University of Isfahan Geography and Environmental Planning 2008-5362 35 1 2024 03 20 Analyzing the Climatic Conditions of Tourism in West Azerbaijan Province Using Bioclimatic Indicators Analyzing the Climatic Conditions of Tourism in West Azerbaijan Province Using Bioclimatic Indicators 1 18 28002 10.22108/gep.2023.136135.1563 FA Ehsan Soureh M.A., Department of Climatology, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran 0000-0001-8475-5379 Bakhtiyar Mohammadi Associate Professor, Department of Climatology, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran Journal Article 2022 12 21 Abstract This study aimed to assess the tourism climate in West Azerbaijan Province. The data on key climatic parameters were obtained from the Meteorological Department of West Azerbaijan Province, spanning from establishment of the stations to 2021. Daily statistics for air temperature (in Celsius), relative humidity (as a percentage), wind speed (in meters per second), and cloudiness (measured in octals) were collected for each station. Additionally, total solar radiation, water vapor pressure, and solar radiation angle were calculated, while longitude, latitude, and sea level altitude were factored into the estimation of indicators. Subsequently, UTCI and PMV indices were computed using Rayman, Bioklima, and Excel software. Monthly maps were generated using the IDW interpolation method in ArcGIS Pro software. The findings revealed that the bioclimatic conditions in the province were very cold, cold, and cool in the first quarter of the year. As spring arrived, comfortable thermal conditions prevailed in most cities and persisted until late. While thermal comfort was observed during the summer months, the prevailing conditions in the province became hot and very hot. At the onset of autumn, a wave of comfortable conditions covered the entire province and continued until November, giving way to cool, cold, and very cold conditions as the year drew to a close. According to the PMV index, the months of April, May, and October, and based on the UTCI index, the months of April, May, and June exhibited the highest climate comfort. Keywords: Climatic Comfort, Tourism, Predicted Mean Vote, Subjective Temperature Index, Universal Thermal Climate Index, West Azerbaijan Province. Introduction The impact of climate on various human activities is readily apparent. Tourism as a prominent example is heavily influenced by climatic conditions. The success of many renowned tourist destinations worldwide can be attributed to favorable weather and thermal comfort. Conversely, unfavorable weather diminishes the appeal and allure of a tourist area, exerting detrimental effects on tourism. Consequently, weather stands out as one of the most pivotal factors in tourism. Indeed, possessing favorable climatic conditions is considered a potential advantage for tourism with many tourists and travelers selecting their destinations and timing based on weather considerations (Gomez, 2005). In recent decades, tourism has emerged as a cornerstone of economic activity with countries continually fostering its development and recognizing its substantial role in national economic growth (Scott et al., 2011). Materials and Methods In this study, bio-climatic indicators, namely PMV and UTCI, were employed to assess bio-climatic conditions relevant to tourism. Climatic data from 16 stations across West Azerbaijan Province were utilized for this purpose. A data repository was established and specific processing for each index was conducted using Rayman, Bioklima, and Excel software. Monthly maps were generated using the IDW interpolation method in ArcGIS software. The time periods for weather station data used in calculating bio-climatic indicators are detailed in Table 1. Given the unequal time periods for the data from different cities, the frequency of occurrence of bio-climatic conditions was calculated to facilitate comparison and analysis. Research Findings In April, the northeastern and southern parts of the province exhibited comfortable conditions, while the western and central cities experienced slightly cool conditions with only Chaldoran being cool. Moving into May, the majority of the province experienced slightly warm conditions with the cities of Selmas, Sardasht, and Takab enjoying comfortable conditions. Additionally, hot conditions were observed in some parts of Peldasht and Khoi cities with only a small part of Chaldoran City experiencing slightly cool conditions. By June, most parts of the province were characterized by hot conditions with cities, such as Chaldoran, parts of Selmas, and Takab, experiencing slightly hot conditions. A comfortable situation was observed in a very small part of Chaldoran City during this month, while a part of Peldasht and Khoi cities were in a very hot state (see Figure 4). In July, the majority of the southern and northern parts of the province experienced very hot conditions, with cities, such as Mako, the central part of Chaldoran, Selmas, the southern part of Sardasht, and Takab, also being in a very hot state. The central part of Chaldoran City exhibitd slightly warm conditions, while a small part of Peldasht City experienced hot conditions. Moving into August, most of the southern and northeastern counties of the province were in a very hot condition with Mako, part of Chaldoran, Selmas, Urmia, Sardasht, and Takab counties having hot conditions. Only Chaldaran County had slightly warm conditions. September saw the northeast and south of the province in a warm state with parts of Mako, Chaldoran, Selmas, northern parts of Urmia, Ashnoye, Sardasht, and Takab experiencing slightly warm conditions. The central part of Chaldoran was in a comfortable state and a small part of North Peldasht also had very hot conditions (see Figure 5). In November, slightly cool conditions prevailed in most parts of the province with cities, such as Chaldoran, Selmas, and a part of Sardasht experiencing cool conditions. Parts of the cities of Poldasht and Khoi were covered by comfortable conditions. October saw most of the cities of the province in a comfortable state with parts of Poldasht, Khoi, Miandoab, Mahabad, and Piranshahr experiencing slightly warm conditions and only Chaldoran having slightly cool conditions. Finally, in December, most parts of the province were in cool conditions with the cities of Chaldoran, Selmas, and parts of Bukan and Chaypare experiencing cold conditions (see Figure 6). In January, based on the UTCI index, most of the cities in the province experienced moderately cold conditions with small parts of Poldasht, Khoi, Urmia, Miandoab, and Naqdeh being in slightly cold conditions. The results of the UTCI index indicated that most parts of Chaldoran, Selmas, and Sardasht cities, as well as a part of Ashnoye City, were in a moderately cold state, while other parts of the province were in a partially cold state. Moving into March, according to the UTCI index, all the cities were in a slightly cold state with only a small part of Chaldoran City experiencing moderately cold conditions (see Figure 7). In April, most southern and northeastern cities exhibited comfortable conditions with cities, such as Chaldoran, Selmas, Ashnoye, Sardasht, and Takab being in a slightly cold state. A small part of Chaldoran City experienced average cold conditions. May saw comfortable climatic conditions prevailing in all parts of the province, except for a part of Chaldoran City, which was in a slightly cold state. By June, all the cities of the province enjoyed comfortable conditions with only the northern part of Peldasht City experiencing moderately hot conditions (see Figure 8). In July, the southern and northeastern parts of the province experienced moderately warm conditions, while the northern, western, and central parts, along with the cities of Sardasht and Takab, enjoyed comfortable conditions. Moving into August, the cities in the south and northeast of the province had moderately warm conditions, while the northern and central parts of the two cities of Takab and Sardasht were in a comfortable state. By September, the entire province experienced comfortable climatic conditions (see Figure 9). In October, all the cities of the province were in comfortable conditions with only a small part of Chaldoran City experiencing slightly cold conditions. November saw the southern and northeastern cities of the province in a comfortable state, while the northern and central parts, along with the cities of Sardasht and Takab, also had slightly cold conditions. Finally, in December, most of the cities in the province had partially cold conditions with parts of Chaldoran and Salmas cities also experiencing moderate cold conditions (see Figure 10). Discussion of Results and Conclusion Based on the calculations derived from the PMV index for April, May, and October, as well as the UTCI index for April, May, and June, these months were identified as exhibiting the most favorable climate comfort conditions in West Azerbaijan Province. The findings of this research hold potential applications in the realms of tourism, medicine, architecture, and sports activities. Future research endeavors can involve the utilization of hourly data and a broader array of indicators, thereby enabling a more comprehensive comparative analysis to enhance result accuracy. It is worth noting that limited research has been conducted on the understanding and estimation of the bioclimatic conditions of West Azerbaijan Province. Overall, the outcomes of this study aligned with the research conducted by Ashari et al. (2016). However, when compared with the findings of Bakhtaki(2011) and Ansari-Kalanji (2011), discrepancies were evident. These disparities could be attributed to the utilization of different time frames for data collection and variations in the indicators employed. It is evident that the use of new and up-to-date data has likely contributed to the alignment of our results with those of Ashari et al. (2016), as climate variables and data are subject to change over time. Abstract This study aimed to assess the tourism climate in West Azerbaijan Province. The data on key climatic parameters were obtained from the Meteorological Department of West Azerbaijan Province, spanning from establishment of the stations to 2021. Daily statistics for air temperature (in Celsius), relative humidity (as a percentage), wind speed (in meters per second), and cloudiness (measured in octals) were collected for each station. Additionally, total solar radiation, water vapor pressure, and solar radiation angle were calculated, while longitude, latitude, and sea level altitude were factored into the estimation of indicators. Subsequently, UTCI and PMV indices were computed using Rayman, Bioklima, and Excel software. Monthly maps were generated using the IDW interpolation method in ArcGIS Pro software. The findings revealed that the bioclimatic conditions in the province were very cold, cold, and cool in the first quarter of the year. As spring arrived, comfortable thermal conditions prevailed in most cities and persisted until late. While thermal comfort was observed during the summer months, the prevailing conditions in the province became hot and very hot. At the onset of autumn, a wave of comfortable conditions covered the entire province and continued until November, giving way to cool, cold, and very cold conditions as the year drew to a close. According to the PMV index, the months of April, May, and October, and based on the UTCI index, the months of April, May, and June exhibited the highest climate comfort. Keywords: Climatic Comfort, Tourism, Predicted Mean Vote, Subjective Temperature Index, Universal Thermal Climate Index, West Azerbaijan Province. Introduction The impact of climate on various human activities is readily apparent. Tourism as a prominent example is heavily influenced by climatic conditions. The success of many renowned tourist destinations worldwide can be attributed to favorable weather and thermal comfort. Conversely, unfavorable weather diminishes the appeal and allure of a tourist area, exerting detrimental effects on tourism. Consequently, weather stands out as one of the most pivotal factors in tourism. Indeed, possessing favorable climatic conditions is considered a potential advantage for tourism with many tourists and travelers selecting their destinations and timing based on weather considerations (Gomez, 2005). In recent decades, tourism has emerged as a cornerstone of economic activity with countries continually fostering its development and recognizing its substantial role in national economic growth (Scott et al., 2011). Materials and Methods In this study, bio-climatic indicators, namely PMV and UTCI, were employed to assess bio-climatic