran for the period 2000-2010 derived from Climate Forecast System Reanalysis (CSFR) dataset with spatial resolution less than 0. 5°lat/ Lon. The Surface energy balance components for land surface are discussed using: RN-HL+HS+HG=0Where RN is the net radiation flux (Wm-2)، HG is the soil heat flux (Wm-2)، HS is the sensible heat flux (Wm-2) and HL is the latent heat flux (Wm-2). Net radiation also known as net irradiative balance، that is the balance of incoming solar radiation and outgoing terrestrial radiation، which varies with latitude and season. Net radiation is generally positive by day and negative by night. The net radiation Rn is obtained from the radiation balance between net shortwave and net long wave radiation at the land surface. RN=RS↓-RS↑+RL↓-RL↑Here RS↓ is the incoming shortwave radiation (Wm-2)، RS↑ is the outgoing shortwave radiation (Wm2)، RL↓ Is the incoming shortwave radiation (Wm-2) and RL↑ Is the outgoing longwave radiation (Wm2). In this study، the flux of net radiation (Rn) is considered positive when it is directed toward the surface and vice versa.

Precise spatiotemporal distribution of surface energy balance components in arid/ semiarid areas such as Iran are critical information for sustainable management of natural resources as well as for a number of applications including climate monitoring، regional solar energy and radiation parameterization used in weather and climate models. In the spring and summer maximum values of net radiation due to increase of solar height were observed over Zagros Mountain and Azarbaijan region. In this regions land surface more warming and reinforce sensible heat flux that cause severe convective precipitation. The highest values of net radiation in period between May to August seems will be seen in southeastern parts of Iran but due to monsoon، increase of clouds and decrease of incoming flux، it occurred in central parts of Zagros Mountain and upper latitudes. In the other hand، the maximum values of this parameter in precipitation period، from October to May، were detected in southeastern parts of Iran like Iranshahr.

information regarding net radiation regime is essential for policy makers and managers within the context of water resources management، hydrology، agriculture، and environment. Hence، it indicates the need for more attention to climate change and different aspects of its effect in the weather regime of Iran. The findings presented here on the spatiotemporal variability of Iran’s net radiation can be implemented to improve the water and solar energy resources strategies in the study region. Future studies would be attractive to examine the probable effects of climate change on the net radiation. In this study we use the CSFR network products in two local times daily (06:00، 12:00)، to calculate the spatiotemporal variability of the net surface solar radiation over Iran. The results of this study indicate that long-term mean net radiation energy flux has a sinusoidal behavior and the net radiation values in 06:00 hour is negative and outgoing of energy more than of incoming flux. The cooling of the surface was observed in this time for whole of the country. Moreover، the warming of the surface and positive values were observed at 12:00 hour because the net incoming flux is more than the net outgoing flux and energy saved over surface. Overall، the seasonal variability of net radiation flux shows that it affected by height of solar radiance، general circulation and local phenomena. The value of net radiation fluxes have peaked around the summer solstice and the minimum amount that can be seen at the winter solstice. In this time the maximum flux is seen at about 720 watts in June over the central Zagros and Damavand mountains، While the minimum flux of 200 watts is seen in north of Ardabil and Kopedagh in December. Monthly changes in energy flux that reflect the effects of changes in sun angle atmospheric circulation and local phenomena. In spring and summer، the sun''s altitude increases and the maximum flux of energy shifted towards higher latitudes and the Zagros and Azerbaijan region have more flux. In the spring، the amount of flux in the regions of Azerbaijan increases due to warming of the earth''s surface and sensible heat flux that resulting in the convection precipitation. In the months of May through August is expected the maximum of this flux to be observed in the southeastern regions of the country. Due to the arrival of monsoon systems and increase cloudiness، input fluxes decreased and the maximum flux occurs at higher latitudes، especially in the central Zagros. In the rainy season، from October to May، because of the reduced height of the sun and the shift of the maximum flux into the lower latitudes، maximum flux occurs in the southeastern region of the country، especially the East Iranshahr. In general، it is necessary to consider the maximum flux in the area East of Iranshahr، and really high peaks of the Zagros. It seems to be considered regions such as the Zagros region، watershed north of Khuzestan and the mountains of Hezar-o-Lalezar to Gawkhoni swamp lack of flux. The results also suggest the need for further investigation on local scale، which could be one of the major causes of evaporation and evapotranspiration.

