iran

Water is a strategic and scarce resource that has become increasingly limited in recent years due to a variety of national and transnational factors, significantly impacting security, stability, development, and prosperity in various countries. The profound influence of water on these domains has positioned it at the forefront of the foreign policy and hydropolitical relations of numerous nations, including those in South West Asia. In recent years, despite the prominence of the water crisis and its implications for the relations between Iran and Iraq within scholarly, political, and media discussions, the complexities of this issue remain poorly understood, leading to disparate interpretations. The current research, which is exploratory in nature, utilized library methods for data collection with the aim of achieving a qualitative understanding of the multifaceted hydropolitical relations between Iran and Iraq. This study not only seeks to identify the content and methodological characteristics of existing literature but also aims to uncover research gaps in this field employing a qualitative meta-analysis approach. Through this method, the research examined 34 studies published between 2014 and 2023, including domestic scientific articles, theses, and contributions to reputable international journals. The findings indicate that a comprehensive analysis of the various dimensions of hydropolitical relations between Iran and Iraq has yet to be undertaken. In this context, the absence of accurate and reliable data, alongside the inadequacy of theoretical and cognitive frameworks, represents significant deficiencies in the existing research on the bilateral relations of these two countries.

The contemporary global landscape is characterized by heightened geopolitical competition, in which energy resources have evolved from being mere support for nations to becoming pivotal elements in the contest for power. This context has transformed corridors into significant arenas for competition, as each country endeavors to establish its position within the intricate network created by these emerging corridors. In this regard, the prevailing global geopolitical trend has intensified the competition over maritime chokepoints and secured access to cross-border markets.This research serves as a theoretical foundation, employing a descriptive-analytical methodology that incorporates a comparative approach, utilizing library and internet resources for data collection. Within the chronopolitical framework of Iran-Iraq relations, each actor strives to delineate its role in international corridors while pursuing various objectives. For instance, Iraq is actively engaged in the "FAW Corridor" initiative, whereas Iran seeks to expand economic cooperation and secure a place in the burgeoning alliances of the East. While it is challenging to make definitive predictions regarding the future of relations between the two countries from a chronopolitical perspective, emerging signs suggest a trend toward diminished cooperation and increased competition, influenced by a multitude of variables. A key indicator of this potential competition is the rivalry over transit routes (corridors).

Iran is one of the countries that is prone to natural hazards due to its geographical situation. One of the risks that has always threatened Iran is the risk of earthquakes. The land of Iran, as a part of the active tectonic zone of the Alps-Himalayas, has been affected by many tectonic activities over time, such as the appearance of the Zagros-Makran and Alborz-Kope Dagh mountain ranges in the Iranian plateau as a result of subduction of the Arabian plates. The Indian Ocean is one of the landforms resulting from this convergence. According to the geological situation of the Iranian plateau, this plateau is facing many disturbances and this problem has caused Iran to be one of the earthquake-prone countries in the world. Earthquake is the most important natural hazard that is always associated with a lot of human and financial losses. Due to its unpredictability and its power, this hazard has faced serious challenges in the seismic regions of the world. In fact, large earthquakes are one of the most destructive natural disasters, which often lead to widespread casualties and many deaths, and many cities are vulnerable to large earthquakes. Among the areas that are vulnerable to the risk of earthquakes are the metropolises because they house a large part of the country's population. According to the statistics of 2015, the metropolitan cities of Tehran, Mashhad, Isfahan, Karaj, Shiraz, Tabriz, Qom, Ahvaz and Kermanshah include about 27% of the country's population. Due to the importance of the subject, in this research, the seismic status of Iran's metropolises has been evaluated.

In this research, information related to the epicenter of earthquakes recorded in Iran during the years 1286 to 1402 (1907 to 2023), demographic information of Iranian metropolises, statistical information related to the state of constructions of metropolises, and also The information obtained from satellite images has been used as the most important research data. The most important research tools are ArcGIS (to prepare the required maps) and SPSS (to analyze the data). Also, in this research, the Analytical Hierarchy (AHP) model was used in order to weight the parameters. According to the desired goals, this research has been done in two general stages. In the first stage, a 100 km boundary is defined for each metropolis, and then the earthquakes that occurred in this area are identified. In the following, the earthquakes that occurred in metropolitan areas have been analyzed in terms of number and size. In the second stage, based on 6 parameters, the state of vulnerability of metropolises has been evaluated. After evaluating the metropolises in terms of the desired parameters, first the parameters were normalized and then the parameters were weighted using the AHP model.

