فصلنامه پژوهش های جغرافیای طبیعی
پیاپی 90 (زمستان 1393)

Thunderstorm rainfall is one of the most important climatic phenomena in the northwest of Iran that has specific variability in spatial distribution. These rains have an important role in case study area climates. The purpose of this study is investigation of spatial distribution of Thunderstorm rainfall of Mountainous Areas of the Northwest of Iran to modeling Thunderstorm in northwest. Because of that TRMM images precipitation data from 2009 to 2012 is selected & in the software Arc Gis، ENVI and EDRISI، have been processed.

The most important indicator of climate in a region is vegetation community. Climate can be different over large areas، because of changes in vegetation community. Vegetation influences weather and climate in its surrounding areas mostly by way of evapotranspiration and albedo so they play a role in the earth’s energy balance. These effects on the earth’s energy balance are taken through air temperature، relative humidity، rainfall، solar radiation and cloud cover on their own micro-weather (Neilson، 1986، Small and Kurc، 2003 and Weiss، et al 2004). Disasters such as drought، flood، forest fire and among them can occur whenever the global energy balance become outside of normal range. Remote sensing data provide valuable information for vegetation studies because it presents a quick look evaluation of the vegetation conditions. Normalized Difference Vegetation Index (NDVI)، Land Surface Temperature (LST) and land surface albedo are key biophysical variables for studying land surface processes and surface-atmosphere interactions. These variabels can be calculated by transforming raw satellite data. The aim of this paper was to study relationship between NDVI، LST and land surface albedo due to the impact of vegetation on surface temperature and albedo and identify dryness status in the northern Iran.

Study area is located in the northern part of Iran which covers with dense vegetation such as Hyrcanian forests in the north and sparse vegetation in the southern part of the Alborz Mountain range. This area is an alteration bio-climate region lying between the humid climate in the north and arid and semi-arid climate in the south. The methodology used in this study consisted of remotely sensed data processes. The remotely sensed data processes involved data acquisition of Moderate Resolution Imaging Spectroradiometer (MODIS)، data pre-processing (i. e. atmospheric correction، geometric correction، and data masking)، and data processing (i. e. derivation of vegetation، biophysical indices such as NDVI، LST and land surface albedo variables). In this study، MODIS data was selected because the MODIS sensor has several benefits compared to other instruments for example MODIS has a wide swath of 2330 km that covered the entire study area. The MODIS dataset had a variety of products that each contained different levels of data processing. In this study، Level 1B dated July، 2010 (MOD021KM and MYD021KM calibrated and geolocated) was used to derive NDVI and surface albedo، and retrieving LST. This level 1B collection contains calibrated and geolocated radiances at-aperture for all 36 MODIS spectral bands at 1km resolution. In this study، Simplified Model for Atmospheric Correction (SMAC) was used for atmospheric correction of MODIS data. Absorbtion in visible light (solar radiation) occurs in live green vegetation because of photosynthesis. Scattering (reflectance) of solar energy in the near infrared occurs at the same time. This difference in absorption and reflectance lead us to NDVI. NDVI is an vegitation index which measures this difference to show vegetation density and condition. NDVI value ranges between -1 and +1. The values close to zero means no green vegetation and close to +1 (0. 8 - 0. 9) represents the highest density of green vegetation. LST is an important parameter in determining the earth radiation budget and heat and moisture flow between the surface and the atmosphere and temperature strongly influence vegetation processes. Thermal bands of MODIS data (band 31 and 32) converted to radiance then converted to brightness temperature using plank law for calculating surface temperature. Albedo is also an important bio-physical indicator of reflecting land surface energy distribution and balance. In the process of broadband albedo retrieval، an empirical regression was used for MODIS data (Liang et al.، 2002). Finally، regression and geostatistical approach (e. g. CoKriging) was used in this study to estimate LST and surface albedo using NDVI of MODIS data.