Extensive fires in the forests are examples of natural crises (Hosseinali، 2005) and forest fire events are increasing in the conditions of changing climate and global warming; (Azizi and Yousefi، 2005). This phenomenon is considered one of the most destructive factors for forest ecosystems، causing irreparable damages (Marozas et al، 2007). Some of these damages include land use changes، emissions of greenhouse gases، disruption of forest structure and nutrients losses in ecosystems resulting from burning of vegetation and forest floor layers (Vakalis et al،2007; Alexandridis et al، 2008; Bakhshandehsavad rudbari et al، 2011). According to FAO (1995) the annual average of fires in forested areas around the world is estimated to be two million hectares. In many parts of the world، fires in forests and ranges is one of the most important issues and concerns، not only from an environmental perspective، but also from economic، social and security viewpoints (Silvia Merino and Gonzale، 2010). One of the research fields for controlling forest fire is to identify critical points in terms of fire in forested areas، because the lack of knowledge about these areas will cause the occurrence and spreading of forest fire، delay in fire suppression، and damage to forest plant and animal life (Jaiswal et al، 2002). Therefore، preparing the potential map of fire (fire critical areas) plays an important role in reducing the number of fires and preventing the destruction of forests (Dong et al، 2005) and helps the forest managers to prevent fires with special care in critical areas before they occur. According to a study by Atrak Chali (2000) the average area in forest areas that is burned due to fires is 7،000 ha and return intervals of forest fire in Golestan province varies from 5 to 7 years; therefore preparing fire hazard maps with high-precision is necessary for planning and crisis management. When، preparing the maps of fire risk، GIS is used as a basic tool for spatial data management. In many studies، GIS have been used to identify critical points and potential techniques have been applied. Mohammadi et al (2009) attempted to map the fire susceptible areas in Paveh forests fires by conducting field operations and by considering the measures of vegetation، physiography، climate، human and distance from roads and streams as well as by applying the analytic hierarchy process (AHP) and they showed that the resulting map was highly corresponding with the real locations of fire. In a study in Spain، Nieto et al (2012) evaluated the occurrence of fire caused by lightning during a 3-year period from 2004 to 2002 using logistic regression. In this study some parameters such as lightning، topography، vegetation and climatic parameters were considered. The results showed that the lightning was most important factor causing fire in the area fires during mentioned period and a risk model with ROC of 0. 7 obtained، indicating the good performance of the model. Golestan National Park is First Park that was considered as the national park in Iran and one-eighth of plant species، one-third of bird species and more than 50% of the mammal species live in this park (Hassanzade Kiyabi et al، 1993). This park is susceptible to fire due to its characteristics vegetation as well as occurring at a region with winds formed by the clash between wet and dry weather fronts (Shokri et al، 2002). This study models and identifies areas susceptible to fire in Golestan National Park using logistic regression، taking into account parameters influencing on the fire in the region. Study Area: Golestan National Park is located at the Northeastern part of Iran، East of Golestan province، Northwest of Khorasan province، and North of Semnan province between 37º 17´ 43´´ to 37º 31´ 35´´ N، and 55º 43´ 25´´ to 56º 17´ 48´´ E. The park area is 91،895 ha with a perimeter of 198 km. A transit road، known as Asian road that connect the northern and central Iran to the north-eastern Iran passes through the park. There are several villages around the park including Tangeh rah، Terjenli، Ghoch Cheshmeh، Zav، Tomak، Kondosku and Dasht Shad in West of the park، Dasht، CheshmehKhan and Armadlu in South of the park، Robat Ghahrahbil in East of the park and Lohondor، Yelcheshmeh and Behkade in North of the park.

