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Nazanin Salimi , Marzban Faramarzi, Dr Mohsen Tavakoli, Dr Hasan Fathizad,
Volume 10, Issue 3 (9-2023)
Volume 10, Issue 3 (9-2023)
Abstract
In recent years, groundwater discharge is more than recharge, resulting in a drop-down in groundwater levels. Rangeland and forest are considered the main recharge areas of groundwater, while the most uses of these resources are done in agricultural areas. The main goal of this research is to use machine learning algorithms including random forest and Shannon's entropy function to model groundwater resources in a semi-arid rangeland in western Iran. Therefore, the layers of slope degree, slope aspect, elevation, distance from the fault, the shape of the slope, distance from the waterway, distance from the road, rainfall, lithology, and land use were prepared. After determining the weight of the parameters using Shannon's entropy function and then determining their classes, the final map of the areas with the potential of groundwater resources was modeled from the combination of the weight of the parameters and their classes. In addition, R 3.5.1 software and the randomForest package were used to run the random forest (RF) model. In this research, k-fold cross-validation was used to validate the models. Moreover, the statistical indices of MAE, RMSE, and R2 were used to evaluate the efficiency of the RF model and Shannon's entropy for finding the potential of underground water resources. The results showed that the RF model with accuracy (RMSE: 3.41, MAE: 2.85, R² = 0.825) has higher accuracy than Shannon's entropy model with accuracy (R² = 0.727, RMSE: 4.36, MAE: 3.34). The findings of the random forest model showed that most of the studied area has medium potential (26954.2 ha) and a very small area (205.61 ha) has no groundwater potential. On the other hand, the results of Shannon's entropy model showed that most of the studied area has medium potential (24633.05 ha) and a very small area (1502.1 ha) has no groundwater potential.
Nabi Mohamadi, Behrouz Sari Saraf, Hashen Rostamzadeh,
Volume 10, Issue 3 (9-2023)
Volume 10, Issue 3 (9-2023)
Abstract
Nowadays, due to global warming, drought and the occurrence of cold periods and heat stress, the study of climatic variables is very important. Therefore, in this research, the long-term forecast of temperature changes in northwest Iran in the base period (1985-2014) and three periods of the near future (2021-2050), the medium future (2051-2080) and the distant future (2100- 2081) was paid. For this purpose, 2 extreme temperature indices including Warm spells duration index (WSDI) and cold spells duration index (CSDI) and Maan-Kendall trend test were used to check the changes. To predict the changes of the profiles in the future period after evaluating 7 general circulation models (GCMs) from the sixth report model series (CMIP6) from two optimal models under three socio-economic forcing scenarios including SSP1-2.6, SSP3-7.0 and SSP5-8.5 was used. The spatial distribution of the trend of changes in the Warm spells duration index (WSDI) in the base period showed that its maximum core is located in the south and southwest of the region, and its amount decreases by moving towards the north and northeast. Spatial changes of the Cold spells duration index (CSDI) are characterized by its maximum cores in the western regions and around Lake Urmia and minimum cores in the central and northern regions of the study area. According to the results, the average Warm spells duration index (WSDI) and of the Cold spells duration index (CSDI) are equal to 5.53 and 3.80 days per year, respectively, and the maximum and minimum Warm spells duration index (WSDI) are 1.8 and 2.7 days, respectively Piranshahr and Parsabad stations and the maximum and minimum and the Cold spells duration index (CSDI) are also 5.7 and 1.32 days corresponding to Zarineh and Marivan stations. Examining the trend of changes also showed that in most stations, the WSDI index has an increasing trend, and this trend has become significant in some stations, but the CSDI index has a decreasing trend and is not significant in any of the stations. The evaluation of different models with different error measurement indices also showed that MRI-ESM2-0 and MPI-ESM1-2-L models have the best performance in simulating temperature extreme in the studied area. The distribution of changes in the future period also showed that the WSDI will increase in most stations and based on all three scenarios, especially the SSP5-8.5 scenario, but the CSDI trend will decrease in most stations and based on the SSP3-7.0 and SSP5-8.5 scenarios will be significant.