In this study three criteria such as mean absolute error، root mean square error and mean absolute percentage error have been used to measure the differences between the values estimated for LST and Albedo using regression and CoKriging geostatistical method. The results obtained in this research indicate that the geostatistical method of cokriging has good potential to estimate LST and surface albedo using normalized difference vegetation index. The results of the study show that changes in vegetation cover alter the LST and surface albedo، leading to a local temperature change. Plants and forest have a very low albedo and absorb a large amount of energy. The relationship between normalized difference vegetation index and LST and surface albedo equations were then used to found the surface dryness condition in the study area. The result of 3D feature space of Albedo-NDVI-LST spectral shows that it has a suitable index for extracting drought information. The study revealed that coastal and forested northern slopes of the Alborz Mountain are identified with high normalized difference vegetation value (0/85)، minimum surface temperature (23° C) and albedo (7%). The southern part of Alborz Mountain and the central Iran experiences low normalized difference vegetation value (-0/09)، high surface temperature of 45 ° C and high surface albedo (38%).

In this study، the relationship between NDVI and LST and surface albedo was analyzed to estimate LST and surface albedo derived by regression and CoKriging methods. It has been recognized that there is a strong correlation between albedo، LST and NDVI. By comparison of the regression relationship among LST، Albedo and NDVI، results exhibit that LST and Albedo are negative correlations with NDVI. In this paper، a 3D feature space of Albedo-NDVI-LST spectral is analyzed for monitoring surface dryness condition. The result represents that surface albedo nad LST is affected by the change of vegetation. This 3D feature space is reliable index to show surface dryness status for soil and plant cover. it is recommended that 3D feature space of Albedo-NDVI-LST spectral can monitor to the surface dryness condition and also it is easy to operate for quick surface dryness assessment. Studies are underway to incorporate other variables in surface dryness condition.

Water vapor is considered to be one of more significant atmospheric constituents as it contributes in precipitation and is also a critical element of the climate system. This climate element extended from earth surface to upper level of troposphere that potentially precipitable. Accordingly it called perceptible water. Therefore The total atmospheric water vapor contained in a vertical column of unit cross-sectional area extending between any two specified levels، commonly expressed in terms of the height to which that water substance would stand if completely condensed and collected in a vessel of the same unit cross section. The total perceptible water is that contained in a column of unit cross section extending all of the way from the earth''s surface to the “top” of the atmosphere. The water vapor component of air requires monitoring because of its importance to weather and climate and the essential role it plays in the operation of the global water cycle. This is the reason that atmospheric perceptible water determines the potential value of precipitation as well as an index for forecast precipitation for a certain time of year. So it is an important variable in climatic study and climate change survey. Precise calculation of perceptible water needs to know about the atmospheric water vapor amount. However the amount of water vapor is determined by many factors including atmospheric density، temperature، cloudiness، wind direction and velocity، humidity in top of geographical situation. All of these factors determine the capacity of humidity، distances from the water bodies as well as leading the water vapor to any location. In this paper it has attempted to calculate perceptible water in atmospheric column from the earth''s surface to the top of troposphere. This purposeful effort has been done to achieve the long term trends of precipitable water over Iran atmosphere. In order to accede this purpose the NCEP/NCAR data has been applied. Data and

Consider a column of liquid water with cross-sectional area، and certain height. This height is the perceptible water. One way to determining the mass of water vapor (in grams) in a vertical column one square centimeter in cross-sectional area that extends from Earth''s surface to the upper reaches of the atmosphere. Mathematically، if x (p) is the specific humidity at the pressure level، p، then the perceptible water vapor، PW، contained in a layer bounded by pressures p1 and p2 is given by Where g refers to gravity acceleration. For the purposes of our study، the pressure and specific humidity of NCEP/NCAR which exist for each 6 hours has been used. This data characterized by 2. 5 longitude*2. 5 latitude degree resolution. In order to find out what we had decided to find، many software including Grads، Surfer and Matlab have been used. So at first general characters including mean and coefficient of variation of percipitable water has been mapped. Then the trends maps have been represented. In addition we have used sequential Man-Kendal method to diagnosing trends during the time sequence. To find the cause and the result of this trends، humidity advection and long term change in temperature as well as precipitation over Iran has calculated.