In this study we first determined parameters and their influences on fire event، then information related to these parameters was collected from the related organizations as well as by inventory in the study area. Affecting parameters were prepared in the ArcGIS and IDRISI software packages. Based on topographic map، Elevation ranges from 467 to 2342 m above sea level in the study area. slope from 0 to 72 degrees and slope aspect maps with 9 classes were extracted from a Digital Elevation Model (DEM). Normalized Difference Vegetation Index (NDVI) map was extracted from MODIS satellite images of 2011. Humidity and temperature isopleths maps were obtained from interpolation of meteorological data 2001-2011 years of climatology and synoptic stations around the park based on Inverse Distance Weighting (IDW). Considering the effect of the presence of hunters and ranchers on fire events in the park، the distance from arresting positions of offenders in 2007-2012 as was mapped the higher probable presences in the park. Also a buffer zone was established from camps as tourist sites، villages around the park، transit road passing through the park. In the study area، 9 vegetation classes were identified including dense-canopy forest، low-canopy forest، average-canopy forest، very low-canopy forest، good pasture، medium-vegetated pasture، woodlands، bushy vegetation، and agricultural land. The occurred fires during the last 30 years was determined based on records of Central Office of Park، information provided by the guards as well as signs of the fire using GPS، then the Boolean fire maps was drown in Arc GIS software. After selection the parameters، fire hazard map prepared using logistic regression method in the IDRISI software. Logistic regression is run as computational binomial regression in which the dependent variables of nature are entered binary. The uses model accessory was assist with Relative operating Characteristic (ROC) and Pseudo-R2 statistics. Finally، sensitivity of variables was examined by removing them using ROC and Pseudo-R2.

The regression equation resulting from the model was calculated as follows: Logit (fire) = 38. 792 + 0. 05475*Aspect + 0. 79038*Tem - 0. 000666*Camping + 0. 0014*Elevation - 0. 00037*Shepherds + 0. 00036*Hunter + 0. 0081*Landuse -0. 7874*Moisture + 0. 0011*NDVI + 0. 0004*Road - 0. 051747*Slope - 0. 00006*VillageIn this model، variables such as aspect، elevation، mean temperature (tem)، distance from road، and presence of hunter، land use and NDVI are positively correlated with fire risk while parameters of slope، camping، presence of ranchers، moisture and distance from village are negatively correlated with fire risk. The ROC، Pseudo-R2 and Chi-square were calculated 0. 9267، 0. 3133 and 102227. 3 in the model، respectively. The fire risk map was prepared using logistic regression. The results of this study both from the obtained equation and from measuring the sensitivity of variables indicate that temperature and humidity are affecting on the occurrence of regional fire. Since the ROC statistic of 0. 7 indicates low accuracy، 0. 7-0. 9 value indicate the practicability and a value more than 0. 9 represents the high accuracy of model and Pesudo-R2 values greater than 0. 2 can be considered as a relatively good fitness، in this study ROC Pesudo-R2 values were found 0. 9264 and 0. 3133، respectively، indicating the high accuracy and good fitness for the fire risk model. Therefore logistic regression can be introduced as an appropriate method to classify the fire risk. Understanding the behavior of forest fire and factors causing the appropriate environment for fire occurrence and influencing on fire behavior are of high importance for fire forest management، thus this model can be useful for designing of fire management and taking preventive measures in high fire risk areas.

Considering the location of area، high temperatures and low humidity that provides favorable conditions for fires، and also given the high traffic of travelers، tourists، ranchers and hunters allowed in the park، the results showed that fire risk is in this park. Due to the high accuracy obtained from the logistic regression model in this study، one can claim that this method is appropriate for the evaluation and modeling of fire risk thus the resulting model can be used for preventive measures.