conditions relevant to tourism. Climatic data from 16 stations across West Azerbaijan Province were utilized for this purpose. A data repository was established and specific processing for each index was conducted using Rayman, Bioklima, and Excel software. Monthly maps were generated using the IDW interpolation method in ArcGIS software. The time periods for weather station data used in calculating bio-climatic indicators are detailed in Table 1. Given the unequal time periods for the data from different cities, the frequency of occurrence of bio-climatic conditions was calculated to facilitate comparison and analysis. Research Findings In April, the northeastern and southern parts of the province exhibited comfortable conditions, while the western and central cities experienced slightly cool conditions with only Chaldoran being cool. Moving into May, the majority of the province experienced slightly warm conditions with the cities of Selmas, Sardasht, and Takab enjoying comfortable conditions. Additionally, hot conditions were observed in some parts of Peldasht and Khoi cities with only a small part of Chaldoran City experiencing slightly cool conditions. By June, most parts of the province were characterized by hot conditions with cities, such as Chaldoran, parts of Selmas, and Takab, experiencing slightly hot conditions. A comfortable situation was observed in a very small part of Chaldoran City during this month, while a part of Peldasht and Khoi cities were in a very hot state (see Figure 4). In July, the majority of the southern and northern parts of the province experienced very hot conditions, with cities, such as Mako, the central part of Chaldoran, Selmas, the southern part of Sardasht, and Takab, also being in a very hot state. The central part of Chaldoran City exhibitd slightly warm conditions, while a small part of Peldasht City experienced hot conditions. Moving into August, most of the southern and northeastern counties of the province were in a very hot condition with Mako, part of Chaldoran, Selmas, Urmia, Sardasht, and Takab counties having hot conditions. Only Chaldaran County had slightly warm conditions. September saw the northeast and south of the province in a warm state with parts of Mako, Chaldoran, Selmas, northern parts of Urmia, Ashnoye, Sardasht, and Takab experiencing slightly warm conditions. The central part of Chaldoran was in a comfortable state and a small part of North Peldasht also had very hot conditions (see Figure 5). In November, slightly cool conditions prevailed in most parts of the province with cities, such as Chaldoran, Selmas, and a part of Sardasht experiencing cool conditions. Parts of the cities of Poldasht and Khoi were covered by comfortable conditions. October saw most of the cities of the province in a comfortable state with parts of Poldasht, Khoi, Miandoab, Mahabad, and Piranshahr experiencing slightly warm conditions and only Chaldoran having slightly cool conditions. Finally, in December, most parts of the province were in cool conditions with the cities of Chaldoran, Selmas, and parts of Bukan and Chaypare experiencing cold conditions (see Figure 6). In January, based on the UTCI index, most of the cities in the province experienced moderately cold conditions with small parts of Poldasht, Khoi, Urmia, Miandoab, and Naqdeh being in slightly cold conditions. The results of the UTCI index indicated that most parts of Chaldoran, Selmas, and Sardasht cities, as well as a part of Ashnoye City, were in a moderately cold state, while other parts of the province were in a partially cold state. Moving into March, according to the UTCI index, all the cities were in a slightly cold state with only a small part of Chaldoran City experiencing moderately cold conditions (see Figure 7). In April, most southern and northeastern cities exhibited comfortable conditions with cities, such as Chaldoran, Selmas, Ashnoye, Sardasht, and Takab being in a slightly cold state. A small part of Chaldoran City experienced average cold conditions. May saw comfortable climatic conditions prevailing in all parts of the province, except for a part of Chaldoran City, which was in a slightly cold state. By June, all the cities of the province enjoyed comfortable conditions with only the northern part of Peldasht City experiencing moderately hot conditions (see Figure 8). In July, the southern and northeastern parts of the province experienced moderately warm conditions, while the northern, western, and central parts, along with the cities of Sardasht and Takab, enjoyed comfortable conditions. Moving into August, the cities in the south and northeast of the province had moderately warm conditions, while the northern and central parts of the two cities of Takab and Sardasht were in a comfortable state. By September, the entire province experienced comfortable climatic conditions (see Figure 9). In October, all the cities of the province were in comfortable conditions with only a small part of Chaldoran City experiencing slightly cold conditions. November saw the southern and northeastern cities of the province in a comfortable state, while the northern and central parts, along with the cities of Sardasht and Takab, also had slightly cold conditions. Finally, in December, most of the cities in the province had partially cold conditions with parts of Chaldoran and Salmas cities also experiencing moderate cold conditions (see Figure 10). Discussion of Results and Conclusion Based on the calculations derived from the PMV index for April, May, and October, as well as the UTCI index for April, May, and June, these months were identified as exhibiting the most favorable climate comfort conditions in West Azerbaijan Province. The findings of this research hold potential applications in the realms of tourism, medicine, architecture, and sports activities. Future research endeavors can involve the utilization of hourly data and a broader array of indicators, thereby enabling a more comprehensive comparative analysis to enhance result accuracy. It is worth noting that limited research has been conducted on the understanding and estimation of the bioclimatic conditions of West Azerbaijan Province. Overall, the outcomes of this study aligned with the research conducted by Ashari et al. (2016). However, when compared with the findings of Bakhtaki(2011) and Ansari-Kalanji (2011), discrepancies were evident. These disparities could be attributed to the utilization of different time frames for data collection and variations in the indicators employed. It is evident that the use of new and up-to-date data has likely contributed to the alignment of our results with those of Ashari et al. (2016), as climate variables and data are subject to change over time.

https://gep.ui.ac.ir/article_28002_ae3fe25a9afa0e01e577fc75c96f085c.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 35 1 2024 03 20 Developing Feasibility of Urban Renewable Energy in Ahvaz with a Passive Defense Approach Developing Feasibility of Urban Renewable Energy in Ahvaz with a Passive Defense Approach 19 44 27871 10.22108/gep.2023.137813.1587 FA Mostafa Mohammadi Dehcheshmeh Associate Professor of Geography and Planning, Shahid Chamran University of Ahvaz, Ahvaz, Iran Masoud Safaeepour Professor of Geography and Planning, Shahid Chamran University of Ahvaz, Ahvaz, Iran Nahid Sajjadian Professor of Geography and Planning, Shahid Chamran University of Ahvaz, Ahvaz, Iran Hossein Ebadi Ph.D. Student of Geography and Planning, Shahid Chamran University of Ahvaz, Ahvaz, Iran Journal Article 2023 06 06 Abstract In the 21st century, global efforts to mitigate environmental pollutants have focused on fostering a low-carbon economy and advancing energy sources that minimize greenhouse gas emissions and energy consumption. However, numerous challenges persist. Therefore, this research aimed to investigate and analyze the obstacles to sustainable development in the city of Ahvaz within an environmentally non-operating context. This study was applied in its purpose and survey-oriented while being descriptive-analytical in its methodology. Data were gathered through document analysis, library research, and fieldwork (questionnaires and interviews). The statistical population of the study comprised experts in the field of energy in Ahvaz with a sampling method based on stratification. The analysis employed quantitative methods, utilizing the ARAS and VIKOR techniques. The findings revealed that the challenges in developing geothermal, biomass, water, wind, and solar energy were primarily environmental in nature. The VIKOR technique results indicated that solar energy ranked highest in terms of ineffectiveness in addressing energy challenges in Ahvaz with a score of 1 followed by wind energy at 0.758 and water energy at 0.2220. Geothermal energy and biomass ranked lowest, respectively. Furthermore, the integration results demonstrated a varying degree of interdependence between non-factor indicators and energy development challenges contingent upon the type of renewable energy. Keywords: Energy Development, Passive Defense, ARAS, VIKOR, Ahvaz Introduction Renewable Energy Sources (RES) are gaining global prominence as a viable alternative to fossil fuels with recent research underscoring their pivotal role in the future. Depleting reserves and the adverse environmental impact of fossil fuels have prompted investors to consider RES for sustainable development. Conventional energy sources, such as oil, coal, and gas, are not only dwindling in supply, but also carrying significant environmental repercussions. A diverse array of renewable energy sources, including solar, geothermal, hydroelectric, and wind power, have been posited as more sustainable alternatives to meet both current and future energy demands. Despite their potential to furnish affordable and clean energy, adoption of renewable energy has encountered varying degrees of governmental policy support and market uptake. Materials & Methods This study was classified as an applied research due to its focus on assessing the development of renewable energies and examining non-functional defense indicators. Methodologically, it adopted a survey-based and descriptive-analytical approach. Data were collected through documentary analysis, library research, and fieldwork involving questionnaires and interviews. The statistical population consisted of experts in the field with their number determined through a systematic review of resumes and statistics within the renewable energy and passive defense sectors. A minimum number of 50 individuals was selected based on this criterion. The sampling method employed in this research was proportional stratified sampling, wherein a percentage of the total statistical sample was allocated to each area based on its population. Additionally, to rank the indicators pertinent to renewable energy development, a questionnaire was distributed to other experts in the field. The snowball sampling method was utilized to select 50 relevant experts. The analysis method utilized quantitative models, specifically employing the ARAS decision-making method and the VIKOR model for ranking with the results subsequently integrated. Research Findings: The outcomes derived from the VIKOR technique revealed that the defense indicators least effective in mitigating the challenges of renewable energy in the city of Ahvaz were solar energy with a score of 1, wind energy ranking second with a score of 0.758, and hydro energy securing the third position with a score of 0.2220. A correlation existed between the non-operating defense indicators and the challenges of energy development, influencing the feasibility of developing each type of energy and likelihood of overcoming the existing challenges based on the conditions specific to Ahvaz. This correlation varied depending on the specific type of renewable energy. Furthermore, biomass and geothermal energy ranked lowest, respectively. The overall conclusion of this study suggested that the development of solar energy was more feasible than those of other energy sources. The interplay between the non-operating defense indicators and energy development challenges determined the relative feasibility of developing each type of energy and overcoming the existing challenges with this relationship varying across different types of renewable energy. Discussion of Results & Conclusion The array of challenges present in the development of geothermal, biomass, hydro, wind, and solar energy respectively exerted a significant influence, necessitating careful consideration by relevant managers in their planning efforts as these challenges had to be addressed concurrently, presenting a formidable task. However, the potential for developing renewable energies varied across different