The mean of precipitable water in Iran is about 14. 3 mm. According to coefficient of variation، the most stationary amount of the mean is at 18:00 o’clock meanwhile the most non stationary take place at 06:00 o’clock. Central Iran which located in dry region as well as far from water bodies، it contains much more precipitable water in compare to Zagros mountain chain. The most precipitable water as well as lowest coefficient of variation is happened in Caspian Sea coast as well as Persian Gulf coasts. In general mountains area has experienced more variation in compare with law areas. In regard for trend analyses، spatial distribution of daily trends has been mapped in fig 1. As it is clear almost all over Iran (except in Bandar Abass and Chabahar) decreasing significant trend by -0. 000043 to -0. 000067 mm/day especially in south as well as southwest of the country has been occurred.

Surveying precipitable water over Iran has shown that this climatic parameter is dramatically depending on local as well as global factors. Accordingly the most spatial variations take place in 00:00 and 06:00 o’clock. Trends analyses have shown decreasing significant trend by -0. 000043 to -0. 000067 mm/day in the country.

In the water resources planning and management، rainfall is considered as the main representative factor of region''s hydroclimate system. There is a high level of spatial and temporal variability in rainfall events. Rain gauges are used for precipitation measurement in different points of the region. Due to limitations of rain gauges development، it is impossible to measure the exact distribution of rainfall over an area، so it is needed to select the optimal number and locations of the rain gauges in a region. There are several factors that affect the optimal number and location of stations، thus، development of an optimization model for development of rain gauges network is necessary. In this study an optimization model is proposed for determining location of the rain gauges considering the transformation entropy and the regional rainfall estimation error. In this model، the points with the minimum transformation entropy and the maximum rainfall estimation error are considered as candidates for development of new stations. The results of two considered criteria are combined to determine the location of the new stations. Geogrpahic information system (GIS) is used to better represent the results of rainfall spatial analysis and explain results of the proposed optimization model. A sub basin of Karkhe basin in South West of Iran has been considered as the case study of this study. Results show that using new rain gauges which are determined to be 17 using the proposed approach could improve accuracy of spatial analysis of rainfall siginficiantly.