The results of the evaluation of earthquakes that occurred in the outskirts of 100 kilometers of metropolises have shown that the largest number of earthquakes with 390 recorded cases was related to the outskirts of Shiraz metropolis, and Isfahan and Qom metropolises recorded 19 and 20 respectively. Have the least number of earthquakes. Also, the results of the survey of the number of earthquakes with a magnitude greater than 6 on the Richter scale have shown that the outskirts of the metropolises of Shiraz and Kermanshah had the largest number of earthquakes with 4 earthquakes, and the outskirts of the metropolises of Isfahan and Ahvaz There has been no earthquake with a magnitude greater than 6 on the Richter scale. Considering that in addition to earthquakes, other factors are also effective in determining the vulnerability of metropolises against earthquake hazards, in this study, population parameters, population density, percentage of open space and percentage of worn-out fabric are also used. Has been According to the results, the largest population was related to Tehran city. The highest population density was related to the city of Mashhad. The highest percentage of worn out fabric was related to the city of Tehran and the lowest percentage of open space was related to the city of Tehran.

The results of this research have shown that Iran's metropolises have different seismic potentials due to their geo-structural position, and also, under the influence of various population factors and constructions, different potentials in terms of damage. They are resistant to earthquakes. In this research, in order to investigate the seismic status of metropolises, the earthquakes that occurred within 100 kilometers of them have been analyzed. According to the results, during the years 1286 to 1402, 999 earthquakes with a magnitude of more than 3 on the Richter scale occurred within a radius of 100 km from these metropolises, 15 of which had a magnitude of more than 6 on the Richter scale. Is. The results of the analysis of earthquakes have shown that the largest number of earthquakes occurred in the metropolitan areas of Shiraz, Ahvaz and Kermanshah, so that 390, 186 and 147 earthquakes occurred in these metropolitan areas, respectively. The lowest number of earthquakes with 19 and 20 cases respectively was related to the metropolitan areas of Isfahan and Qom. Also, the largest number of earthquakes with a magnitude greater than 6 on the Richter scale was related to the metropolitan areas of Shiraz and Kermanshah. The results of this section have shown that the seismic status of Iran's metropolises has been very different, and considering that in addition to the number of earthquakes, various human parameters are also effective in the degree of vulnerability to earthquakes, in this research Based on different parameters, the state of vulnerability of metropolises was evaluated. Based on the results, Shiraz metropolis with a total score of 17.68 is considered the most vulnerable metropolis in the country against earthquake risk. After this metropolis, Kermanshah and Tehran metropolises have the highest vulnerability potential with 13.12 and 10.87 points, respectively. Also, Isfahan metropolis with a total of 2.75 points has the lowest vulnerability potential among the metropolises of the country, and after that, Ahvaz and Qom metropolises have the lowest with 5.72 and 6.66 points, respectively. They are potential vulnerabilities.

Street is a primary component of the establishment of cities. Given the continuity of its functional dimensions over time, it constitutes a key element in the appearance of the spatial organization and subsequently, of the urban landscape. The functional role of the street has been merged with its other roles, to be precise: the social, cultural, economic, or political; fact which caused the complexity of its existential dimensions. Thus, this role constantly oscillates on a spectrum between the function (access, passage) and the user’s experience in the urban space. The present paper is an essay on reading the street landscape to state its role in explaining the meaning of the city, by going through a historical trajectory around the cities of Iran from Antiquity until the end of the Safavid reign. The question of this research is How did the street, as a multidimensional element, influence the formation of the material and semantic aspects of Iranian cities before and after the emergence of Islam? The hypothesis of this research is The street landscape in Iranian cities has always had a ritual character and its role has been to conduct the nature of the urban landscape from a sacred fact toward a social one during the historical evolutions in Iran.