Hayedeh Ara, Zahra Gohari, Hadi Memarian,
Volume 10, Issue 3 (9-2023)
Volume 10, Issue 3 (9-2023)
Abstract
Introduction
Desertification is one of the major environmental, socio-economic problems in many countries of the world (Breckle, et.al., 2001). Desertification is actually called land degradation in dry, semi-arid and semi-humid areas, the effects of human activities being one of the most important factors (David and Nicholas, 1994). Sand areas are one of the desert landforms, whose progress and development can threaten infrastructure facilities. The timely and correct identification of the changes in the earth's surface creates a basis for a better understanding of the connections and interactions between humans and natural phenomena for better management of resources. To identify land cover changes, it is possible to use multi-temporal data and quantitative analysis of these data at different times (Lu, et.al., 2004), therefore, one of the accurate management tools that causes the application of management based on current knowledge, these studies Monitoring is done using the mentioned data. The use of satellite data and ground information in such studies has caused many temporal and spatial changes of phenomena to be well depicted, which can be beneficial in better understanding and interaction with the environment and ultimately its sustainable management and development. To obtain and extract basic information, the best tool is to use telemetry technologies, which by using satellite data, in addition to reducing costs, increases accuracy and speed, and its importance is increasing day by day in the direction of sustainable development (Alavi Panah, 1385). Since field studies in the field of spatial changes of sandy areas of this city are difficult and expensive to repeat, facilities such as simulating these areas with expert algorithms and artificial intelligence can be used to investigate and monitor critical areas at regular intervals. Accurate and economically appropriate. Therefore, in this research, with the aim of investigating the effectiveness of these models in the periodic changes of the sandy plains of Ferkhes plain, two algorithms, perceptron neural network and random forest, were chosen, and the reason for choosing these models is the ability to model according to the existing uncertainties, interference Fewer users and insensitivity of the model to how the data is distributed.
Materials and Methods
The progress and development of the sandy areas of the Fern Plain depends on three factors, climatic, environmental and human. Therefore, the input variables to the expert and artificial intelligence models were chosen to cover these three factors. Therefore, factors such as drought, the number of dusty days, as well as vegetation index were entered into the model as dynamic variables, and environmental factors such as soil, elevation and altitude, geology, slope and direction were entered into the model as static variables. The statistical period investigated for the changes of wind erosion zones was considered to be 15 years from 2000 to 2015, based on this time base, qualitatively homogeneous and reconstructed meteorological data and images A satellite was selected and processed in 5-year periods (2000, 2005, 2010 and 2015). Modeling of the changes of sandy areas was done using two algorithms of perceptron neural network and random forest in MATLAB software environment. To choose the best neural network structure, a large number of neural networks with different structures were designed and evaluated. These neural networks were built and implemented by changing adjustable parameters (including transfer function, learning rule, number of middle layer, number of neurons of middle layer, number of patterns). One of the most common types of neural networks is multilayer perceptron (MLP). This network consists of an input layer, one or more hidden layers and an output. MLP can be trained by a back propagation algorithm. Typically, MLP is organized as a set of interconnected layers of input, hidden, and output artificial. The accuracy of these networks was checked by the statistical criteria calculated in the test stage, and finally the network that had the closest result to the reality was selected as the main network. The main active function used in this research is sigmoid, which is a logistic function. Then by comparing the network output and the actual output, the error value is calculated, this error is returned in the form of back propagation (BP) in the network to reset the connecting weights of the nodes (Chang and Liao, 2012). Other evaluation indices MSE, RMSE and R were used as network performance criteria in training and validation. The selection of Fern plain as a study area is due to the high potential of this area in the advancement of sand areas, for this purpose, 8 effective factors in the development of these areas were investigated. These factors were entered into the model in the form of three dynamic indices and five static indices.
Results and Discussion
In evaluating the results of modeling algorithms, dynamic variables in all periods were introduced as the most important factors in the occurrence of wind erosion and the advancement of sand areas. The diagram of the importance of predictor variables is presented in Figure 7. The results show that the vegetation cover index ranks first in all periods, the drought index ranks second in 2000 and 2015, and the dust days index ranks third in these two years. Meanwhile, in 2005 and 2010, the dust index and drought index ranked second and third respectively. Among the static variables used in this research, the height digital model variable was ranked fourth in 2000 and 2010, and in 2005 and 2015, geological and soil variables were important. In almost all studied periods, the direction factor is less important than other factors, which can be removed from the set of variables required for modeling to predict sand areas.