energy types. According to the findings of ARAS, geothermal energy development ranked as the lowest priority in terms of feasibility. From a non-agent perspective, prioritizing a comprehensive and interdisciplinary approach that encompasses the broader social and environmental impacts of energy policy and technology is imperative. This approach allows for a better understanding of the opportunities and challenges associated with transitioning to a more sustainable energy system, enabling the identification of effective strategies to achieve this objective. With the burgeoning population and economy, the demand for energy in Ahvaz City was escalating rapidly. The development of renewable energy in Ahvaz was essential to meet the ever-increasing energy demand and mitigate the environmental impacts stemming from the city's industrial nature and heavy reliance on fossil fuels. Nonetheless, numerous challenges existed in the path of renewable energy development in Ahvaz. Abstract In the 21st century, global efforts to mitigate environmental pollutants have focused on fostering a low-carbon economy and advancing energy sources that minimize greenhouse gas emissions and energy consumption. However, numerous challenges persist. Therefore, this research aimed to investigate and analyze the obstacles to sustainable development in the city of Ahvaz within an environmentally non-operating context. This study was applied in its purpose and survey-oriented while being descriptive-analytical in its methodology. Data were gathered through document analysis, library research, and fieldwork (questionnaires and interviews). The statistical population of the study comprised experts in the field of energy in Ahvaz with a sampling method based on stratification. The analysis employed quantitative methods, utilizing the ARAS and VIKOR techniques. The findings revealed that the challenges in developing geothermal, biomass, water, wind, and solar energy were primarily environmental in nature. The VIKOR technique results indicated that solar energy ranked highest in terms of ineffectiveness in addressing energy challenges in Ahvaz with a score of 1 followed by wind energy at 0.758 and water energy at 0.2220. Geothermal energy and biomass ranked lowest, respectively. Furthermore, the integration results demonstrated a varying degree of interdependence between non-factor indicators and energy development challenges contingent upon the type of renewable energy. Keywords: Energy Development, Passive Defense, ARAS, VIKOR, Ahvaz Introduction Renewable Energy Sources (RES) are gaining global prominence as a viable alternative to fossil fuels with recent research underscoring their pivotal role in the future. Depleting reserves and the adverse environmental impact of fossil fuels have prompted investors to consider RES for sustainable development. Conventional energy sources, such as oil, coal, and gas, are not only dwindling in supply, but also carrying significant environmental repercussions. A diverse array of renewable energy sources, including solar, geothermal, hydroelectric, and wind power, have been posited as more sustainable alternatives to meet both current and future energy demands. Despite their potential to furnish affordable and clean energy, adoption of renewable energy has encountered varying degrees of governmental policy support and market uptake. Materials & Methods This study was classified as an applied research due to its focus on assessing the development of renewable energies and examining non-functional defense indicators. Methodologically, it adopted a survey-based and descriptive-analytical approach. Data were collected through documentary analysis, library research, and fieldwork involving questionnaires and interviews. The statistical population consisted of experts in the field with their number determined through a systematic review of resumes and statistics within the renewable energy and passive defense sectors. A minimum number of 50 individuals was selected based on this criterion. The sampling method employed in this research was proportional stratified sampling, wherein a percentage of the total statistical sample was allocated to each area based on its population. Additionally, to rank the indicators pertinent to renewable energy development, a questionnaire was distributed to other experts in the field. The snowball sampling method was utilized to select 50 relevant experts. The analysis method utilized quantitative models, specifically employing the ARAS decision-making method and the VIKOR model for ranking with the results subsequently integrated. Research Findings: The outcomes derived from the VIKOR technique revealed that the defense indicators least effective in mitigating the challenges of renewable energy in the city of Ahvaz were solar energy with a score of 1, wind energy ranking second with a score of 0.758, and hydro energy securing the third position with a score of 0.2220. A correlation existed between the non-operating defense indicators and the challenges of energy development, influencing the feasibility of developing each type of energy and likelihood of overcoming the existing challenges based on the conditions specific to Ahvaz. This correlation varied depending on the specific type of renewable energy. Furthermore, biomass and geothermal energy ranked lowest, respectively. The overall conclusion of this study suggested that the development of solar energy was more feasible than those of other energy sources. The interplay between the non-operating defense indicators and energy development challenges determined the relative feasibility of developing each type of energy and overcoming the existing challenges with this relationship varying across different types of renewable energy. Discussion of Results & Conclusion The array of challenges present in the development of geothermal, biomass, hydro, wind, and solar energy respectively exerted a significant influence, necessitating careful consideration by relevant managers in their planning efforts as these challenges had to be addressed concurrently, presenting a formidable task. However, the potential for developing renewable energies varied across different energy types. According to the findings of ARAS, geothermal energy development ranked as the lowest priority in terms of feasibility. From a non-agent perspective, prioritizing a comprehensive and interdisciplinary approach that encompasses the broader social and environmental impacts of energy policy and technology is imperative. This approach allows for a better understanding of the opportunities and challenges associated with transitioning to a more sustainable energy system, enabling the identification of effective strategies to achieve this objective. With the burgeoning population and economy, the demand for energy in Ahvaz City was escalating rapidly. The development of renewable energy in Ahvaz was essential to meet the ever-increasing energy demand and mitigate the environmental impacts stemming from the city's industrial nature and heavy reliance on fossil fuels. Nonetheless, numerous challenges existed in the path of renewable energy development in Ahvaz.

https://gep.ui.ac.ir/article_27871_851dc2b2ee99aafcd14a6f30a7015dd1.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 35 1 2024 03 20 Arabian Sea’s Moisture Transfer Mechanisms in Pervasive Dry and Wet Periods of Iran Arabian Sea’s Moisture Transfer Mechanisms in Pervasive Dry and Wet Periods of Iran 45 72 27794 10.22108/gep.2023.136560.1571 FA Zahed Deldarzehi MA, Department of Physical Geography, Faculty of Geography and Environmental Planning, University of Sistan and Baluchestan, Zahedan, Iran Peyman Mahmoudi Associate Professor, Department of Physical Geography, Faculty of Geography and Environmental Planning, University of Sistan and Baluchestan, Zahedan, Iran Mahmood Khosravi Professor, Department of Physical Geography, Faculty of Geography and Environmental Planning, University of Sistan and Baluchestan, Zahedan, Iran Journal Article 2023 01 23 Abstract To recognize the Arabian Sea’s moisture transfer mechanisms during the occurrence of pervasive drought and wet years in Iran, a standardized precipitation index (SPI) was applied to quantize Iran’s droughts within the format of a monthly scale. Next, based on a spatial threshold, the drought or the wet years that had engaged about 75% or more of the studied stations (63 synoptic stations) within the period of a cold period (October-April) during 30 years (1986-2016) were defined as the pervasive drought or wet years. In the end, using atmospheric gridded variables, the various mechanisms of the Arabian Sea’s moisture transfer were examined during the occurrence of Iran’s pervasive drought and wet years. The results indicated that during winter, the Asian thermal high pressure reaches its strongest state, its western part is expanded, and, together with the Atlantic Ocean’s dynamic high pressure, they capture the whole of central Asia, the Middle East, and northern Africa. Under these conditions, the high pressure established over the Saudi Arabian Peninsula takes a more western position and this new position disrupts moisture transfer from the Arabian Sea into Iran the result of which would be pervasive dry winters for Iran. Keywords: Geopotential Height, Dynamical High Pressure, Thermal Low Pressure, Saudi Arabian Peninsula, Tibetan Plateau, Monsoon. Introduction Due to the transfer of a large volume of moisture, the Arabian Sea and the Mediterranean Sea are amongst the most important moisture resources of Iran’s precipitations. The Mediterranean Sea, during the early fall and late spring, and the Arabian Sea, as well, as during the other months of the year’s cold periods, are at the top of the most significant moisture resources for supplying Iran with precipitations. The superior role of the Arabian and Mediterranean seas in the supplying of moisture to Iran’s precipitations can stem from factors like their wide vastness and depth in contrast to the other water breadths. Considering the results of the studies during the recent several decades, appropriate knowledge on the identification of the synoptic patterns leading to Iran’s drought and wet years in various temporal and spatial scales is obtained in this regard in Iran’s climatological literature. However, even with such very rich literature, there are still ambiguities regarding the mechanisms of moisture transfer from the adjacent seas, especially the Indian Ocean and Arabian Sea at the time of the occurrence of pervasive drought and wet years. To fill the gap, the present study intends to investigate the synoptic reasons for the translocation of the cyclonic and anti-cyclonic circulation patterns over the Arabian Sea and north of the Indian Ocean at the time of the occurrence of the pervasive drought and wet years in Iran. Materials and Methods To recognize the Arabian Sea’s moisture transfer mechanisms during the occurrence of pervasive drought and wet years in Iran, two different databases were used. The first belongs to the monthly precipitation data recorded in 63 synoptic stations for 30 years (1986-2016) and obtained from Iran’s meteorological organization. The second database, as well, is pertinent to the atmospheric gridded variables recorded in the form of monthly monitoring and acquired from the European Center for Medium-Range Weather Forecast (ECMWF). After collecting the data and forming an information bank, a standardized precipitation index (SPI) was applied to quantize Iran’s droughts within the format of a monthly scale. Next, based on a spatial threshold, the drought or the wet years that had engaged about 75% or more of the studied stations (63 synoptic stations) within a cold period (October-April) during 30 years (1986-2016) were defined as the pervasive drought or wet years. In the end using atmospheric gridded variables, the various mechanisms of the Arabian Sea’s moisture transfer were examined during the occurrence of Iran’s pervasive drought and wet years. Research Findings During fall, the delay in the translocation of southward monsoon low pressure in southern Asia causes its western part to be expanded over the Arabian Sea. This expansion causes dislocation of westward high pressure situated over the Saudi Arabian Peninsula and the moisture transfer from this sea into Iran is resultantly disrupted leading to pervasive droughts in Iran. But, when the South Asian monsoon low pressure is located in a more southern situation, the expansion of its western part is reduced and the high pressure located over the Saudi Arabian peninsula moves to the coasts of the Arabian Sea with a little eastward dislocation. Under such circumstances, the whole Arabian Sea is overwhelmed by this high pressure and