The use of climatic and natural variables in the regulation of agricultural activities has a particular importance. Of the important characteristics of climate are the onset and retreat dates of main rainy season which have a determining role in the agricultural activities such as seeding time، cultivation period and other agricultural programs and strategies like irrigation. Iran residing in the arid and semiarid region has a variety of climates and consequently experiences high irregularities of spatial and temporal distribution of precipitation and other climatic elements. Southern coasts of Caspian Sea in Iran as a region with the highest precipitation in the country، has good potentials for agricultural activities. Among the most important crops for the development of cultivation in this plain is colza (canola). Since colza can be cultivated under rainfed conditions in high precipitation areas، therefore the analysis of precipitation characteristics in the region on the one hand، and onset and retreat dates of main rainy season in that plain on the other hand، can play an important role in the development of cultivation area. Average onset and retreat dates of main rainy season were calculated at selected stations of the region using an index called “cumulative percentage of mean daily rainfall during the year in 5-day periods (pentads)” with Instat software، and the relevant graphs were plotted. Average onset and retreat dates of main rainy season are the dates of year when 10% and 90% cumulative mean annual rainfall during pentads are obtained respectively. The length of the main rainy season is taken as the time interval between the rainfall onset and retreat. The cumulative rainfall based on pentads is used to decrease the daily rainfall fluctuations during the year، so that the detection of onset and retreat dates of main rainy season is much more convenient. Based on the dates obtained from the software and using the daily data of climatic elements including rainfall، minimum temperature، maximum temperature، minimum relative humidity، maximum relative humidity، solar radiation and wind speed in a 26-year period (1984-2009)، and also with the aid of soil properties at the stations، the cultivation period and potential yield values of colza were estimated by CropSyst model. Finally، based on the highest yield obtained from the dates entered to the model، the most suitable planting date and duration of cultivation were determined. The results of this study showed that the onset dates of main rainy season in the stations vary between 30 Aug to 1 Nov، and these dates have had less fluctuations in comparison with the retreat dates; since the retreat dates have had differences about 50 days، i. e. from 17 Mar in Bandar Anzali in the west to 6 May in Gorgan in the east of the region. The low differences among onset dates of main rainy season in the stations prove the regularity of rainfalls which result from the regularity of rainfall-producing mechanisms in the region. This occurs especially in September as the onset of rainy season in the region and the onset of advection rainfalls originating from Siberian high pressure، particularly around the Rasht and Bandar Anzali. It seems that determining the onset and retreat dates of main rainy season using rainfall amounts leads to more reasonable results than the use of number of the rainy days. Also the length of the main rainy season in the stations varies from 185 days in Manjil to 234 days in Ghaemshahr، which represents a few weeks difference in comparison with the graph illustrated by Sedaghat (2007:36) regarding the cumulative mean monthly rainfall in Iran. The most appropriate planting dates for colza in the selected stations of the region were suggested from 5 Oct in Manjil to 20 Nov in Bandar Anzali. Relevant cultivation durations in the stations vary from 173 to 209 days. Potential yield of the product in the region shows significant direct correlation with amount of rainfall، and significant inverse correlation with distance from shore. Recognition of characteristics of main rainy season and its onset and retreat dates has a determining role in the various activities especially agricultural activities. In this research average onset and retreat dates of main rainy season were calculated at selected stations of coastal provinces of Caspean Sea in Iran using an index called “cumulative percentage of mean daily rainfalls during the year in 5-day periods”. The results showed that the onset dates are more regular than the retreat dates due to regularity of rainfall-producing mechanisms in September. Differences in suggested planting dates in this study and the report of the Ministry of Agriculture can be related to different varieties of colza used in the studies، and different calibrations of models based on the climatic and natural circumstances at the various parts of the country; Hence our special offer for respected researchers in the future studies is to calibrate the CropSyst model with regard to the climatic and natural circumstances of the study area.

To avoid the adverse consequences of tourism، some decisions must be made about its development. To achieve this purpose، one of the first steps is to identify the suitable regions for tourism development and land use planning which will eventually lead to optimum model of development of tourism destination. Due to having unique natural attractions such as mountains، dense forests، rivers، up-country - historical villages، waterfalls and natural springs as well as beautiful beaches of the Caspian Sea، Talesh County has a very good potential for ecotourism. However unfortunately، the lack of proper tourism management as well as the unsustainable tourism development have led to destruction of these unique resources with a growing trend. As the largest county of Gilan province، this county is located in the west of this province. According to the intended evaluation features of the research which aims at identifying the ecological capabilities and the regional zoning in terms of ecotourism development capabilities and nature-based tourism planning، the feasibility of the areas of ecotourism of the region was performed by the use of Geographical Information System (GIS) and the ecological model of ecotourism for Iran and with regard to the special conditions of the region. In this survey، the researcher used the Arc GIS 10 software in order to overlay the maps and create the layers. Moreover، she used the information which had been obtained through climatic data (temperature، precipitation، humidity، number of sunny days)، topography، vegetation، soil texture، geology and protected areas. The model used in this study was the ecological model of ecotourism of land use development which had been proposed for Iran and had been based on the systemic analysis and multiple criteria evaluation. This model classifies the region into two groups of intensive and extensive ecotourism and each of which are classified and analyzed in two classes. The first class represents the most suitable condition and the second one represents the suitable condition for the development of ecotourism. To achieve an optimal model for the evaluation of the ecological potential of ecotourism، in the first step of the research، in this model the effective spatial and descriptive data were collected and then through georeferencing these data and linking them with the descriptive tables، the data layers were created. To achieve this purpose، the researcher used the Arc GIS 10 software. After the data layers were preparing based on data classification in evaluation model، the classified information was obtained. Then، through overlaying the maps، the spatial information was integrated together and based on their ratings، the potential regions for ecotourism development were identified and the extent of which were determined. To overlay the maps The findings suggest that 406 square kilometers of Talesh lands have the potential for development of intensive ecotourism and 1541 square kilometers of Talesh lands have the potential for development of extensive ecotourism. In addition، Markazi district has the most potential for the development of intensive and extensive ecotourism. Given that the regions which are related to intensive and extensive ecotourism of the first type are mostly seen in plains and coastal areas of Talesh County، these regions have the necessary conditions for the development of water- base and coastal tourism activities as well as the rural tourism and agritourism. The regions which have the potential for intensive and extensive ecotourism of the second type are mostly located in the highlands of the county. These regions have the necessary conditions for the development of the mountain Sports and activities. Due to the existence of Marian and Agh Evlar up-country-Historical villages، the scientific and specialized tours are also recommended in this area. In general it can be concluded that most parts of the county have the necessary conditions for the development of ecotourism and it indicates that Talesh County has a high potential for ecotourism development. It is in such a way that about 19% of the total area of the county (406 square kilometers)، is suitable for the development of the intensive ecotourism and 71% of its total area (1541 square kilometers) is suitable for the development of the extensive ecotourism. Moreover، given that Markazi district is of the most regions for the development of two types of intensive and extensive ecotourism، planning for the development of infrastructures and providing programs for tourism development in this region is very essential.