Defining effective mechanisms, this research seeks to design a model for establishing integrated regional governance in Iran, realizing "convergent interaction" with a flexible structure with macro and micro players, resource mobilization for redistribution, development, and improvement of resource allocation in an integrated manner. The main research question addressed in this research is: "What mechanisms can be formulated for the establishment of integrated regional governance in Iran? "This research was conducted using the grounded theory method. The statistical population included experts and managers of macro-level and micro-level ministries selected through the snowball sampling technique. Based on the theoretical summary and the results of the opinion of the expert panel, to design a model for the establishment of integrated regional governance in Iran, it is necessary to define mechanisms. First, the conditions that led to this were formulated with propositions such as decentralization in the planning system and political-administrative decentralization which directly affect the main category of "spatial management." The next layer involves the governing platform  with the definition of institutional-legal, economic, and environmental mechanisms. The next level is the intervening conditions by defining the mechanisms of reforming the educational system and reforming the culture. Finally, all these levels related to the actions and interactions by defining the mechanisms of reforming the management structure with an integration approach, can create structures to realize the model of the establishment of integrated governance in Iran. Therefore, integrated regional governance in Iran will be made by multi-level governance systems with complex configurations of connecting structures and mechanisms at different levels.

The research mostly aims to investigate the correlation analysis of the Indian Ocean Dipole (IOD) index   and drought and wet years in Iran on a monthly basis. To this aim, a correlation analysis was performed between the Standardized Precipitation Index (SPI) of 63 synoptic stations in Iran and the Indian Ocean Dipole (IOD) index values using the Pearson product-moment correlation coefficient and Spearman's rank correlation coefficient. The findings suggested that in autumn, a moderate positive correlation was noted between the Indian Ocean Dipole (IOD) Index and    drought and wet years in Iran in a one-month lag. In other words, droughts of the autumn season in Iran occurred in the negative phase while wet years in the positive phase of this index. In the winter, however, no significant correlation was noted between the drought and wet years in Iran and the Indian Ocean Dipole (IOD) index. It was also noted in springs that there was a negative correlation between drought and wet years in Iran, especially in its southern parts and the Indian Ocean Dipole (IOD) index. In other words, the droughts in this season in Iran occurred in the positive phase while the wet years in the negative phase, i.e., exactly the opposite of the relationship seen in the autumn.

One of the important climatic events that has a great impact on the life of living organisms is extreme temperature events. Cold days and cold waves are examples of extreme temperature events in which unusual minimum temperature values are observed. The creation of these temperature conditions is a function of complex synoptic and dynamic patterns, the identification of which can be useful in increasing awareness of how these conditions are formed and predicting similar situations and thus reducing possible damages. In this research, based on the concept of relative coldness in time and place, cold wave was defined as a condition in which the minimum temperature standard score is less than -1.2; continue for at least 3 days and cover more than 20% of the country's area. In order to meet the objectives of the present research, two environmental (minimum temperature) and atmospheric databases (sea level pressure, geopotential height, atmospheric temperature and orbital and meridional wind component) were used for the winters of 1339 to 1394. The results of examining the patterns showed that all the cold waves in the country were caused by the formation of a high-pressure pattern on the surface of the earth. The arrangement of the two high-pressure systems of Siberia and Azores have played a very important role in guiding the cold air of northern latitudes towards the country. The location of sub-arctic low pressure in the northern regions of Europe and Russia has also caused the cold polar air to move to more southern latitudes. Mid-atmosphere patterns have also had a significant impact on the creation and continuation of cold waves. In such a way that the most severe, widespread and continuous winter cold waves were formed when the barrier systems were established in Eastern Europe and their eastern flank was placed over Iran.

It is essential to disclose or evaluate the impacts of global warming and climate change on temperature in order to account for the climate variations in each given area, such as Iran. This research aimed to assess the effectiveness of the MPI-ESM-LR model, a part of the CMIP5 model series, in evaluating the seasonal anomaly of Iran's temperature. It addressed the lack of comprehensive studies on modeling and forecasting the effects of global warming on temperature events in Iran. This study focused on different Representative Concentration Pathways (RCPs) to provide a comprehensive analysis. It examined two time periods, including the historical eras (1980–2005) and the future (2021–2100). The analysis was done based on the CORDEX-WAS dynamical downscaling approach at the station size. The present study aimed to provide solutions to the following two questions: Is the described model, which utilizes the CORDEX dynamical downscaling approach, capable of accurately forecasting seasonal temperature fluctuations in Iran with little error? Will there be a rise in air temperature conditions on a seasonal scale in the future?