Droughts are long-term phenomena that can affect large areas and cause severe downturn in economic and social activities. Recognizing this phenomenon، its features and properties، knowledge of facilities، capabilities and talents of areas and providing short and long term solutions leads to the effort of the surface water resource managers to prepare for drought mitigation. The Regional distribution of drought is its most notable feature. Accordingly، regional analysis of drought conditions compared to its station survey results in a much more complete understanding of this phenomenon. Therefore، awareness of the severity، duration and extent of the area affected by the drought and the possibility of its occurrence in the certain return period can be useful in the management of water resources and the condition in which these vital resources are threatened (water، soil، forest and pasture). This can help managers in making appropriate decisions to minimize the damage caused by years of drought. Determining the characteristics of intensity، duration، frequency and level of involvement with the drought and the relationship between them can be a great help for authorities and researchers towards appropriate management of surface water resources، soil، agriculture، environmental، urban and rural planning and the tourist. According to the importance of drought in the North West of Iran in recent years، we have decided to identify and evaluate drought features to deal with this phenomenon correctly. The Study Area: The study area is located in Western North between 440220to 480222 Eastern longitude and 355805to 394616 Northern latitude this area surrounds eastern and western Azerbaijan and Ardebil provinces. The researched area included two areas 0f h1 and h2 namely some parts of Caspian Sea and Orumie Lake from hydrological view.

This study was conducted to investigate the meteorological situation of drought in the North West of Iran by selecting monthly rainfall data from the studied stations among synoptic stations with 22 years of data in terms of geographical location and climatic conditions with proper distribution in the area. The required information was prepared by the Meteorology and Water Management organization. By collecting data from 20 stations for 22 years (October 1988 to September 2009)، a data file was prepared in the required format by the Excel software. To identify، analyse and monitor the drought in the above stations، the Standardized Precipitation Index، SPI was used. McKee et al (1993) determined a threshold for drought in a time scale. Drought occurs when SPI consistently becomes negative or highly reaches to -1. The drought ends when SPI becomes positive. Therefore، a drought has a period of which the beginning and ending and the intensity are determined based on the values obtained in the continuous ongoing months. In order to calculate the SPI، the mean، standard deviation and skewness of monthly precipitation data is calculated; then، the logarithm of precipitation data is taken and the data logarithmic mean is calculated. Using the defined relations، scale factor and the form α and β are calculated. Then، data is fitted to gamma function; finally، drought index value is determined by Abramowitz-Stegun approximation. Therefore، the SPI is obtained from displacement t by various formulas according to magnitude of a displaced gamma value. The numbers obtained to determine the 3، 6، 12، 18، 24 and 48-month droughts are also used. Results and Disscution: The results show that the overall frequency of 1، 2 and 4 month droughts have the most iteration in all stations and the frequency of، 3، 5، 6، 7، 8 and 9 month droughts have the least iteration. The regression equations are used to estimate the relationship between frequency and duration of drought in the stations of North West. Equations obtained by the independent variable، duration، show that the trend was reversed between the two stations and does not merely follow a one-order linear equation. For a sudden increase in the frequency of droughts in 4 and 5 months changes the general trend of decreasing and removes the linear mode. On the other hand، decreased frequency is not proportional to increased duration of drought and there are various slopes. By fitting frequency and duration data to non-linear equations، as a result، R2 can be considered as the suitable equation criteria for determining the severity of the relation. R2، that is the ratio of the square of the predicted variance to the variance of the observed values، is higher. In other words، the coefficient shows how much of the total variance of the observed variable can be explained by the variance of the predicted values by the regression model. Creating a 264*20 matrix by SPSS، wet and drought coefficients are grouped. With this method، the stations are divided into 4 clusters (separate groups) in terms of wet-drought features. based on SPI values، stations included Piranshahr، Sardasht، Saghez، Mahabad، Orumieh، Maragheh، Tekab، Zarina Obato and Zanjan in the first group، Astara and Pars Abad (Group II)، Ardebil، Ahar، Khalkhal، Mianeh، Tabriz، Sarab (Group III) and Julfa، Khoy and Maku in Group IV. Hence، wet and drought conditions in terms of both spatial and temporal stations are almost identical in stations of a group and differ between groups. As noted in the theoretical discussion of the drought characteristics، onset، termination، intensity and level of involvement is very important in terms spatial and temporal conditions. In this regard، an 8 month period (February to September 2007) was selected and wet-drought classes were zoned on the studied region in the form of 8 maps using GIS. Reviewing the drought monitoring occurred in September 2007، it is clear that a large part of northern West in September was involved with the drought in the defined ranges، while droughts in September covered total area in all 4 periods. The above analysis has been performed for other months of 2007.