its moisture enters Iran through the Saudi Arabian Peninsula’s moisture canal. Nevertheless, Iran’s pervasive drought and wet years during winter are a function of the jigsaw behavior between Asia’s thermal high pressure and the Atlantic Ocean’s dynamic high pressure. When Asia’s thermal high pressure reaches its strongest state, its western part is expanded and, along with the Atlantic Ocean’s dynamical high pressure, spread over the entire Central Asia, the Middle East, and Northern Africa. Under these conditions, the high pressure situated over the Saudi Arabian Peninsula takes a more western position and this new location causes disruption in the moisture transfer from the Arabian Sea into Iran and this ends in pervasive dry winters in Iran. However, during some times when the Asian thermal high pressure is in its weakest state, the western part thereof would not have the spatial expansion it has to. In such a situation, the eastern part of the Atlantic Ocean’s dynamic high pressure is corroborated and expanded. Such an expansion caused the high pressure situated over the Saudi Arabian Peninsula to move eastward and become established over the eastern coasts of the Saudi Arabian Peninsula. This new situation causes the transfer of moisture from the Arabian Sea into Iran to happen easily and the result would be pervasive wet winters for Iran. But, during spring, Tibetan low pressure and the Atlantic Ocean’s high pressure are the most important actors of climate in southwest Asia. Whenever the low pressure of the Tibetan plateau low pressure is strengthened and expanded over the eastern half of the Arabian Sea, the high pressure established over Saudi Arabia would be dislocated westward as a result of which pervasive droughts happen in Iran. However, when the Tibetan Plateau’s low pressure is ameliorated and its western part distances away from the Arabian Sea, the Atlantic Ocean’s dynamic high pressure is corroborated and its eastern part is expanded. This expansion causes the high pressure situated over the Saudi Arabian Peninsula to move eastward with its central core taking place over the western shores of the Arabian Sea under which conditions the whole Arabian Sea would be captured by this high pressure. This high pressure transfers the Arabian Sea’s moisture through the Saudi Arabian Peninsula’s moisture canal into Iran via a clockwise circulation. During the ending months of spring, as well, and with the northward dislocation of the tropical convergence belt and its establishment over southern Asia and also with the establishment of some parts of India’s monsoon low pressure over the eastern half of the Arabian Sea, the moisture transfer from the Arabian Sea into Iran is practically decreased to a minimum. Discussion of Results and Conclusion The results indicated that certain patterns play roles during every season in this sea’s transferring of moisture. During fall, delay in the southward dislocation of southern Asia’s monsoon low pressure causes the transfer of moisture from this sea into Iran to be disrupted the result of which would be pervasive droughts in Iran. During winter when the Asian thermal high pressure reaches its strongest state, its western part is expanded and, together with the Atlantic Ocean’s dynamical high pressure, it captures the whole of central Asia, the Middle East, and northern Africa. Under these conditions, the high pressure established over the Saudi Arabian Peninsula takes a more western position and this new position disrupts moisture transfer from the Arabian Sea into Iran the result of which would be pervasive dry winters for Iran. During spring, the Tibetan low pressure and the Atlantic Ocean’s high pressure are the most important players in the climate in southwest Asia. Whenever the western part of the Tibetan Plateau’s low pressure is strengthened and expanded over the eastern half of the Arabian Sea, the high pressure established over Saudi Arabia is dislocated westward the result of which would be pervasive droughts for Iran. Abstract To recognize the Arabian Sea’s moisture transfer mechanisms during the occurrence of pervasive drought and wet years in Iran, a standardized precipitation index (SPI) was applied to quantize Iran’s droughts within the format of a monthly scale. Next, based on a spatial threshold, the drought or the wet years that had engaged about 75% or more of the studied stations (63 synoptic stations) within the period of a cold period (October-April) during 30 years (1986-2016) were defined as the pervasive drought or wet years. In the end, using atmospheric gridded variables, the various mechanisms of the Arabian Sea’s moisture transfer were examined during the occurrence of Iran’s pervasive drought and wet years. The results indicated that during winter, the Asian thermal high pressure reaches its strongest state, its western part is expanded, and, together with the Atlantic Ocean’s dynamic high pressure, they capture the whole of central Asia, the Middle East, and northern Africa. Under these conditions, the high pressure established over the Saudi Arabian Peninsula takes a more western position and this new position disrupts moisture transfer from the Arabian Sea into Iran the result of which would be pervasive dry winters for Iran. Keywords: Geopotential Height, Dynamical High Pressure, Thermal Low Pressure, Saudi Arabian Peninsula, Tibetan Plateau, Monsoon. Introduction Due to the transfer of a large volume of moisture, the Arabian Sea and the Mediterranean Sea are amongst the most important moisture resources of Iran’s precipitations. The Mediterranean Sea, during the early fall and late spring, and the Arabian Sea, as well, as during the other months of the year’s cold periods, are at the top of the most significant moisture resources for supplying Iran with precipitations. The superior role of the Arabian and Mediterranean seas in the supplying of moisture to Iran’s precipitations can stem from factors like their wide vastness and depth in contrast to the other water breadths. Considering the results of the studies during the recent several decades, appropriate knowledge on the identification of the synoptic patterns leading to Iran’s drought and wet years in various temporal and spatial scales is obtained in this regard in Iran’s climatological literature. However, even with such very rich literature, there are still ambiguities regarding the mechanisms of moisture transfer from the adjacent seas, especially the Indian Ocean and Arabian Sea at the time of the occurrence of pervasive drought and wet years. To fill the gap, the present study intends to investigate the synoptic reasons for the translocation of the cyclonic and anti-cyclonic circulation patterns over the Arabian Sea and north of the Indian Ocean at the time of the occurrence of the pervasive drought and wet years in Iran. Materials and Methods To recognize the Arabian Sea’s moisture transfer mechanisms during the occurrence of pervasive drought and wet years in Iran, two different databases were used. The first belongs to the monthly precipitation data recorded in 63 synoptic stations for 30 years (1986-2016) and obtained from Iran’s meteorological organization. The second database, as well, is pertinent to the atmospheric gridded variables recorded in the form of monthly monitoring and acquired from the European Center for Medium-Range Weather Forecast (ECMWF). After collecting the data and forming an information bank, a standardized precipitation index (SPI) was applied to quantize Iran’s droughts within the format of a monthly scale. Next, based on a spatial threshold, the drought or the wet years that had engaged about 75% or more of the studied stations (63 synoptic stations) within a cold period (October-April) during 30 years (1986-2016) were defined as the pervasive drought or wet years. In the end using atmospheric gridded variables, the various mechanisms of the Arabian Sea’s moisture transfer were examined during the occurrence of Iran’s pervasive drought and wet years. Research Findings During fall, the delay in the translocation of southward monsoon low pressure in southern Asia causes its western part to be expanded over the Arabian Sea. This expansion causes dislocation of westward high pressure situated over the Saudi Arabian Peninsula and the moisture transfer from this sea into Iran is resultantly disrupted leading to pervasive droughts in Iran. But, when the South Asian monsoon low pressure is located in a more southern situation, the expansion of its western part is reduced and the high pressure located over the Saudi Arabian peninsula moves to the coasts of the Arabian Sea with a little eastward dislocation. Under such circumstances, the whole Arabian Sea is overwhelmed by this high pressure and its moisture enters Iran through the Saudi Arabian Peninsula’s moisture canal. Nevertheless, Iran’s pervasive drought and wet years during winter are a function of the jigsaw behavior between Asia’s thermal high pressure and the Atlantic Ocean’s dynamic high pressure. When Asia’s thermal high pressure reaches its strongest state, its western part is expanded and, along with the Atlantic Ocean’s dynamical high pressure, spread over the entire Central Asia, the Middle East, and Northern Africa. Under these conditions, the high pressure situated over the Saudi Arabian Peninsula takes a more western position and this new location causes disruption in the moisture transfer from the Arabian Sea into Iran and this ends in pervasive dry winters in Iran. However, during some times when the Asian thermal high pressure is in its weakest state, the western part thereof would not have the spatial expansion it has to. In such a situation, the eastern part of the Atlantic Ocean’s dynamic high pressure is corroborated and expanded. Such an expansion caused the high pressure situated over the Saudi Arabian Peninsula to move eastward and become established over the eastern coasts of the Saudi Arabian Peninsula. This new situation causes the transfer of moisture from the Arabian Sea into Iran to happen easily and the result would be pervasive wet winters for Iran. But, during spring, Tibetan low pressure and the Atlantic Ocean’s high pressure are the most important actors of climate in southwest Asia. Whenever the low pressure of the Tibetan plateau low pressure is strengthened and expanded over the eastern half of the Arabian Sea, the high pressure established over Saudi Arabia would be dislocated westward as a result of which pervasive droughts happen in Iran. However, when the Tibetan Plateau’s low pressure is ameliorated and its western part distances away from the Arabian Sea, the Atlantic Ocean’s dynamic high pressure is corroborated and its eastern part is expanded. This expansion causes the high pressure situated over the Saudi Arabian Peninsula to move eastward with its central core taking place over the western shores of the Arabian Sea under which conditions the whole Arabian Sea would be captured by this high pressure. This high pressure transfers the Arabian Sea’s moisture through the Saudi Arabian Peninsula’s moisture canal into Iran via a clockwise circulation. During the ending months of spring, as well, and with the northward dislocation of the tropical convergence belt and its establishment over southern Asia and also with the establishment of some parts of India’s monsoon low pressure over the eastern half of the Arabian Sea, the moisture transfer from the Arabian Sea into Iran is practically decreased to a minimum. Discussion of Results and Conclusion The results indicated that certain patterns play roles during every season in this sea’s transferring of moisture. During fall, delay in the southward dislocation of southern Asia’s monsoon low pressure causes the transfer of moisture from this sea into Iran to be disrupted the result of which would be pervasive droughts in Iran. During winter when the Asian thermal high pressure reaches its strongest state, its western part is expanded and, together with the Atlantic Ocean’s dynamical high pressure, it captures the whole of central Asia, the Middle East, and northern Africa. Under these conditions, the high pressure established over the Saudi Arabian Peninsula takes a more western position and this new position disrupts moisture transfer from the Arabian Sea into Iran the result of which would be pervasive dry winters for Iran. During spring, the Tibetan low pressure and the Atlantic Ocean’s high pressure are the most important players in the climate in southwest Asia. Whenever the western part of the Tibetan Plateau’s low pressure is strengthened and expanded over the eastern half of the Arabian Sea, the high pressure established over Saudi Arabia is dislocated westward the result of which would be pervasive droughts for Iran.