Eight models, namely CanESM2, CSIRO-Mk3-6-0, GFDL-ESM2M, ICHEC-EC-EARTH, IPSL-CM5A-MR, MIROC-ESM, MPI-ESM-LR, and NorESM1-M, were examined to determine the optimum model for forecasting Iran's seasonal temperature. The verification findings of the preceding models indicate that the MPI-ESM-LR model exhibits the least bias, making it the most accurate model for forecasting Iran's seasonal temperature in future periods. To verify the accuracy of the air temperature data obtained from the MPI-ESM-LR model, a total of 49 synoptic stations were chosen across the country. This selection was made based on the historical data provided by the CORDEX project, covering the statistical period from 1980 to 2005. This study examined the effectiveness of the MPI-ESM-LR model, a collection of CMIP5 models, in assessing seasonal air temperature in Iran. It focused on three scenarios: RCP 2.6 (optimistic), RCP 4.5 (moderate), and RCP 8.5 (pessimistic). The research analyzed the seasonal temperature anomaly in Iran for three time periods: the near future (2021-2050), the middle future (2051-2075), and the distant future (2076-2100). The time frame spanning from 1980 to 2005 was designated as the historical period for comparing the data collected from synoptic stations with the simulations generated by CMIP5 models. The validity of observational and modeled data from 1980 to 2005 has been assessed using statistical measures such as the mean bias error (MBE), root mean square error (RMSE), and Pearson correlation coefficient (r). The non-parametric sense approach was employed to calculate the slope of the data trend in the time series. The present study utilized CORDEX-WAS dataset with a spatial resolution of 0.44 arc degrees. The dynamical downscaling was performed using the RCA4 model for regional climate modeling (RCM) and the r1i1p1 ensemble.

The findings indicated that the MPI-ESM-LR model, when implemented with the CORDEX dynamical downscaling approach, demonstrates a high level of accuracy in forecasting seasonal temperature extremes in Iran. This is evident from its average correlation coefficient of 0.99, average RMSE index of 0.55° c, and MBE of -0.3° c. The majority of stations have mean square error values that are below 1 ° c. The greatest bias was found in Bandar Lengeh, with a deviation of 1.6° c, while the smallest bias was found in Sanandaj, with a deviation of 0.06° c. The average error deviation index reveals that Khorram Abad had the highest positive skewness, measuring 0.81° c, whereas Dushan Tappeh displayed the highest negative skewness, measuring -1.8°c. Throughout the year, the lowest rise in air temperature under the 2.6 RCP scenario in the distant future is 7.1°, 21.5°, 25.7°, and 10.8° c. The highest temperature increase in the pessimistic scenario is 8.5 RCP in the distant future. The expected temperatures for winter, spring, summer, and autumn are 10.5°, 25.7°, 30.3°, and 14.9° c, respectively. During the historical period, the mean air temperature in winter, spring, summer, and autumn was 6.3°, 20.3°, 24.8°, and 9.9° c, respectively. In RCP 2.6, the spring, summer, and autumn seasons exhibit a declining trend in temperature. Specifically, the temperature decreases by -0.037°, -0.075°, and -0.037 ° c every decade, respectively. However, in other times and scenarios, the model and station data from the historical period consistently demonstrate a rising temperature trend throughout all seasons. During the winter season, the highest deviation from the average temperature occurs in the Zagros, Sablan, and Sahand Mountains in the western and northwestern regions of the country. Conversely, the lowest deviation from the average temperature is observed in the low-altitude parts of the desert plain and the eastern slopes of Shirkouh. During the spring season, the northwest and Zagros mountains have the most deviation from the average maximum temperature, while the coastal parts of the Caspian and the eastern part of the country see the lowest deviation from the average minimum temperature. During the summer season, the northwest and western regions of the country have had the highest temperature anomalies in most times and scenarios. Conversely, the southeast regions of Jask and Chabahar have shown the lowest temperature anomalies. During the autumn season, the eastern half of the country, particularly the southeastern region and the Lut plain, experience the most deviation in temperature. The lowest temperature anomaly occurs mostly in the elevated regions of Talesh and Sabalan and sometimes on the western slopes of the Zagros Mountains.

Regarding the projected increase in air temperature in the upcoming decades and the concern of water stress, it is recommended to carefully strategize future water management, particularly in arid and semi-arid areas. This planning should take into account population growth as well as the development of industrial and agricultural sectors. Additionally, the impact of climate change on water demand and water resources must be taken into consideration.