Drought frequency has mostly occurred in the weak and moderate intensities during the considered time cycle. The frequency-duration relation indicates a reverse correlation between two characteristics of droughts. The results obtained from analysing droughts occurred in the North West of Iran indicate that frequency of 1-، 2- and 4-month droughts was most-iterated frequency in all stations. Therefore، it is not clear that all short-time droughts are more than long-time droughts. For example، the frequency of 3-month drought is lower than that of 4-month drought. Correlation of SPI values at 20 studied stations indicates synchronized drought in adjacent stations; the rate decreases with increasing distance. Given that the equation is of 6 orders in most of the times، the curve is sinusoidal and nonlinear. On the other hand، decreased frequency is not proportional to increased duration and different slopes can be observed. Therefore، the duration-frequency relation cannot be linear. In addition، grouping the stations into four separate groups suggests an extra-group adifference between stations of a group and little or no difference between inter-groups. Hence، wet and drought spatial and temporal conditions are almost similar in stations of a group and differ between groups. Monitoring drought occurred in September 2007، finally، it is clear that a large part of northern West was involved with SPI drought in the September within the defined range; according to maps، it is not clear that spatial behaviour of drought was the same in all stations during drought.

Natural hazards have existed in all periods of human life، but nowadays due to the exponential growth of human and population density in all aspects of life، especially in high risk areas، human has been faced with major disasters such as the Asia tsunami، Hurricane Katrina and the earthquake in Sichuan of China with significant casualties even in developed countries. These hazards in many cases have caused severe damages on human community in both urban and rural societies and their effects are perceptible in environmental، social، economic and psychological aspects in human settlements for several years. A basic concept in natural hazards analysis on human community has been hidden in pathology of economics and mainly depends on diversity of economic and macroeconomic performance before the occurrence of a natural disaster. For instance، Caribbean is small country that its vulnerable economics mainly depends on tourism، agricultural exports and sales of products. Study Area: Alamut region is adopted for the case study. The mountains native، the valley location of the Alamut region and poor access of this area to road cause to consider it as a human rural area with 67 settlements (Claye Moalem city and 66 villages of up and down Alamut roud). Ecological position of Alamut area (in both natural and human)، on the one hand، depicts many factors and potentials for the occurrence of natural hazards. On the other hand it indicates the weakness of existing structures، particularly in human ecological aspect when the hazards happen. The appropriate reasons، (for example، the numbers of active faults، weak tectonic bed، existence of tectonic failures، and wide belt of thrust sedimentary sand stones، record of seismicity and also placement of 60 villages in expose of flood and earthquake risk، distribution of village and low levels of literacy in rural areas)، take the attentions toward the natural hazards and identifying common risks as the first step of the natural hazards management. 3. Material and MethodsThis methods can be used to transform data، such that the transformed data have similar characteristics (e. g.، mean or variance) at all locations، are discussed. In other words، the concern is with nonstationary models and with methods that can be used to transform، or otherwise modify، data so that a stationary model can be applied to the transformed data. A widely-used approach to accounting for spatial variation is a geographical weighting scheme. A distance matrix can be used to assign geographical weights in any standard operation: Where si is the i th location s، with coordinates x-y، and win is the weight with respect to locations i and n. 3. 1. Principal components analysisPrincipal components analysis (PCA) is widely used in many contexts for reducing the dimensionality of multivariate data. PCA is based on the variance–covariance matrix or the correlation matrix and، in the present analysis، the latter is used. The variances of the log-ratios differ markedly because the ranges of values on which they are based vary. When large multivariate datasets are analyzed، it is often desirable to reduce their dimensionality. Principal component analysis is one technique for doing this. It replaces the p original variables by a smaller number، q، of derived variables، the principal components، which are linear combinations of the original variables. Often، it is possible to retain most of the variability in the original variables with q very much smaller than p. Despite its apparent simplicity، principal component analysis has a number of subtleties، and it has many uses and extensions. A number of choices associated with the technique are briefly discussed، namely، covariance or correlation، how many components، and different normalization constraints، as well as confusion with factor analysis. Various uses and extensions are outlined. 3. 2. Geographically weighted principal components analysisFotheringham et al. (2002) introduce the idea of geographically weighted principal components analysis (GWPCA). With GWPCA، geographically weighted means and GW variances and covariances around the means are obtained (Fotheringham et al.، 2002)، with the result that there is a set of GW means، variances and covariances for each of the n data locations. Once the geographically weighted variance– covariance matrix is obtained، conducting GWPCA is straightforward. In this study statical society includes 2080 and 2589 persons in down of and up Alamut area separately that all were selected in 15-64 age group in 1390. Kokaram sampling with 0. 95 confidence factor and accuracy probability (P، Q=0. 5) in 610 samples was calculated. Spatial analysis of natural hazards based on the initial findings in seven natural risks such as earthquake، floods، falling، snow break، frostbite and blizzard with risk indicator method such as 11 identified indicator interns of conceptual is performed.