https://gep.ui.ac.ir/article_27794_bb2f30a4f6c97dbd013dbc13ab381065.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 35 1 2024 03 20 Analysis of Tectonic Status of Lavasan Sub-Basins Using Geomorphic Indicators and Radar Images Analysis of Tectonic Status of Lavasan Sub-Basins Using Geomorphic Indicators and Radar Images 73 88 27994 10.22108/gep.2023.133365.1518 FA Maesomeh Asadi Ph.D. of Geomorphology, faculty member of Payam-e Noor University, Tehran, Iran Hamid Ganjaeian Ph.D. of Geomorphology, Tehran University, Tehran, Iran Mahnaz Javedani Ph.D. student of Geomorphology, Ferdowsi University, Mashhad, Iran Journal Article 2022 04 28 Abstract The tectonic positioning of Iran has led to significant seismic activity in the region, particularly in the Alborz Unit. This study focused on investigating the morphotectonic status of Lavasan Sub-basins located on the southern slopes of the Alborz. To achieve this, a digital elevation model with 30-meter resolution, a 1:50,000 topographic map, a 1:100,000 geological map, and Sentinel-1 radar images were utilized as research data. The analysis employed GMT, ArcGIS, and SPSS software, along with specific indicators to assess the tectonic condition of the region. The research was conducted in two stages. Firstly, the tectonic conditions of the sub-basins were evaluated using morphotectonic indicators and secondly, the vertical displacement of the region was assessed using radar images and the SBAS time-series method. The results of the study indicated that Lavasan Sub-basins exhibited high tectonic activities with Barg and Kond basins averaging a score of 1.88 and Lavasan and Afjeh basins averaging a score of 2. Consequently, the latter basins demonstrated a more active tectonic status based on the IAT index. Additionally, the results obtained from the SBAS time-series method over a 3-year period (from 01/06/2016 to 12/21/2018) revealed a 79-mm elevation and a 14-mm depression, which could be attributed to tectonic activity, thus corroborating the accuracy of the results obtained from morphotectonic indicators. Keywords: Morphotectonics, Morphotectonic Indices, SBAS, Lavasan Introduction Iran, situated within the Alpine-Himalayan tectonic active zone, has been significantly impacted by tectonic activities throughout its history. The formation of the Indian Ocean is a direct result of this tectonic convergence. The Iranian plateau, due to its tectonic positioning, has experienced various seismic events, including those within the Alborz Unit. The presence of newborn landforms in Alborz Region, such as cliffs, anticline morphology, and seismic activity, serves as evidence of the high frequency of recent tectonic activities, a concept explored in geomorphological tectonics. Geomorphological tectonics focuses on the study of landforms shaped and transformed by tectonic activity. Landforms in regions with active tectonics are the product of a complex interplay between vertical and horizontal movements of crustal blocks and erosion or sedimentation by surface processes. Therefore, assessing and studying tectonic activities and their impacts is crucial in regional development planning, land management, and environmental conservation. Catchments are one of the key areas used to investigate the tectonic status of a region. River systems, in general, serve as valuable tools for studying tectonic interactions as rivers, drainage networks, and alluvial fans are highly sensitive to tectonic changes. Accordingly, this study focused on examining the morphotectonic status of Lavasan Sub-basins located on the southern slopes of the Alborz. Materials and Methods This study utilized a digital elevation model with a 30-meter resolution, a 1:50,000 topographic map, a 1:100,000 geological map, and Sentinel-1 radar images as primary research data. Key research tools included GMT, ARCGIS, and SPSS software, along with specific indicators used to assess the tectonic condition of the region. The research was conducted in two stages. Firstly, the morphotectonic status of the studied basins was evaluated using 8 indicators, namely branching ratio (Br), basin drainage density (Dd), drainage basin asymmetry (AF), longitudinal river gradient (SL), basin shape (Bs), inverse topographic symmetry (T), hypsometric integral (Hi), and river sine index (S). In the second stage, 27 radar images of Sentinel 1 (SLC type with VV polarization) were employed to assess the vertical displacement of the region as detailed in Table 3. Following the preparation of the images and necessary preprocessing, a specific pair of images was selected based on the timeline for radar interference (refer to Figure 3). Subsequently, interferograms were generated using radar interferometry and ultimately, the vertical displacement of the region was determined using the SBAS time-series method. Research Findings The evaluation of the branching ratio (Br) in the studied basins revealed that Kond Basin with a coefficient of 4.64 exhibited the highest branching coefficient, indicating greater tectonic activity compared to other sub-basins. Similarly, calculation of the drainage density index (Dd) demonstrated that Kond Basin, with a coefficient of 3.57 had the highest drainage density (Figure 3), signifying elevated tectonic activity compared to other sub-basins. Furthermore, the drainage basin asymmetry (AF) index indicated that Kond Basin with a coefficient of 61.2 displayed the highest asymmetry, suggesting a more active tectonic state. The longitudinal river gradient index (SL) revealed that Kond Basin with a coefficient of 2698 had the highest gradient, positioning it as the most active basin. Additionally, the basin shape index (Bs) highlighted that Afjeh Basin with a coefficient of 2.87 exhibited the highest coefficient, indicating it as the most active basin. The inverse topographic symmetry index (T) and the hypsometric integral index (Hi) also identified Afjeh Basin as the most active basin with a coefficient of 2.87. Moreover, the river sinusoidal index (S) indicated that Kond Basin with a coefficient of 1.19 had the lowest coefficient, designating it as the most active basin based on this index. Finally, the results from the SBAS time-series method revealed a 79-mm increase and a 14-mm decrease in the region over a 3-year period (from 01/06/2016 to 12/21/2018). Discussion of Results & Conclusion Assessment of the tectonic status of the studied sub-basins using morphometric indices indicated that all sub-basins exhibited significant tectonic activities. Specifically, the results obtained from the IAT index categorized the study basins as having high tectonic activities. Barg and Kond basins had an average score of 1.88, while Lavasan and Afjeh basins had an average score of 2, signifying a higher level of tectonic activity in Barg and Kond basins based on the IAT index. Comparative analysis of the results revealed that Kond Basin demonstrated a more active tectonic status across various indices, including Br, Dd, AF, SL, T, and S, positioning it as the most active basin among the study basins. Furthermore, the findings from the radar images corroborated the tectonic activity in the study area. The results obtained from the SBAS time-series method over a 3-year period (from 01/06/2016 to 12/21/2018) indicated a significant elevation of 79 mm and a depression of 14 mm, which could be attributed to tectonic activity, thus validating the accuracy of the results obtained from the morphotectonic indices. Abstract The tectonic positioning of Iran has led to significant seismic activity in the region, particularly in the Alborz Unit. This study focused on investigating the morphotectonic status of Lavasan Sub-basins located on the southern slopes of the Alborz. To achieve this, a digital elevation model with 30-meter resolution, a 1:50,000 topographic map, a 1:100,000 geological map, and Sentinel-1 radar images were utilized as research data. The analysis employed GMT, ArcGIS, and SPSS software, along with specific indicators to assess the tectonic condition of the region. The research was conducted in two stages. Firstly, the tectonic conditions of the sub-basins were evaluated using morphotectonic indicators and secondly, the vertical displacement of the region was assessed using radar images and the SBAS time-series method. The results of the study indicated that Lavasan Sub-basins exhibited high tectonic activities with Barg and Kond basins averaging a score of 1.88 and Lavasan and Afjeh basins averaging a score of 2. Consequently, the latter basins demonstrated a more active tectonic status based on the IAT index. Additionally, the results obtained from the SBAS time-series method over a 3-year period (from 01/06/2016 to 12/21/2018) revealed a 79-mm elevation and a 14-mm depression, which could be attributed to tectonic activity, thus corroborating the accuracy of the results obtained from morphotectonic indicators. Keywords: Morphotectonics, Morphotectonic Indices, SBAS, Lavasan Introduction Iran, situated within the Alpine-Himalayan tectonic active zone, has been significantly impacted by tectonic activities throughout its history. The formation of the Indian Ocean is a direct result of this tectonic convergence. The Iranian plateau, due to its tectonic positioning, has experienced various seismic events, including those within the Alborz Unit. The presence of newborn landforms in Alborz Region, such as cliffs, anticline morphology, and seismic activity, serves as evidence of the high frequency of recent tectonic activities, a concept explored in geomorphological tectonics. Geomorphological tectonics focuses on the study of landforms shaped and transformed by tectonic activity. Landforms in regions with active tectonics are the product of a complex interplay between vertical and horizontal movements of crustal blocks and erosion or sedimentation by surface processes. Therefore, assessing and studying tectonic activities and their impacts is crucial in regional development planning, land management, and environmental conservation. Catchments are one of the key areas used to investigate the tectonic status of a region. River systems, in general, serve as valuable tools for studying tectonic interactions as rivers, drainage networks, and alluvial fans are highly sensitive to tectonic changes. Accordingly, this study focused on examining the morphotectonic status of Lavasan Sub-basins located on the southern slopes of the Alborz. Materials and Methods This study utilized a digital elevation model with a 30-meter resolution, a 1:50,000 topographic map, a 1:100,000 geological map, and Sentinel-1 radar images as primary research data. Key research tools included GMT, ARCGIS, and SPSS software, along with specific indicators used to assess the tectonic condition of the region. The research was conducted in two stages. Firstly, the morphotectonic status of the studied basins was evaluated using 8 indicators, namely branching ratio (Br), basin drainage density (Dd), drainage basin asymmetry (AF), longitudinal river gradient (SL), basin shape (Bs), inverse topographic symmetry (T), hypsometric integral (Hi), and river sine index (S). In the second stage, 27 radar images of Sentinel 1 (SLC type with VV polarization) were employed to assess the vertical displacement of the region as detailed in Table 3. Following the preparation of the images and necessary preprocessing, a specific pair of images was selected based on the timeline for radar interference (refer to Figure 3). Subsequently, interferograms were generated using radar interferometry and ultimately, the vertical displacement of the region was determined using the SBAS time-series method. Research Findings The evaluation of the branching ratio (Br) in the studied basins revealed that Kond Basin with a coefficient of 4.64 exhibited the highest branching coefficient, indicating greater tectonic activity compared to other sub-basins. Similarly, calculation of the drainage density index (Dd) demonstrated that Kond Basin, with a coefficient of 3.57 had the highest drainage density (Figure 3), signifying elevated tectonic activity compared to other sub-basins. Furthermore, the drainage basin asymmetry (AF) index indicated that Kond Basin with a coefficient of 61.2 displayed the highest asymmetry, suggesting a more active tectonic state. The longitudinal river gradient index (SL) revealed that Kond Basin with a coefficient of 2698 had the highest gradient, positioning it as the most active basin. Additionally, the basin shape index (Bs) highlighted that Afjeh Basin with a coefficient of 2.87 exhibited the highest coefficient, indicating it as the most active basin. The inverse topographic symmetry index (T) and the hypsometric integral index (Hi) also identified Afjeh Basin as the most active basin with a coefficient of 2.87. Moreover, the river sinusoidal index (S) indicated that Kond Basin with a coefficient of 1.19 had the lowest coefficient, designating it as the most active basin based on this index. Finally, the results from the SBAS time-series method revealed a 79-mm increase and a 14-mm decrease in the region over a 3-year period (from 01/06/2016 to 12/21/2018). Discussion of Results & Conclusion Assessment of the tectonic status of the studied sub-basins using morphometric indices indicated that all sub-basins exhibited significant tectonic activities. Specifically, the results obtained from the IAT index categorized the study basins as having high tectonic activities. Barg and Kond basins had an average score of 1.88, while Lavasan and Afjeh basins had an average score of 2, signifying a higher level of tectonic activity in Barg and Kond basins based on the IAT index. Comparative analysis of the results revealed that Kond Basin demonstrated a more active tectonic status across various indices, including Br, Dd, AF, SL, T, and S, positioning it as the most active basin among the study basins. Furthermore, the findings from the radar images corroborated the tectonic activity in the study area. The results obtained from the SBAS time-series method over a 3-year period (from 01/06/2016 to 12/21/2018) indicated a significant elevation of 79 mm and a depression of 14 mm, which could be attributed to tectonic activity, thus validating the accuracy of the results obtained from the morphotectonic indices.