Natural disasters management requires local information in order to be ready against dangers and reduce their procedure. Hence، evaluation of landslide occurrence in the area which is prone to landslide due to geographical condition and human constructions is high crucial. Ghale Chai dam located at Ajabshir Watershed is one kind of such areas. So the aim of present investigation is to identify hillside instabilities and movements and their influencing factors to prevent their harmful effects on natural resources and other parts of economical and engineering development and recognize points with high prone of danger. Hence، the aim of present investigation is to assess analytical network process and Heuristic method in determining the landslide prone areas in range axis and reservoir of Ghale Chai dam of Ajabshir. Methods and Materials: The efficiency of network analysis process and logistic regression method were studied to investigate landslide potential in studied area dam. ANP model building requires the definition of elements and their assignment to clusters and a definition of their relationships (I. e. the connections between them indicating the flow of influence between the elements). Like AHP، ANP is founded on ratio scale measurements and pair wise comparisons of elements to divide priorities of selected alternatives. In addition relations among criteria and sub-criteria are included in evaluations، allowing dependencies both within a cluster (inner dependence) and between clusters (outer dependence) (Saaty: 2001). Pairwise comparison is now done، both for weighting clusters (criteria) and for estimating the direction and importance of influences between elements، numerically pictured as ratio scale in a so-called super matrix. Network analysis process was used for the first time in Iran in order to evaluate landslide، done using super decision and arc GIS software. However، to assess landslide susceptibility using heuristic method there are two common approaches: direct and indirect method. The first method applies direct assessment to interpret susceptibility in the field on the basis of detailed maps (geomorphological maps، for instance). The latter does not assess directly in the field، but via data integration techniques in any particular software. This study uses indirect heuristic method. Heuristic approach is a semi-qualitative method. Besides uses knowledge properties (expert opinions، previous research results or literature recommendations)، it also uses index-based procedures such as simple ranking and rating or analytical hierarchy process (AHP) in assigning weight and creating model. Concerning this، scoring and weighting process are crucial to build a model in heuristic approach.