The output of the GWPCA model illustrates dominance and spread of the seven natural risks such as earthquake، flood، landslide، landfall، Avalanche، frostbite and blizzard using data co-variance matrix in each village with at least 30 neighborhood points. The index offear among residents indicates the spread of 56% flood risk. The index of disruption of rural transportation shows the spread of 57% landslide risk، which is the most important disruption of rural transportation. Finally، the index of prevalence of disease suggests the spread of 67% frost risk، which impressed the Valley Villages and villages in southern high lands of the Alamut.

The results demonstrate that flood and frostbite risks within the seven studied risk has the greatest impact on rural areas at Alamut valley. From the villagers view point، flood risk have greats fear، tend to immigration، destroy the infrastructure of the village and the risk of frostbite has the most villagers despair in the agricultural، interruption of rural economic activities and out breaks of disease among the villagers. Earthquake and landslide risk because the largest forced migration and the most disruption of transportation in villagers separately.

Drought is an insidious hazard of nature. It is often referred to as a «creeping phenomenon» and its impacts vary from region to region. Drought can therefore be difficult for people to understand. Drought is often classified into three types: (1) Meteorological drought is a period of months to years with below-normal precipitation. It is often accompanied with above-normal temperatures، and precedes and causes other types of droughts. Meteorological drought is caused by persistent anomalies (e. g.، high pressure) in large-scale atmospheric circulation patterns، which are often triggered by anomalous tropical sea surface temperatures (SSTs) or other remote conditions. 4–6 Local feedbacks such as reduced evaporation and humidity associated with dry soils and high temperatures often enhance the atmospheric anomalies، (2) Agricultural drought is a period with dry soils that results from below-average precipitation، intense but less frequent rain events، or above-normal evaporation، all of which lead to reduced crop production and plant growth، and (3) Hydrological drought occurs when river stream flow and water storages in aquifers، lakes، or reservoirs fall below long-term mean levels. Hydrological drought develops more slowly because it involves stored water that is depleted but not replenished. A lack of precipitation often triggers agricultural and hydrological droughts، but other factors، including more intense but less frequent precipitation، poor water management، and erosion، can also cause or enhance these droughts. Drought is different than aridity، which is a permanent feature of climate in regions where low precipitation is the norm، as in a desert. So many factors are important in drought creating. Human factors، such as water demand and water management، can exacerbate the impact that drought has on a region. Because of the interplay between a natural drought event and various human factors، drought means different things to different people. In practice، drought is defined in a number of ways that reflect various perspectives and interests. Three commonly used definitions for drought are based on: agricultural، Meteorological and Hydrological indexes. Of all natural disasters، drought is the most gradual and hard to predict، also are among the most costly weather related events، in terms of economics and loss of life. Iran country، because of its position on drought belt extremely is exposed to drought and the damage of this creeper disaster. Main affect of this disaster are tangible in agricultural dimension and for this reason، after drought happening، the different reactions could be observable from farmers. Amount of Damages and lesions in economic، environmental and social aspect and also، farmer’s resistance in front of this disaster are appearance from variety way. Community and farmers Resilience are one of the main instruments for precaution of crisis creating in result of living in dangerous place. Desertification and leaving the farmlands by farmers are the common impacts of this disaster that happen because of weakness in drought management and Expresses low levels of resiliency and flexibly in different dimension. The recent drought in Iran and its damages are the alarm of farmer’s vulnerability in front of this phenomenon. Study Area: Ijrud County is one of the most hazard prone areas in Zanjan province about drought disaster. This County is a county in Zanjan Province in Iran. The capital of the county