Spatial diversity and temporal variability of natural phenomena make their study time-consuming and difficult. On the other hand, there are mutual relationship between the phenomena and aspects and the position of their performance, that have spatial and temporal homogeneity. Based on these criteria, space (time) can be divided into independent units (Kavyani and Alijani, 2001: 344). therefore, classification is the systematic grouping of phenomena or events that have common characteristics or relationships within groups (Heydari, 1999: 8). Climatic phenomena are one of the important and most variety things in the nature of the world. There is no environmental-climatic phenomenon that is not caused by a specific pattern of air pressure distribution (Alijani, 2006: 201). Air pressure is an element that can be used to determine the characteristics of climatic elements, including temperature, precipitation, etc... Therefore, pressure systems are the main and independent factors that control characteristics of humidity, temperature and pressure with their temporal and spatial changes. Most of these pressure systems have a medium or synoptic scale (Boucher, 2006: 5). Therefore, in this study, sea level pressure was chosen as the climate index. Heavy rainfalls are one of the climate phenomena that can have many effects on the environment. This kind of rainfalls are most important natural reason of floods that cause irreparable damage to the natural environment and human societies. Therefore, the study of heavy rainfalls, especially in pervasive areas, is essential to understand the behavior of this type of rains. Identifying the behavior of this type of precipitation is an important step in water resources management. According to the amount of available data and for the ease of knowing the behavior of heavy rainfalls, we will need to use classification. Because despite the variety of patterns leading to heavy rainfall, there are similarities in these patterns.

In this research, heavy and pervasive rainfall in Iran has been studied by using the third version of Esfazari database. For this purpose, the values of the 90th, 95th and 99th percentiles of precipitation on rainy days were calculated for all cells of the map. This means that for each cell a specific threshold was obtained. Then, data above the 90th, 95th, and 99th percentiles were identified respectively as heavy, very heavy, and extremely heavy rain days. To determine the threshold for the definition of " pervasive rainfall " in this research, at first, anomaly of heavy rainfall area was calculated, and then the days with a positive anomaly was selected. Then the 75th percentile of the area of the selected days were obtained. The 75th percentile value obtained for the mentioned days is equal to 16% of the country's area and it was determined as the threshold of pervasive area. Result shows that 160 days with pervasive heavy rainfall (with precipitation equal or more than 90th percentile) occurred during the study period. Rainfall data of 160 days classified by using Binary cluster analysis. For this purpose, the Euclidean distance method and "Ward" linkage method were used. After identifying the number of heavy rainfall patterns, Indicator Days for each pattern identified by using correlation method (Lund) and the average area method. After identifying the Indicator days by both methods, by using sea level maps and the upper atmosphere levels and checking moisture convergence flux maps, Omega and statistical methods, the Indicator days obtained through both methods are compared.

As mentioned above, 160 days with pervasive heavy rainfall were identified and then classified by using binary cluster analysis method. Result show that the 160 studied days are placed in 10 groups (patterns). After determining the number of patterns, the indicator days for each pattern were identified by using correlation method and the average area method. Then, the indicator (obtained from both methods) days were compared by using sea level pressure maps and upper atmosphere levels and checking moisture convergence flux maps, Omega and statistical methods. Result show that average area method can choose indicator days better than correlation method. In the other hand indicator days chosen by correlation method most of the patterns are attributed to the Red sea low pressure and the role of other factors is small or ignored. For example, in this method, the role of the Indian Ocean in providing moisture for the heavy rains in the east and southeast of the country has been very small. But on the indicator days selected by the area average method, the pressure centers are arranged in such a way that a relative balance has been established in the role of factors that cause heavy rainfall.

The results of this research show that 160 days with heavy rainfall (with precipitation equal or more than 90th percentile) and in the area of more than 16% of the country (pervasive) occurred during the study period. The classification shows that 8 synoptic patterns cause heavy rainfalls. Also, Result show that average area method can choose indicator days better than correlation method.

Flood is one of the most destructive natural disasters with social, economic and environmental consequences. Therefore, comprehensive flood management is necessary to reduce the effects of floods on human life and livelihood. The main goal of this study is to investigate the application of the maximum entropy model (Entropy Maxent) in R software for flood susceptibility mapping in Fars province (Jahrom urban basin). First, by using the information of natural resources of Fars province and field visits, flood-prone points (50 points) were determined. In the next step, environmental variables such as altitude, slope, and distance from the river, drainage density, average annual rainfall, land use, soil type, and geology were selected by performing the multiple collinearity test, and vegetation cover and topographic humidity index were removed. Among the selected environmental variables, the three factors of height distance from the waterway and land use have had the greatest impact in the modeling process. After that, the receiver operating characteristic curve (ROC) was drawn for the flood sensitivity map, and the value of training data (0.943) and test data (0.932) was obtained. In the following, the model was optimized and upgraded using the genetic algorithm. As a result, this flood susceptibility map can be useful for researchers and planners in flood mitigation strategies.