https://gep.ui.ac.ir/article_27994_6237c47839774370043fb2d2c765adf9.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 35 1 2024 03 20 Investigating the Effects of Some Ecological Indicators of Forest Patches on the Supply of Selected Ecosystem Services (Study Area: Eastern Part of Gilan Province) Investigating the Effects of Some Ecological Indicators of Forest Patches on the Supply of Selected Ecosystem Services (Study Area: Eastern Part of Gilan Province) 89 110 27792 10.22108/gep.2023.138399.1595 FA Mahdis Sadat - Ph.D. of Environmental Planning, Department of Environmental Planning, Management and Education, Factuality of Environment, University of Tehran, Tehran, Iran Mahmood Zoghi h.D. of Environmental Planning, Department of Environmental Planning, Management and Education, Factuality of Environment, University of Tehran, Tehran, Iran Mohammad Javad Amiri Assistant professor, Department of Environmental Planning, Management and Education, Factuality of Environment, University of Tehran, Tehran, Iran Journal Article 2023 07 15 Abstract In recent years, augmentation of ecosystem services has emerged as a critical concern. However, there is a dearth of information regarding ecosystem services within the realm of planning. This study sought to address this gap by assessing the influence of landscape structure on ecosystem functionality. To achieve this, we utilized InVEST software to model ecosystem services, such as carbon sequestration, soil maintenance, and flood prevention. Additionally, we employed MSPA and Fragstate software to derive 4 key ecological indicators: biomass quantity, fragmentation, core area, and ratio of environmental area to forest core area. Subsequently, we examined the relationship between these ecological indicators and the selected ecosystem services. Our findings indicated a robust and positive correlation between the presence of forested and verdant areas, as well as larger and more interconnected cores within these areas, and the provision of desired services. Notably, in forest patches, a decrease in ecosystem service provision was observed with increased fragmentation and instability, underscoring the importance of preserving and expanding the Hyrcanian forests while also prioritizing integrity and reducing isolated patches for enhancing ecological productivity in the northern provinces of the country. Keywords: Ecosystem, Ecosystem Services, Ecological Indicators, Planning Introduction The decline of ecosystem services is a matter of grave concern as it has the potential to undermine the long-term resilience of ecosystems and precipitate abrupt changes that jeopardize a safe habitat for humanity. The type and intensity of land use, along with the spatial arrangement of land cover types within a region, can significantly alter its capacity to furnish ecosystem services. This is because transitioning from one land use type to another impacts crucial ecological processes, such as energy exchange, water cycle, and biogeochemical cycles, consequently influencing the provision of ecosystem services. Configuration of land use is a pivotal structural factor that influences ecosystem functionality and delivery of services. Notably, human activities, land cover, and associated changes have been identified from among the most influential factors shaping the structure, composition, and function of ecosystems that underpin their services. Effective land use management and planning necessitate an initial phase of assessing and mapping ecosystem services. This stage yields crucial information, including identification of areas that yield high levels of service and require protection or management to sustain the services provided, as well as recognition of areas with specific ecosystem services and changes in the provision of ecosystem services over time. Despite previous research efforts, no study has comprehensively explored the significant ecological indicators in relation to overall ecosystem services. Furthermore, optimization of ecological network elements to enhance ecosystem services has been predominantly limited to the establishment of corridors between ecological network cores (Xiao et al., 2020; Guo et al., 2018; Shi and Qin, 2018). Therefore, this study endeavored to identify and evaluate the relationships between key ecological indicators and ecosystem services. Materials & Methods The research area encompassed two watersheds, Lahijan Chaboksar and Astana-Kuchesfahan, situated in the eastern and central regions of Gilan Province, respectively. The initial step of this study involved the classification of satellite images of the study area in 2020. To achieve this, Landsat 8 images captured between 01/01/2020 and 12/31/2020 with cloud cover below 10% were utilized. Subsequently, classification of land cover was conducted, employing normalized vegetation difference index products and guidelines for the four seasons, urban areas, and tree cover to identify forested areas with trees exceeding 30 meters in height. Additionally, ground-based data input by the user was utilized to classify land cover into 8 categories: forested areas, open spaces, pastures, agricultural lands, tea cultivation lands, gardens, water bodies, and man-made lands encompassing roads and urban areas. In the subsequent phase, 3 pivotal ecosystem services—carbon storage, flood mitigation, and sediment preservation—were selected for assessment. These services represented crucial contributions of the watershed, reflecting its equilibrium. The latest iteration of the Integrated Valuation of Ecosystem Services (InVEST) model was employed to quantify these services. Following the modeling and unweighting of the targeted services, the aggregate ecosystem service value was computed from the set of unweighted services. Furthermore, 4 ecological indicators—fragmentation, Normalized Difference Vegetation Index (NDVI), forest core area, and ratio of environmental area to core area—were evaluated. Subsequently, 1600 samples were selected using the "Fishnet" tool to calculate the correlation coefficient of total ecosystem services with the designated indicators. The data pertaining to ecological indicators and total ecosystem services were extracted from these samples. Pearson's correlation was then utilized to ascertain the magnitude, nature, and direction of the relationship between the two variables. Research Findings The index of Total Ecosystem Services (TES) for the three services under scrutiny ranged from 2.67 to 0.0, representing the highest and lowest values, respectively. Notably, the lowest value of service provision within the watershed was modeled in urban and built-up areas, registering a value of 0, while the highest value was observed in areas with a slope of less than 10% within the Hyrcanian forests, reaching a peak value of 2.67. Furthermore, in the northern region where agricultural lands had expanded, they accounted for the highest level of service provision following the forests. Calculation of NDVI revealed a range of 0.03 to 0.99 across the region. The highest NDVI values were recorded in densely populated areas in the south where the Hyrcanian forests were prevalent, while the lowest values were observed in man-made areas. Additionally, the disintegration index computed using GTB software fluctuated between 0 and 101 within the studied watershed. The lowest forest fragmentation rates were concentrated in the inner and central areas of the Hyrcanian forests in the southern half of the region, whereas the highest rates were found in isolated patches in the northern half part. Despite being fragmented, the forest edges exhibited an intermediate state owing to the high density of patches. An examination of the correlation between the aforementioned indices and TES revealed a significant positive correlation between TES and NDVI, as well as core area, with the correlation coefficients of 0.77 and 0.70, respectively. This suggested that an increase in either of these factors could lead to an enhancement in the quantity of the ecosystem services in question. Conversely, there existed a notable negative correlation between the TES index and the ratio of environmental area to core area, as well as the fragmentation index, with the correlation coefficients of -0.63 and -0.71, respectively. This implied that an increase in forest fragmentation or a shift towards edge-like configurations would diminish the provision of the desired services. Discussion of Results & Conclusion The findings indicated that areas with more forest cover and greenery, as well as larger cores within these areas, were capable of providing more substantial ecosystem services. These results aligned with the findings of Situmorang et al. in 2016 and Shen et al. in 2019. Conversely, as the perimeter-to-core area ratio of forest patches increased, leading to a greater tendency for patches to become smaller and unstable, and as fragmentation within these patches intensified, the capacity of these patches to provide ecosystem services diminished significantly. These outcomes were consistent with the findings of Saeed et al. in 2019. Overall, this research underscored the influential role of secondary factors, in addition to land use, in the provision of ecosystem services. This insight can inform planning efforts aimed at enhancing the efficiency of programs and optimizing the delivery of desired ecosystem services. It is imperative to take proactive measures in this regard. Abstract In recent years, augmentation of ecosystem services has emerged as a critical concern. However, there is a dearth of information regarding ecosystem services within the realm of planning. This study sought to address this gap by assessing the influence of landscape structure on ecosystem functionality. To achieve this, we utilized InVEST software to model ecosystem services, such as carbon sequestration, soil maintenance, and flood prevention. Additionally, we employed MSPA and Fragstate software to derive 4 key ecological indicators: biomass quantity, fragmentation, core area, and ratio of environmental area to forest core area. Subsequently, we examined the relationship between these ecological indicators and the selected ecosystem services. Our findings indicated a robust and positive correlation between the presence of forested and verdant areas, as well as larger and more interconnected cores within these areas, and the provision of desired services. Notably, in forest patches, a decrease in ecosystem service provision was observed with increased fragmentation and instability, underscoring the importance of preserving and expanding the Hyrcanian forests while also prioritizing integrity and reducing isolated patches for enhancing ecological productivity in the northern provinces of the country. Keywords: Ecosystem, Ecosystem Services, Ecological Indicators, Planning Introduction The decline of ecosystem services is a matter of grave concern as it has the potential to undermine the long-term resilience of ecosystems and precipitate abrupt changes that jeopardize a safe habitat for humanity. The type and intensity of land use, along with the spatial arrangement of land cover types within a region, can significantly alter its capacity to furnish ecosystem services. This is because transitioning from one land use type to another impacts crucial ecological processes, such as energy exchange, water cycle, and biogeochemical cycles, consequently influencing the provision of ecosystem services. Configuration of land use is a pivotal structural factor that influences ecosystem functionality and delivery of services. Notably, human activities, land cover, and associated changes have been identified from among the most influential factors shaping the structure, composition, and function of ecosystems that underpin their services. Effective land use management and planning necessitate an initial phase of assessing and mapping ecosystem services. This stage yields crucial information, including identification of areas that yield high levels of service and require protection or management to sustain the services provided, as well as recognition of areas with specific ecosystem services and changes in the provision of ecosystem services over time. Despite previous research efforts, no study has comprehensively explored the significant ecological indicators in relation to overall ecosystem services. Furthermore, optimization of ecological network elements to enhance ecosystem services has been predominantly limited to the establishment of corridors between ecological network cores (Xiao et al., 2020; Guo et al., 2018; Shi and Qin, 2018). Therefore, this study endeavored to identify and evaluate the relationships between key ecological indicators and ecosystem services. Materials & Methods The research area encompassed two watersheds, Lahijan Chaboksar and Astana-Kuchesfahan, situated in the eastern and central regions of Gilan Province, respectively. The initial step of this study involved the classification of satellite images of the study area in 2020. To achieve this, Landsat 8 images captured between 01/01/2020 and 12/31/2020 with cloud cover below 10% were utilized. Subsequently, classification of land cover was conducted, employing normalized vegetation difference index products and guidelines for the four seasons, urban areas, and tree cover to identify forested areas with trees exceeding 30 meters in height. Additionally, ground-based data input by the user was utilized to classify land cover into 8 categories: forested areas, open spaces, pastures, agricultural lands, tea cultivation lands, gardens, water bodies, and man-made lands encompassing roads and urban areas. In the subsequent phase, 3 pivotal ecosystem services—carbon storage, flood mitigation, and sediment preservation—were selected for assessment. These services represented crucial contributions of the watershed, reflecting its equilibrium. The latest iteration of the Integrated Valuation of Ecosystem Services (InVEST) model was employed to quantify these services. Following the modeling and unweighting of the targeted services, the aggregate ecosystem service value was computed from the set of unweighted services. Furthermore, 4 ecological indicators—fragmentation, Normalized Difference Vegetation Index (NDVI), forest core area, and ratio of environmental area to core area—were evaluated. Subsequently, 1600 samples were selected using the "Fishnet" tool to calculate the correlation coefficient of total ecosystem services with the designated indicators. The data pertaining to ecological indicators and total ecosystem services were extracted from these samples. Pearson's correlation was then utilized to ascertain the magnitude, nature, and direction of the relationship between the two variables. Research Findings The index of Total Ecosystem Services (TES) for the three services under scrutiny ranged from 2.67 to 0.0, representing the highest and lowest values, respectively. Notably, the lowest value of service provision within the watershed was modeled in urban and built-up areas, registering a value of 0, while the highest value was observed in areas with a slope of less than 10% within the Hyrcanian forests, reaching a peak value of 2.67. Furthermore, in the northern region where agricultural lands had expanded, they accounted for the highest level of service provision following the forests. Calculation of NDVI revealed a range of 0.03 to 0.99 across the region. The highest NDVI values were recorded in densely populated areas in the south where the Hyrcanian forests were prevalent, while the lowest values were observed in man-made areas. Additionally, the disintegration index computed using GTB software fluctuated between 0 and 101 within the studied watershed. The lowest forest fragmentation rates were concentrated in the inner and central areas of the Hyrcanian forests in the southern half of the region, whereas the highest rates were found in isolated patches in the northern half part. Despite being fragmented, the forest edges exhibited an intermediate state owing to the high density of patches. An examination of the correlation between the aforementioned indices and TES revealed a significant positive correlation between TES and NDVI, as well as core area, with the correlation coefficients of 0.77 and 0.70, respectively. This suggested that an increase in either of these factors could lead to an enhancement in the quantity of the ecosystem services in question. Conversely, there existed a notable negative correlation between the TES index and the ratio of environmental area to core area, as well as the fragmentation index, with the correlation coefficients of -0.63 and -0.71, respectively. This implied that an increase in forest fragmentation or a shift towards edge-like configurations would diminish the provision of the desired services. Discussion of Results & Conclusion The findings indicated that areas with more forest cover and greenery, as well as larger cores within these areas, were capable of providing more substantial ecosystem services. These results aligned with the findings of Situmorang et al. in 2016 and Shen et al. in 2019. Conversely, as the perimeter-to-core area ratio of forest patches increased, leading to a greater tendency for patches to become smaller and unstable, and as fragmentation within these patches intensified, the capacity of these patches to provide ecosystem services diminished significantly. These outcomes were consistent with the findings of Saeed et al. in 2019. Overall, this research underscored the influential role of secondary factors, in addition to land use, in the provision of ecosystem services. This insight can inform planning efforts aimed at enhancing the efficiency of programs and optimizing the delivery of desired ecosystem services. It is imperative to take proactive measures in this regard.