is Zarrinabad. At the 2006 census، its population was 35،661، in 9،029 families. The county is subdivided into two districts: the Central District and Halab District. The county has two cities: Zarrinabad and Halab. Agricultural production is one of the most important aspects of economic growth in Ijrud rural areas. In recent years، decreasing rainfall rate، weather warming، misuse of water resource and inappropriate irrigation systems are the main reason for drought event in this area and resiliency of farmer are so low in front of it. Rural Resistant and resiliency a mount are different and is depended to so many factors. For this study، we chose 20 rural of Golabar rural district that have 3176 farmer family and chose 388 farmers as sample community by Cochran formula. The main purpose of this study is ranking the effective factor in farmer resilience. This study has been made by using of descriptive- survey methodology and by data gathering of 388 farmers in Ijrud region، through of questionnaire. After community sample size determination، questionnaires design based on extracted indexes and complete by 388 farmers that were chose by Cochran model. After data entry، VIKOR model from multi-criteria decision-making techniques was used to analyze the data. Therefore، we have three stages for this process: - Determination of indexes and measurements of farmer’s resilience based on theorical literature and studies and in three dimensions (policies and governmental aid، economical –social capacities and local practices). - Determination of affections amount of each of these factors and indexes by using of statistical approaches. - And finally، ranking of important factor in farmers resilience in front of drought by using of MCDM techniques. Data gathered from case study area based on questionnaire method and had been analyzed by SPSS and MCDM techniques. 4. Result and Discussion T-test result indicates the low level average factors in local farmer’s resilience. This is especially obvious in governmental supports and strategies dimension. Also، the result of VIKOR technique indicate that based on farmers attitude، the insurance development، Warning System about drought disaster، damage assessment and Indigenous knowledge and using of it، are the most important factors for resilience increasing in farmers and in front of drought. In new pattern of risk and hazard management، in addition of emphasis on structural and non structural management before of hazard happening، recovery and returning of community and its people after disaster occurring will be important. Drought is one of these hazards that need to be managed in all of period: before، among and after occurring. We have tow category of definition about phenomena as like drought: Conceptual and operational definition. Conceptual definitions، formulated in general terms، help people understand the concept of drought. For example: Drought is a protracted period of deficient precipitation resulting in extensive damage to crops، resulting in loss of yield. Conceptual definitions may also be important in establishing drought policy. For example، Australian drought policy incorporates an understanding of normal climate variability into its definition of drought. The country provides financial assistance to farmers only under “exceptional drought circumstances،” when drought conditions are beyond those that could be considered part of normal risk management. Declarations of exceptional drought are based on science-driven assessments. Previously، when drought was less well defined from a policy standpoint and less well understood by farmers، some farmers in the semiarid Australian climate claimed drought assistance every few years. Operational definitions help define the onset، severity، and end of droughts. No single operational definition of drought works in all circumstances، and this is a big part of why policy makers، resource planners، and others have more trouble recognizing and planning for drought than they do for other natural disasters. In fact، most drought planners now rely on mathematic indices to decide when to start implementing water conservation or drought response measure. Identifying the factors of resilience increasing، is the main stage for natural hazard vulnerability reduction، especially in rural area that people life style is depend on environmental potential such as water، land and…. Based on the final result، the planning for resilience improvement need to having a long term strategies and local government offers، awareness about insurance benefits and capability for drought prediction are the most solution that could increase rural farmer resilience.