Desertification is one of the major environmental, socio-economic problems in many countries of the world (Breckle, et.al., 2001). Desertification is actually called land degradation in dry, semi-arid and semi-humid areas, the effects of human activities being one of the most important factors (David and Nicholas, 1994). Sand areas are one of the desert landforms, whose progress and development can threaten infrastructure facilities. The timely and correct identification of the changes in the earth's surface creates a basis for a better understanding of the connections and interactions between humans and natural phenomena for better management of resources. To identify land cover changes, it is possible to use multi-temporal data and quantitative analysis of these data at different times (Lu, et.al., 2004), therefore, one of the accurate management tools that causes the application of management based on current knowledge, these studies Monitoring is done using the mentioned data. The use of satellite data and ground information in such studies has caused many temporal and spatial changes of phenomena to be well depicted, which can be beneficial in better understanding and interaction with the environment and ultimately its sustainable management and development. To obtain and extract basic information, the best tool is to use telemetry technologies, which by using satellite data, in addition to reducing costs, increases accuracy and speed, and its importance is increasing day by day in the direction of sustainable development (Alavi Panah, 1385). Since field studies in the field of spatial changes of sandy areas of this city are difficult and expensive to repeat, facilities such as simulating these areas with expert algorithms and artificial intelligence can be used to investigate and monitor critical areas at regular intervals. Accurate and economically appropriate. Therefore, in this research, with the aim of investigating the effectiveness of these models in the periodic changes of the sandy plains of Ferkhes plain, two algorithms, perceptron neural network and random forest, were chosen, and the reason for choosing these models is the ability to model according to the existing uncertainties, interference Fewer users and insensitivity of the model to how the data is distributed.
Materials and Methods
The progress and development of the sandy areas of the Fern Plain depends on three factors, climatic, environmental and human. Therefore, the input variables to the expert and artificial intelligence models were chosen to cover these three factors. Therefore, factors such as drought, the number of dusty days, as well as vegetation index were entered into the model as dynamic variables, and environmental factors such as soil, elevation and altitude, geology, slope and direction were entered into the model as static variables. The statistical period investigated for the changes of wind erosion zones was considered to be 15 years from 2000 to 2015, based on this time base, qualitatively homogeneous and reconstructed meteorological data and images A satellite was selected and processed in 5-year periods (2000, 2005, 2010 and 2015). Modeling of the changes of sandy areas was done using two algorithms of perceptron neural network and random forest in MATLAB software environment. To choose the best neural network structure, a large number of neural networks with different structures were designed and evaluated. These neural networks were built and implemented by changing adjustable parameters (including transfer function, learning rule, number of middle layer, number of neurons of middle layer, number of patterns). One of the most common types of neural networks is multilayer perceptron (MLP). This network consists of an input layer, one or more hidden layers and an output. MLP can be trained by a back propagation algorithm. Typically, MLP is organized as a set of interconnected layers of input, hidden, and output artificial. The accuracy of these networks was checked by the statistical criteria calculated in the test stage, and finally the network that had the closest result to the reality was selected as the main network. The main active function used in this research is sigmoid, which is a logistic function. Then by comparing the network output and the actual output, the error value is calculated, this error is returned in the form of back propagation (BP) in the network to reset the connecting weights of the nodes (Chang and Liao, 2012). Other evaluation indices MSE, RMSE and R were used as network performance criteria in training and validation. The selection of Fern plain as a study area is due to the high potential of this area in the advancement of sand areas, for this purpose, 8 effective factors in the development of these areas were investigated. These factors were entered into the model in the form of three dynamic indices and five static indices.
Results and Discussion
In evaluating the results of modeling algorithms, dynamic variables in all periods were introduced as the most important factors in the occurrence of wind erosion and the advancement of sand areas. The diagram of the importance of predictor variables is presented in Figure 7. The results show that the vegetation cover index ranks first in all periods, the drought index ranks second in 2000 and 2015, and the dust days index ranks third in these two years. Meanwhile, in 2005 and 2010, the dust index and drought index ranked second and third respectively. Among the static variables used in this research, the height digital model variable was ranked fourth in 2000 and 2010, and in 2005 and 2015, geological and soil variables were important. In almost all studied periods, the direction factor is less important than other factors, which can be removed from the set of variables required for modeling to predict sand areas.