Nourabad of Fars, like other geographical spaces, has been affected by geopolitical trends. This trend has affected it both on a neighboring and extraterritorial scale. In the meantime, the active actor of Iran could have greatly influenced this trend and emerged as a global player at least up to the border of the Arab countries of the Persian Gulf, and at most, as a global player. In general, these trends have affected the country of Iran and also on an internal scale, Nourabad of Fars, and suddenly, its elite human resources realized that they were not fluent in the first language of the world and were isolated and far from the global network. Along with the effective geopolitical trends, climate change and drought made this human (Iranian and Nourabad of Fars) vulnerable and made the conditions difficult and challenging for them. Geopolitical trends are those forces that are created by actors and affect national and intra-national spaces. Sometimes geopolitical trends cause development, in which case countries are guided by measured governance in the direction of the trends and are absorbed in them, but most often they cause underdevelopment because governance is against the trends or is in conflict with them. Therefore, it can be said that in parallel with inward-oriented statecraft, geopolitical trends have caused Iran's territorial isolation and backwardness from the communication network and integrated geographical scope.

In Iran, various fire spread models have been used to predict fire behavior and spread at regional and local scales (Alhaj Khalaf, Shataee Joibary, Jahdi & Bacciu, 2021; Jahdi, Salis, Alcasena & Del Giudice, 2023). However, the calculation of an integrated fire risk index using these fire spread models has not yet been conducted. Typically, fire risk assessments are based on a set of fire spread descriptors that are used to map fire-prone areas and identify the most appropriate fire and fuel management measures in line with predefined goals (e.g., reducing fire intensity or minimizing fire size).Fire and fuel management involves a comprehensive approach that integrates land management practices, considering fire regimes, impacts, values at risk, and multiple resource use activities. Despite the merits of each approach, limited resources often prevent the implementation of management measures in all areas with significant fire risk. Therefore, it is essential to prioritize high-risk areas and identify appropriate management strategies that maximize ecosystem protection. This study aims to develop an integrated method for identifying areas with the highest fire risk in the forests and rangelands of Guilan Province. The method combines simulation models of fire spread with landscape data (topography and fuel), fire weather conditions, and historical ignition point data. Additionally, anthropogenic factors, such as proximity to roads and settlements, are included in the fire risk modeling process, given their significant influence on fire behavior and regimes (Twidwell et al., 2016). The results of this research can support land-use planning, management, and future studies on fire hazards.

Study Area: This research was conducted in Guilan Province, which spans 1,404,400 hectares in northern Iran. The area ranges from -74 meters in the north to approximately 3,700 meters in the southeast. The province receives an average of 1,100 mm of annual rainfall, and the relative humidity averages 80%, decreasing during the summer months with 185 mm of rainfall during this period.

Three Landsat-8 OLI/TIRS L1TP images from October 2021 were used to identify the main land cover types and produce a land cover map of the study area using ENVI 5.6 software. A map of surface fuel models was created by assigning local fuel models (Jahdi et al., 2020, 2023) and standard fuel models (Scott & Burgan, 2005) to the land cover types. Additionally, a vegetation density map and forest canopy density map (in percentage) for 2021 were generated from Landsat-8 images using the FCD model in ENVI software.Historical fire ignition data were used to calculate ignition probability by interpolating ignition points using the Inverse Distance Weighting (IDW) algorithm with a fixed radius of 5 km.The frequency of fire recurrence was determined from historical fire perimeters. Weather data, including temperature, relative humidity, wind speed, and wind direction, were collected for the fire season in the study area.To prepare input data for fire risk modeling:FlamMap 6 fire simulator (Finney, 2006) was used to model fire behavior, including fireline intensity and fire rate of spread, at a 100-meter resolution across the study area.Raster maps showing Euclidean distance from roads and settlements were created using ArcMap 10.8 software.Kernel density estimation was applied to convert the historical ignition point map into a fire density raster map.The fireline intensity, fire rate of spread, human factor maps, and fire history maps were rescaled to values between 0 and 1. These layers were combined to calculate the fire risk index (Xofis, Konstantinidis, Papadopoulos & Tsiourlis, 2020). The fire risk index values ranged from 0 (low risk) to 1 (highest risk).