https://gep.ui.ac.ir/article_27792_0f990e8d675bd919d02c6123c627cf46.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 35 1 2024 03 20 Forecasting Magnitudes and Locations of Potential Earthquakes along Railway Lines in Hormozgan Province Using Artificial Neural Network (ANN) Forecasting Magnitudes and Locations of Potential Earthquakes along Railway Lines in Hormozgan Province Using Artificial Neural Network (ANN) 111 128 28047 10.22108/gep.2023.136336.1569 FA Mohsen Pourkhosravani Associate professor, Department of Geography, Shahid Bahonar University of Kerman, Kerman, Iran Ali Mehrabi Associate professor, Department of Geography, Shahid Bahonar University of Kerman, Kerman, Iran Zahra Amirjahanshahi Master's degree in Natural Hazards, Shahid Bahonar University of Kerman, Kerman, Iran Journal Article 2023 01 09 Abstract Predicting the magnitude and location of earthquakes can significantly mitigate the impact of this natural phenomenon. Anticipating potential earthquake locations can enhance infrastructure resilience and reduce vulnerability. This study aimed to forecast and analyze the magnitude and location of potential earthquakes along the railway lines in Hormozgan Province using intelligent Artificial Neural Network (ANN) algorithms. The model utilized earthquake location, magnitude, and depth data from the International Institute of Seismology and Earthquake Engineering, as well as fault lengths in the region as the input variables. The findings revealed 32 potential earthquake points in the study area with projected magnitudes ranging from 4.3 to 5.2 on the Richter scale. The earthquake prediction-based zoning of Hormozgan Province indicated that the southern and central parts (north of the Strait of Hormuz) were at a high risk. Consequently, the rail lines in this area were more susceptible. Specifically, Tunnel No. 23 was situated in a high-risk zone and Tunnels 21, 22, and 23 were in close proximity to earthquakes with magnitudes exceeding 5 on the Richter scale. Keywords: Forecast, Railway Lines, Earthquake, Artificial Neural Network (ANN), Hormozgan Province. Introduction Earthquakes represent one of the most intricate and nonlinear natural phenomena. Their complex nature and system variability make predicting their magnitudes and locations seemingly impossible. However, forecasting these aspects of earthquakes can significantly mitigate the damage caused by such events. Anticipating the locations of potential earthquakes can bolster infrastructure and facilities in these areas, reducing their vulnerability. Consequently, the quest for reliable methods to predict the timing, location, and magnitude of earthquakes has been a focal point of recent research. Artificial Neural Networks (ANNs) have emerged as powerful tools for earthquake prediction, offering several key advantages. Firstly, they excel at learning complex, nonlinear environments. Secondly, they make no assumptions about data distribution and thirdly, they exhibit flexibility in handling incomplete or missing data (Vellido et al., 1999, p. 53). Overall, ANNs have demonstrated success in various domains, including system identification, approximation and estimation, optimization, and behavior prediction (Cigizoglu & Kisi, 2006, p. 236). Hormozgan Province situated in the folded Zagros belt harbors numerous faults and has experienced destructive earthquakes in the past, indicating its high seismic potential. Therefore, this study sought to address the following questions: What is the likelihood of high-magnitude earthquakes occurring in Hormozgan Province? And where are the potential locations of these earthquakes? Materials & Methods This applied study aimed to forecast the magnitudes and locations of potential earthquakes in Hormozgan Province using the ANN algorithm. The simulation utilized earthquake location, depth, and magnitude data for events exceeding 4 on the Richter scale in the study area, along with fault length, as the model inputs. The prediction of earthquake magnitudes was carried out using the Perceptron neural network, while the Cohen's neural network was employed to forecast potential earthquake locations. Specifically, the Perceptron neural network was utilized for magnitude prediction and the Self-Organizing Feature Map (SOFM) neural network was employed for location prediction. Research Findings In general, the seismic potential of faults to generate earthquakes is influenced by seismic history, tectonic movement, and fault dimensions. Through the application of ANNs, a total of 32 potential earthquake locations were predicted with projected magnitudes ranging from 4.3 to 5.2. Discussion of Results & Conclusion The study's findings indicated the prediction of 32 potential earthquake locations in the study area with projected magnitudes ranging from 4.3 to 5.2 on the Richter scale. Consequently, zoning of Hormozgan Province based on these predictions revealed that the southern and central parts of the province (north of the Strait of Hormuz) were situated in high-risk zones. This heightened risk could make the rail lines in this area more susceptible to potential seismic events. Notably, Tunnel No. 23 was located in a high-risk area and Tunnels 21, 22, and 23 were in close proximity to earthquakes with magnitudes exceeding 5 on the Richter scale. Abstract Predicting the magnitude and location of earthquakes can significantly mitigate the impact of this natural phenomenon. Anticipating potential earthquake locations can enhance infrastructure resilience and reduce vulnerability. This study aimed to forecast and analyze the magnitude and location of potential earthquakes along the railway lines in Hormozgan Province using intelligent Artificial Neural Network (ANN) algorithms. The model utilized earthquake location, magnitude, and depth data from the International Institute of Seismology and Earthquake Engineering, as well as fault lengths in the region as the input variables. The findings revealed 32 potential earthquake points in the study area with projected magnitudes ranging from 4.3 to 5.2 on the Richter scale. The earthquake prediction-based zoning of Hormozgan Province indicated that the southern and central parts (north of the Strait of Hormuz) were at a high risk. Consequently, the rail lines in this area were more susceptible. Specifically, Tunnel No. 23 was situated in a high-risk zone and Tunnels 21, 22, and 23 were in close proximity to earthquakes with magnitudes exceeding 5 on the Richter scale. Keywords: Forecast, Railway Lines, Earthquake, Artificial Neural Network (ANN), Hormozgan Province. Introduction Earthquakes represent one of the most intricate and nonlinear natural phenomena. Their complex nature and system variability make predicting their magnitudes and locations seemingly impossible. However, forecasting these aspects of earthquakes can significantly mitigate the damage caused by such events. Anticipating the locations of potential earthquakes can bolster infrastructure and facilities in these areas, reducing their vulnerability. Consequently, the quest for reliable methods to predict the timing, location, and magnitude of earthquakes has been a focal point of recent research. Artificial Neural Networks (ANNs) have emerged as powerful tools for earthquake prediction, offering several key advantages. Firstly, they excel at learning complex, nonlinear environments. Secondly, they make no assumptions about data distribution and thirdly, they exhibit flexibility in handling incomplete or missing data (Vellido et al., 1999, p. 53). Overall, ANNs have demonstrated success in various domains, including system identification, approximation and estimation, optimization, and behavior prediction (Cigizoglu & Kisi, 2006, p. 236). Hormozgan Province situated in the folded Zagros belt harbors numerous faults and has experienced destructive earthquakes in the past, indicating its high seismic potential. Therefore, this study sought to address the following questions: What is the likelihood of high-magnitude earthquakes occurring in Hormozgan Province? And where are the potential locations of these earthquakes? Materials & Methods This applied study aimed to forecast the magnitudes and locations of potential earthquakes in Hormozgan Province using the ANN algorithm. The simulation utilized earthquake location, depth, and magnitude data for events exceeding 4 on the Richter scale in the study area, along with fault length, as the model inputs. The prediction of earthquake magnitudes was carried out using the Perceptron neural network, while the Cohen's neural network was employed to forecast potential earthquake locations. Specifically, the Perceptron neural network was utilized for magnitude prediction and the Self-Organizing Feature Map (SOFM) neural network was employed for location prediction. Research Findings In general, the seismic potential of faults to generate earthquakes is influenced by seismic history, tectonic movement, and fault dimensions. Through the application of ANNs, a total of 32 potential earthquake locations were predicted with projected magnitudes ranging from 4.3 to 5.2. Discussion of Results & Conclusion The study's findings indicated the prediction of 32 potential earthquake locations in the study area with projected magnitudes ranging from 4.3 to 5.2 on the Richter scale. Consequently, zoning of Hormozgan Province based on these predictions revealed that the southern and central parts of the province (north of the Strait of Hormuz) were situated in high-risk zones. This heightened risk could make the rail lines in this area more susceptible to potential seismic events. Notably, Tunnel No. 23 was located in a high-risk area and Tunnels 21, 22, and 23 were in close proximity to earthquakes with magnitudes exceeding 5 on the Richter scale.