Considering research questions، a three-layer network model composed of target layer، criteria layer and options layer was designed and organized in network analysis process. The priority of danger classes was determined based on their coefficients after doing paired comparisons among elements and clusters. Zoning map was classified in five classes from very high to very low. The weighting judgment process in pair-wise comparison gives a weight for every Influencing factor. From the calculation، the final criteria tree (with weight in 2 digits) was created. Bigger weights indicates that، the pertinent factor gives bigger influence toward the model. Aspect has the biggest contribution (0. 2519)، followed by distance to road and litology with value 0. 1786 and 0. 1747، respectively. On the other side، the lowest contribution is given by slope (0. 0387)، followed by Dem (0. 0590). No negative weights in heuristic method. The inconsistency value is 0، 0 62194: smaller than 0، 1. It means، according to SMCE validation، the choosing process is consistent. No improper stage while positioning the factor based on its importance to another After running paired comparisons between elements and clusters the priority of the danger classes based on their significance was determined and the coefficients of the factors showed that the aspect factor has the maximum effect in occurrence of the landslides if the area.

The Recognition of behaviors of the atmospheric circulation patterns and effective climatic elements in occurrence of flood is very important، especially because abnormal climate changes such as global warming in recent years tend to change in atmospheric circulation patterns and outbreak climatic inelegances in many areas in the world. Intensive and torrential precipitations in anomalous time and space is very important for a country like Iran with specific climatic characteristics and is always among the factors which in different geographical regions has some irrecoverable effects on humans life and finance and has affected human beings and nature widely. The south-west region of Iran that has been located in the windward slops of Zagros mountains and in the path of westerlies and rainbearing air masses، is among the regions which due to different atmospheric circulation patterns and receives heavy precipitations and is exposed to destructive floods. That flood of 20 November 2011 which has occurred in Khuzestan and Kohkilou-e-va-buyer-Ahmad provinces is obvious among them. This flood imposed many death tolls and caused a big mass of financial damages to those regions. Coordination before occurring accidents and hazards is the key factor in crisis management. Therefore identification of flood causing patterns and their punctual prediction can facilitate better management of crises and hazards and minimize mortality and financial damages caused by these type of natural disasters. This flood in the study area created by an extreme storm in western and southwestern regions of Iran. In order to analyze the synoptic pattern of this flood، the data of sea level pressures، surface wind directions، surface temperatures، geopotential heights of 500 Hpa and specific humidity and wind directions of 850 and 700 hpa and data representing omega values from NCEP/NCAR website has been collected and then synoptic maps were drawn by using GrADS software which were related to 2 days before flood until a day after that. Then the causes of flood were revealed by synoptic analysis of the maps. Analysis of synoptic maps reveals role of some systems in creating the flood. By positioning the pressure center of Sudan low between European high pressure and Arabian subtropical high pressure has been resulted to form a convergence belt over the Sudan and the Red sea. European high pressure caused the advection of cold air from high latitudes and in other hand، Arabian subtropical high pressure caused to advection of warm and humid air from low latitudes into the Sudan low - Red sea’s convergence belt. Convergence of northern cold air and southern warm air in this belt، tend to intensify the belt. Gradually، with intensification of the system and its NE move، the convergence belt lied over SW regions of Iran. Pressure map of 500 hp shows a deep trough in North Africa. This trough intensifies temperature gradient in upper levels of the atmosphere and following of this event، the trough becomes deeper and its axis lies over the Red sea. Analysis of specific humidity and wind direction maps of 850 and 700 hpa indicated that the humidity sources for the rainfall systems were the Red sea، Arabian Sea and Persian Gulf in 850 hp level and Red sea and Persian Gulf in 700 hp level. Locating Sudan low pressure between Arabian subtropical high pressure and European high pressure tends to create an air convergence belt with SW-NE trend from Sudan to north of Arabian Peninsula. Cold Advection from European high pressure and warm advection from Arabian high pressure finally intensify temperature and pressure gradients in the convergence belt and the transformed the system into a dynamic system. In result of advection of cold air to back part of the system، its eastward movement became faster and pull the system over SW areas of Iran. Movement of cold air in back part of the system caused an extreme updraft of air and generated a severe rainfall. The Arabian subtropical high pressure provided required humidity for this rainfall from warm waters of Red sea and، Arabian Sea and Persian Gulf into the system and eventually resulted in a heavy rainfall that in a short time generated the disastrous flood with abundant damages in study area.