Fifteen land cover classes were identified in the study area (Fig. 2, Table 4). The overall accuracy of the classification was 91%, with a Kappa statistic of 0.88. Dense broadleaf forest (30.6%) and orchard-irrigation farming (26%) were the dominant land cover types. Approximately 65% of the study area comprised natural forests, plantations, woodlands, shrublands, and rangelands. The remaining area included agricultural lands, built-up areas, water bodies, and bare lands.Based on the simulation outputs for fireline intensity and fire rate of spread (Fig. 4):In over 93% of the study area, the fire rate of spread did not exceed 0.25, and less than 7% of the area had higher values.Similarly, in over 90% of the area, the fireline intensity remained below 0.25, with about 10% exceeding this threshold.The highest values for fireline intensity and fire rate of spread were observed at high altitudes with dense vegetation, consistent with findings by Okano & Yamano (2015), which showed topography and slope significantly influenced fire behavior in broadleaf forests.Human factors, such as proximity to roads and the fire kernel density/fire history (Fig. 5), were found to impact a smaller proportion of the study area. This finding aligns with the study by Xofis et al. (2020).The integration of these components (Fig. 4 and Fig. 5) produced the final fire risk index map (Fig. 6). Fire risk values ranged from 0.0 to 0.68, with an average value of 0.11. Lowlands covered by non-burnable fuel models had the lowest risk (0.0), while the highest fire risk values were observed in the highlands with dense forest cover.

This study demonstrates how landscape information (topography and fuel), weather conditions, and historical fire data, combined with human factors, can be used to estimate fire risk spatially using fire behavior modeling. Moderate and high-risk areas account for 21% of Guilan Province, where fire management efforts should be prioritized. Specific measures include:Strengthening fire prevention infrastructure.Conducting fire prevention training to raise public awareness.Enhancing ecosystem resilience in vulnerable areas.While many fires remain random and difficult to fully control, estimating fire risk and developing prediction models can help mitigate fire hazards, reduce potential damages, and improve the allocation of fire prevention resources.

The purpose of this research is to analyze the beginning, end and length of the snow season in Iran. For this purpose, daily data from the MODIS, spanning from 20/03/2000 to 19/03/2020, was obtained from the NASA website at a spatial resolution of 500 meters. First, temporal and spatial filters were applied to eliminate the impact of cloudiness on the data. Furthermore, the first day when a cell was reported to have snow cover (based on the elapsed days since the start of Mehr) was determined for every water year. This process was conducted separately for each water year, ultimately yielding a matrix of dimensions 20 × 7541502, where each row represented the first day that the MODIS detected snow on a given cell, and each column represented a spatial cell. Similarly, the same procedure was employed to calculate the end and length of snow season. The findings indicate that, in general, the beginning of snow season is shifting towards the winter season in the western parts of the country. Conversely, in the northwestern regions, including the northern slopes of Alborz and certain areas of the southern Zagros, the beginning of snow season is transitioning towards the autumn season. Moreover, in many highland areas in the west and northwest, as well as on the Alborz mountain range, the end of the snow season is progressively occurring towards late winter and spring.

Despite the many restrictions on Iran's oil exports due to the post-IPO sanctions, oil is still considered an important source of income for the country. Considering the strategic importance of oil in the country's financial policy portfolio, the present research has investigated Iran's petroleum geo-economics and the impact of post-JCPOA sanctions on it. The research method is descriptive-analytical, and by using first-hand sources and reliable statistics, the impact of sanctions on Iran's oil industry has been explained. The findings of the research showed that from a geopolitical point of view, Iran's acting power in the joint oil fields as well as the energy market has declined; In such a way that countries like Saudi Arabia and Russia (despite the sanctions after the attack on Ukraine), exert the hegemonic role in the oil markets. From the geo-economic point of view, the decrease in Iran's oil exports has had a direct relationship with the decrease in domestic production. In a way that has reduced the acting and deterrence power of the country in different scales. After the imposition of severe sanctions against Iran when the United States unilaterally withdrew from the JCPOA in 2018, dependence on oil has intensified, and subsequently the state of domestic production shows a significant drop.