https://gep.ui.ac.ir/article_28047_7187dc529fb1ba340c19bd3d8b4ca801.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 35 1 2024 03 20 Analyzing Spatial Dust Changes in Tehran Using Chaos Theory in Spatial Epistemology Analyzing Spatial Dust Changes in Tehran Using Chaos Theory in Spatial Epistemology 129 144 28060 10.22108/gep.2023.138767.1604 FA Manijeh Ghahroudi Tali Ph.D., Department of Physical Geography, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran 0000-0002-8817-9329 Ramin Rahimi Ph.D. student of geomorphology, Department of Physical Geography, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran Journal Article 2023 08 19 Abstract This research investigated the specific patterns of dust influx into the metropolis of Tehran from 2005 to 2017. The study utilized the data on dust occurrence days and synoptic station data in Tehran. The research methodology involved employing the HYSPLIT trajectory model, as well as dust detection indices, and determining the chemical properties of dust, including main and rare elements, by using the X-Ray Fluorescence (XRF) method. The findings indicated that the primary source of dust entering Tehran originated from desert regions and vast, arid areas outside the country. External sources of dust, such as the North Arabian Sahara and the East African Sahara, have been active since ancient times and are not solely related to modern dust occurrences. The cause of their impact on Tehran could be attributed to the desiccation of internal lagoons and lakes. The changes in the frequency of fine-dust trajectories could not be solely explained by their connection with external sources. Instead, it appeared that the micro-particle movement system was striving to establish a deeper order, which was not solely influenced by changes in the origin and destination of the particles. Rather, the entry of fine particles into this movement system had undergone changes during their movement within the system. Keywords: Dust, Tehran, Chaos, HYSPLIT Introduction The shifting distribution of dust in various regions around the world has led to the presence of dust in major cities during certain seasons. Tehran has been particularly affected by this phenomenon from its onset. Despite the fact that numerous research efforts have aimed at understanding the origins of this phenomenon, the spatial patterns of its changes remain a topic of ongoing investigation. This study sought to elucidate the spatial dynamics of dust influx into Tehran by using a spatial epistemology approach. Analysis of MODIS images and their correlation with climate models was conducted for the period spanning 2005 to 2020. Preliminary findings indicated that the dust phenomenon adhered to specific patterns and pathways, from its initial emergence at focal points to its eventual arrival in the city of Tehran. Materials & Methods Tehran, the capital and one of the largest cities in the world, is situated on the southern slope of the Alborz highlands near the major permanent water networks of the region, namely the rivers of Karaj to the west and Jajrud to the east. The city grapples with various environmental challenges, including the issue of fine dust. Investigation into the trajectory of fine dust movement has revealed that the presence of features, such as playas, lakes, dried-up wetlands, old alluvial terraces, and sand mines significantly influences the arrival of fine dust in the area of Tehran. These particles are exceedingly small. Given the frequent occurrences of dust particles between 2000 and 2015 and availability of local data archives, the period from 2005 to 2017 was chosen for this study. Data collection was conducted in Tehran and its synoptic stations. Analysis of long-term wind-rose data from the indicator stations revealed that the prevailing wind direction in Tehran Province was predominantly from the west and south in most months. To identify regional dust sources, wind speed and direction maps were utilized and the HYSPLIT trajectory model was employed to track their paths. The HYSPLIT model in conjunction with atmospheric maps and satellite images was used to enhance the validity of the research findings for all dust events. Detection indices for fine dust, including the Brightness Temperature Difference (BTD) index, dust index method, and Miller's method, were utilized. Additionally, the X-Ray Fluorescence (XRF) method was employed to determine the chemical compositions of dust, including major and rare elements, in the samples collected from specific areas. The results obtained from climate modeling and MODIS image processing facilitated the identification of key areas influencing the movement patterns of fine dust toward Tehran. These areas predominantly corresponded to end basins (playas, lakes, lagoons) of old alluvial terraces and desert plains. Research Findings Through the analysis of MODIS images and their correlation with climate models spanning the years 2005 to 2020, it was established that the phenomenon of dust followed specific patterns and pathways from its origin at focal points to its arrival in Tehran. This pattern predominantly occurred in July with its initial flow originating from the northeast of Syria. Another pattern occurring in late winter and early spring originated from the Arabian Desert. Patterns with a more west-east axis corresponding to westerly currents originating from the deserts of northern Arabia predominantly occurred in the warm months of the year. Additionally, dust concentration nuclei might have been formed in East Africa and over Saudi Arabia, subsequently moving to Iraq and Iran. The primary source of dust entering Tehran was located in desert and arid expanses outside the country. Many of the external sources of dust, such as the North Arabian Sahara and the East African Sahara, are not new phenomena and have been active since ancient times, never previously extending into Iran's interior regions like Tehran. The current spread of this dynamic phenomenon is being investigated with its cause being attributed to drying of wetlands and internal lakes. The areas under scrutiny in this study included sand exploitation levels and sand mines in Tehran, Alikhan Dam, Hoze Soltan Lake, Mighan, and the desert lands around Qazvin Plain. Geochemical tests confirmed the similarity in elemental composition between the area and the dust collected in Tehran. The resemblance in chemical compositions of the elements sampled from mine surfaces and those collected with the MDCO sediment trap suggested that a significant portion of silicon dioxide (SiO2) found in the chemical compositions of dust in Tehran was likely sourced from the sand and sand mines of Tehran. This was because all dust-carrying streams passed over these mines, indicating the potential role of these mines in the elemental composition and deposition of dust in Tehran. MODIS images indicated the formation of dust condensation cores on the surfaces of Hoze Soltan and Mighan lakes, which had the potential to intensify dust flows. A comparison of the average compositions of Hoze Soltan, Mighan, and Tehran lakes revealed the presence of potassium and sodium compounds, as well as chlorine, similar to the samples from these lakes, suggesting that some of the elements of sodium, chlorine, and potassium entering Tehran might have been collected while passing through the fine-grained and separated lands around these lakes. Furthermore, the observations related to the geochemical sediment compositions of samples collected in Tehran using sediment traps compared to those collected in Qazvin Plain showed the significant presence of chlorine, potassium, and silicon among the elements. Discussion of Results & Conclusion The research findings revealed that the sources influencing the alterations in the trajectory of micro-storms demonstrated spatial adaptation to playas, wetlands, and end basins in general. In essence, there were discernible changes in the frequency of dust entry patterns in Tehran and these changes could not be solely attributed to their connection with the input sources. Instead, it appeared that the micro-particle movement system was striving to establish a more deeply organized structure independent of changes in its origin and destination. Rather, the entry of fine particles into this movement system had undergone modifications during their transit within the system. Consequently, alterations were being introduced to the initial conditions within the system governing dust entry into Tehran from its feeding sources. Although the dimensions of these sources were relatively small compared to the original source, they could significantly impact the trajectory of fine particles. Laboratory studies on the samples from Tehran's sediment traps, as well as sand mines, Alikhan Dam, Hoze Soltan and Mighan lakes, and the desert lands around Qazvin Plain, underscored their role in contributing to fine dust in Tehran. Abstract This research investigated the specific patterns of dust influx into the metropolis of Tehran from 2005 to 2017. The study utilized the data on dust occurrence days and synoptic station data in Tehran. The research methodology involved employing the HYSPLIT trajectory model, as well as dust detection indices, and determining the chemical properties of dust, including main and rare elements, by using the X-Ray Fluorescence (XRF) method. The findings indicated that the primary source of dust entering Tehran originated from desert regions and vast, arid areas outside the country. External sources of dust, such as the North Arabian Sahara and the East African Sahara, have been active since ancient times and are not solely related to modern dust occurrences. The cause of their impact on Tehran could be attributed to the desiccation of internal lagoons and lakes. The changes in the frequency of fine-dust trajectories could not be solely explained by their connection with external sources. Instead, it appeared that the micro-particle movement system was striving to establish a deeper order, which was not solely influenced by changes in the origin and destination of the particles. Rather, the entry of fine particles into this movement system had undergone changes during their movement within the system. Keywords: Dust, Tehran, Chaos, HYSPLIT Introduction The shifting distribution of dust in various regions around the world has led to the presence of dust in major cities during certain seasons. Tehran has been particularly affected by this phenomenon from its onset. Despite the fact that numerous research efforts have aimed at understanding the origins of this phenomenon, the spatial patterns of its changes remain a topic of ongoing investigation. This study sought to elucidate the spatial dynamics of dust influx into Tehran by using a spatial epistemology approach. Analysis of MODIS images and their correlation with climate models was conducted for the period spanning 2005 to 2020. Preliminary findings indicated that the dust phenomenon adhered to specific patterns and pathways, from its initial emergence at focal points to its eventual arrival in the city of Tehran. Materials & Methods Tehran, the capital and one of the largest cities in the world, is situated on the southern slope of the Alborz highlands near the major permanent water networks of the region, namely the rivers of Karaj to the west and Jajrud to the east. The city grapples with various environmental challenges, including the issue of fine dust. Investigation into the trajectory of fine dust movement has revealed that the presence of features, such as playas, lakes, dried-up wetlands, old alluvial terraces, and sand mines significantly influences the arrival of fine dust in the area of Tehran. These particles are exceedingly small. Given the frequent occurrences of dust particles between 2000 and 2015 and availability of local data archives, the period from 2005 to 2017 was chosen for this study. Data collection was conducted in Tehran and its synoptic stations. Analysis of long-term wind-rose data from the indicator stations revealed that the prevailing wind direction in Tehran Province was predominantly from the west and south in most months. To identify regional dust sources, wind speed and direction maps were utilized and the HYSPLIT trajectory model was employed to track their paths. The HYSPLIT model in conjunction with atmospheric maps and satellite images was used to enhance the validity of the research findings for all dust events. Detection indices for fine dust, including the Brightness Temperature Difference (BTD) index, dust index method, and Miller's method, were utilized. Additionally, the X-Ray Fluorescence (XRF) method was employed to determine the chemical compositions of dust, including major and rare elements, in the samples collected from specific areas. The results obtained from climate modeling and MODIS image processing facilitated the identification of key areas influencing the movement patterns of fine dust toward Tehran. These areas predominantly corresponded to end basins (playas, lakes, lagoons) of old alluvial terraces and desert plains. Research Findings Through the analysis of MODIS images and their correlation with climate models spanning the years 2005 to 2020, it was established that the phenomenon of dust followed specific patterns and pathways from its origin at focal points to its arrival in Tehran. This pattern predominantly occurred in July with its initial flow originating from the northeast of Syria. Another pattern occurring in late winter and early spring originated from the Arabian Desert. Patterns with a more west-east axis corresponding to westerly currents originating from the deserts of northern Arabia predominantly occurred in the warm months of the year. Additionally, dust concentration nuclei might have been formed in East Africa and over Saudi Arabia, subsequently moving to Iraq and Iran. The primary source of dust entering Tehran was located in desert and arid expanses outside the country. Many of the external sources of dust, such as the North Arabian Sahara and the East African Sahara, are not new phenomena and have been active since ancient times, never previously extending into Iran's interior regions like Tehran. The current spread of this dynamic phenomenon is being investigated with its cause being attributed to drying of wetlands and internal lakes. The areas under scrutiny in this study included sand exploitation levels and sand mines in Tehran, Alikhan Dam, Hoze Soltan Lake, Mighan, and the desert lands around Qazvin Plain. Geochemical tests confirmed the similarity in elemental composition between the area and the dust collected in Tehran. The resemblance in chemical compositions of the elements sampled from mine surfaces and those collected with the MDCO sediment trap suggested that a significant portion of silicon dioxide (SiO2) found in the chemical compositions of dust in Tehran was likely sourced from the sand and sand mines of Tehran. This was because all dust-carrying streams passed over these mines, indicating the potential role of these mines in the elemental composition and deposition of dust in Tehran. MODIS images indicated the formation of dust condensation cores on the surfaces of Hoze Soltan and Mighan lakes, which had the potential to intensify dust flows. A comparison of the average compositions of Hoze Soltan, Mighan, and Tehran lakes revealed the presence of potassium and sodium compounds, as well as chlorine, similar to the samples from these lakes, suggesting that some of the elements of sodium, chlorine, and potassium entering Tehran might have been collected while passing through the fine-grained and separated lands around these lakes. Furthermore, the observations related to the geochemical sediment compositions of samples collected in Tehran using sediment traps compared to those collected in Qazvin Plain showed the significant presence of chlorine, potassium, and silicon among the elements. Discussion of Results & Conclusion The research findings revealed that the sources influencing the alterations in the trajectory of micro-storms demonstrated spatial adaptation to playas, wetlands, and end basins in general. In essence, there were discernible changes in the frequency of dust entry patterns in Tehran and these changes could not be solely attributed to their connection with the input sources. Instead, it appeared that the micro-particle movement system was striving to establish a more deeply organized structure independent of changes in its origin and destination. Rather, the entry of fine particles into this movement system had undergone modifications during their transit within the system. Consequently, alterations were being introduced to the initial conditions within the system governing dust entry into Tehran from its feeding sources. Although the dimensions of these sources were relatively small compared to the original source, they could significantly impact the trajectory of fine particles. Laboratory studies on the samples from Tehran's sediment traps, as well as sand mines, Alikhan Dam, Hoze Soltan and Mighan lakes, and the desert lands around Qazvin Plain, underscored their role in contributing to fine dust in Tehran.

https://gep.ui.ac.ir/article_28060_3c0c23ad4677c1ebcdee2ccafd92ac7e.pdf