The effect of blocking on Iran’s precipitation in numeral way and long-term has not been done yet. However، in some researches based on weak indexes like one-dimension has been implied to Iran that in studying many cases we observe lack of blocking event and or their continuation that has been for less than 5 days. This phenomenon in some cases occurs in our country directly and most of its parts are under its predominance، but according to its placement in proximity of zone، its maximum in the world، Atlantic-Europe zone is influenced by its effects repeatedly and probably may be affected more by recent cases. Given the fact that in each zone، precipitation is considered as a permanent development base، therefore the knowledge of effective models on it has an extraordinary importance in order to predict and knowing from them. On the other hand، with respect to this that most studies have been carried out in sample way، the knowledge of these patterns can have a high carefulness and accuracy in quantity way. Study Area: In order to investigate the blocking systems affecting the climate of Iran، at first the study area was chosen in the within the 0– 90N and 90W – 100E. At the second stage the origin and location of the blocking systems were determined and study area was decreased to the 20N – 80N and 40W – 100E in order to study only those systems in close contact with the climate of Iran. In order to better understand the effect of blocking patterns of precipitation and temperature the study area was limited to Iran.

Data related to geo-potential height of 500 hPa level in regard to two dimensions index of visible blocking، daily for cold season in year for a 65-year period from 1953 to 2012 in a 2/5 *2/5 network that is appropriate for studying the large-scale occurrences like the blocking was extracted from site NCEP-NCAR for an area between 0 to 90N latitudes and 90W to100E longitudes. Then the investigated zone was bounded according to the knowledge of the limit and the origin of the effective blocking on Iran’ weather from 40 W to 100 E longitude Using a quantity way of two-dimensional revelation and synoptic filters along with it، all blocking events were revealed. The effective happenings on rainfall were separated then these events with use of a factor analysis way were analyzed and based on classification way of K-means were categorized and finally the blocking prevailing events that are effective on Iran’s precipitation were identified. Four prevailing patterns for rainfall were extracted that the first two models، the precipitation pattern resulted from the left and right half were totally considered as omega kind model. Two other models were including dipole and Rex Patterns of blocking. Synoptic conditions of above levels of atmosphere and ground level were analyzed for each pattern

In omega pattern، right trough of Iran is located in front of the trough. Lifetime duration of this blocking from forming until puberty and death has been in total the days and the system with regard to the feature of its being quasi-stationary، has had a moving toward east with a very low speed and this matter has been caused that Iran’s different parts from west to east is located respectively in front of trough and under trough axis several continuous days and have instable conditions and necessary rise for raining. In omega model، left trough of west and western north is situated in front of the left trough and conditions for instability and continuous precipitation has been ready and in most stations in addition to the permanence of rainfall for several days، it was also shown heavy rainfall. In dipole pattern of west and western north، the country is located in front of below low-rise trough and conditions are appropriate for rising، instability and continuous and heavy precipitation. In Rex Pattern، ridge is placed in high latitudes and trough is situated in lower latitudes and Iran is influenced by in front of below trough. In this model، in Iran’s western half، conditions are available for constant and heavy precipitation

Blocking is one of the atmospheric large-scale phenomenon which have numerous synoptic phenomenon synoptic scales. The effective blockings on Iran’s weather among atmospheric parameters have the most effect on rainfall. Blocking event in some cases can on account of severity and continuous precipitation in a zone lead to flood and damage، therefore the knowledge of its synoptic prevailing pattern in order to predict and issuing the necessary per-awareness’s and taking the essential measures in the affected area in terms of risk management have considerable importance. Among the blocking patterns leaded to rainfall، the omega model has more abundance than other models. In omega pattern، two marginal troughs on ground level have a low pressure and under and in front of trough، conditions for raining are available. In terms of the continuity of more precipitation، the omega model can has more permanence and other kinds have less severity and permanence. Statistical survey of the precipitations resulted from blocking showed that blocking can lead to continual and severe rainfalls، but every continual and severe rainfall is not resulted from blocking.