The border position of a state can play an influential role in shaping its foreign relations. Access to waterways, commercial areas, and transportation routes are among the things that affect the geographical importance of a region in terms of borders and politics, and this issue is more important in sensitive international situations such as wars in which the countries involved each seek their own influence and interests. Iran enjoyed such a position during World War I and was the focus of the Allied (England-Russia) and Allied (Ottoman-Germany) governments. The study of Iran's border position in the Persian Gulf and its role in Germany's approach to this country during World War I is the subject of this research. The research method is descriptive-analytical. The achievements of this research show that Iran's land and water borders through the Persian Gulf, Arvand River, and proximity to Kuwait and Iraq due to the Berlin-Baghdad railway were among the reasons for Germany's economic and political interest in Iran. Also, proximity to Afghanistan is another reason for Germany's political presence in Iran during World War I.

The investigation and evaluation of development plans is a common scientific method through which one can understand the aims, approaches, and underlying concepts of these plans. Considering the significant role of such plans in the growth and development processes of countries, particularly in promoting the sustainability and prosperity of nomadic communities, this study aims to investigate the regulations and laws governing these plans concerning the empowerment of Iran's nomadic community from the period of the Islamic Revolution to the present. The method employed in this paper is based on documentary approaches that examine government policies in development plans related to the empowerment of nomadic communities. This investigation utilizes two planning approaches: technology-based rational planning and a communicative and participatory approach. The results indicate a lack of coordination between policy and implementation, a predominance of up-down and non-participatory approaches in the development plans, and the inefficiency of empowerment methods as the primary findings of this paper. The study recommends a reevaluation of government policies outlined in the nomadic development plans. This should involve the selection of more suitable social and economic policies, the adoption of effective empowerment methods, and the enforcement of existing laws within these plans.

 The Intergovernmental Panel on Climate Change (IPCC) has reported that climate change results in anomalies, fluctuations or trends in climatic elements, such as precipitation and temperature. In this study, we aim to investigate the decadal changes in the probability of different durations of precipitation in Iran over the past four decades (1977-2016). To achieve this goal, we used the third version of the Asfazari database. We defined a rainy day as a day when the precipitation is more than the average precipitation in a given place. The Markov chain method was employed to estimate the probability of precipitation duration from 1971 through 2016.

We adopted the daily data of 2188 stations under the supervision of Iran’s Meteorological Organization for the period 1971 through 2016. Accordingly, we estimated the probability of precipitation duration for 1-7 days for the entire period. We investigated the decadal changes in the probability of precipitation duration for the four study decades and compared them to the whole period under investigation. To understand the spatial features of these changes, we estimated the relationship between changes in the probability of precipitation duration for 1-7 days and spatial factors using multivariate regression models.

Our findings revealed that as the duration of rainy days increased, the area affected by precipitation decreased. Therefore, the spatial distribution of the probability of precipitation duration for more than 7 days indicated the smallest area that received precipitation. The probability duration of precipitation lasting 4 days or more throughout Iran was very small, which can be attributed to the effects of local features on precipitation formation. The probability of 1-day precipitation for most regions of Iran was higher than other durations; however, there was only a probability of 1-day precipitation in half of Iran. The highest probability of precipitation duration occurred in the Caspian region, the only region that experienced all durations of precipitation, indicating the presence of various precipitation mechanisms in this area. The greatest probability of decadal changes was observed in the 1-7 day duration in the northern part of Iran, including the northwest to the east of the Caspian Sea and in the south of Alborz Mountain range. Additionally, the most changes in the probability durations of 1-7 days of precipitation in the south have been seen in Sistan and Baluchistan. The lowest probability of decadal changes was shown in large areas of the regions from the east, southeast, and southwest. Therefore, the changes in precipitation durations in the southern half of the regions were generally low; however, in the northern half, the changes were relatively significant.In general, during the four study decades, the relationship between changes in the probability of 1-7 day precipitation durations and spatial factors, particularly latitude, was positive. Thus, decreasing latitudes resulted in an increasing probability of 1-7 day precipitation.

The most likely changes in precipitation duration were related to the western and eastern coast of the Caspian Sea and the northwestern region of Iran, as well as southern Alborz, where the probability of changes decreased. The least amount of possible changes was related to the south of Iran, where only two provinces, Sistan and Baluchistan, and Hormozgan, experienced the greatest change in the probability of one to seven days of precipitation. Thus, the possible changes in the spatial continuation of precipitation in the southern half of the country were primarily low. However, in the northern half, the possible changes in the duration of precipitation were more significant. changes in the duration of precipitation, along with changes in the intensity and frequency of precipitation, can have significant consequences in extreme events such as droughts and floods. Accurately depicting changes in precipitation duration can be helpful in addressing problems concerning precipitation.