Javad Sadidi, Hassan Ahmadi, . Ramin Rezae Shahabi, Amir Pishva, Omid Kheyri, Godratallah Nooraie,
Volume 10, Issue 3 (9-2023)
Volume 10, Issue 3 (9-2023)
Abstract
The pervasiveness of the concept of vulnerability in various dimensions has led to the emergence of the theory of vulnerability in the spatial sciences. According to the theory of vulnerability, in any given space, there is a coefficient of vulnerability, while the levels and amplitude of safety are not evenly distributed on the surface of that space. Residential use is one of the most important and main uses in the urban land use system, and safety management and attention to its defense requirements are very important due to the high population density in large cities. The present study is in the field of assessing the vulnerability of residential uses against external threats with a passive urban defense approach in District 10 of Tehran, which was conducted in the form of spatial studies and by implementing an analytical model in three steps. First, the principles and requirements of passive defense were identified and classified into three groups of structural, demographic and spatial parameters, and using the questionnaire and expert survey tools, the priorities of passive defense principles in relation to residential spaces were determined. Then, based on the network analysis process, the weight of each criterion was determined and the weight of the ANP model was applied to the spatial layers of the region in ArcGIS software. The results of the model showed that in terms of structural indicators, more than 78% of residential units in the region are in the group of structures with high vulnerability and in terms of demographic indicators, in 88% of residential units in case of external threats, the level of vulnerability is high. In terms of spatial indicators, more than 92% of residential spaces are adjacent to several incompatible uses and have the highest vulnerability. In general, the results of overlapping layers showed that more than 86% of residential units in the area are located in vulnerable zones and the vulnerability of residential units in these zones is very high.
Hossein Hataminejad, Alireza Sadeghi,
Volume 10, Issue 3 (9-2023)
Volume 10, Issue 3 (9-2023)
Abstract
Measuring urban resilience can help develop appropriate strategies and policies for cities facing unexpected shocks and their consequences. Since urban resilience is a complex concept and difficult to operationalize, developing a technique or method to actualize this concept is a major milestone in understanding the factors and interactions that help create and maintain resilience. Tehran's metropolis has a high concentration of industries, government organizations, services, and facilities, which makes its management very complicated when a natural disaster occurs. Previous conditions or inherent socio-economic characteristics show that Tehran is not immune from flood forces. In fact, it is important to measure resilience against urban disasters for areas located on rivers in Tehran due to its inherent characteristics and spatial-temporal changes of floods in the region. This research focuses on measuring the resilience of the areas located on the rivers of Tehran. The measurement approach is based on creating a composite index based on six dimensions of social, economic, institutional, infrastructure, social capital, and environmental resilience against floods. This research has been done by developing a mixed multi-criteria decision-making method. The AHP model has been used for prioritizing the selected indicators and the TOPSIS model has been used to rank the areas located on the rivers of Tehran city based on their resilience levels. The results show that region 22 is the most resilient region, while regions 4, 5, and 14 have the lowest resilience levels. The findings of this research can help urban planning organizations such as Tehran Research Planning Center to integrate disaster resilience in urban planning and change from reactive plans to preventive urban adaptive strategies such as risk-sensitive urban land use planning.
Tajdin Karami, Ali Shamaei, Fateme Mohebi,
Volume 10, Issue 4 (12-2023)
Volume 10, Issue 4 (12-2023)
Abstract
Abstract
Ecological resilience is a concept that implies the reversibility of ecological structures and functions against the shocks experienced. The northern zone of Tehran, as the most important ecological support of this city, has undergone many land-use changes in recent decades. The present study has analyzed the role of land-use change in the ecological resilience of green infrastructure (as one of the pillars of ecological structure) in District 1 of Tehran Municipality. This study is an applied one in terms of purpose and is considered a descriptive-analytical one in terms of the method used. In this study Landsat satellite data (1976-2021) were used to detect the changes of interest, and landscape metrics were used to analyze the ecological resilience conditions. Based on the results of this study period, the Number of Patches (NP) has significantly increased and the Class Area (CA) has decreased during the period covered by this study. These changes indicate the fragmentation process and loss of structural cohesion of the green patches. The measurement results for the connectivity metrics (ENN and GYRATE) also showed a small connectivity between the green patches in the area. In addition, the results for CONTAG (Contagion Landscape metrics) measure indicated that, due to low connectivity, the transmission rate is low. Therefore, it can be said that the green infrastructure of the region has lost its structural cohesion in the face of land-use change, and as a result, the expected ecological functions and services have also failed. According to the results, the green infrastructure of the study area is vulnerable to land-use changes and their ecological resilience has been significantly reduced.
Dr. Habibollah Fasihi, Dr. Taher Parizadi,
Volume 10, Issue 4 (12-2023)
Volume 10, Issue 4 (12-2023)
Abstract
Urban planners consider historical fabric as the beating heart of cities. However, cities and specifically their historical fabrics are constantly under influence of natural and human-induced hazards. This study aimed to assess the vulnerability of Ferdowsi neighborhood as an example of Tehran’s historical fabric. The data was obtained from geographical information system (GIS) files and a survey, as well as historical contexts and documents were analyzed as part of this study. Ten municipal experts were also asked to provide a score of 1 to 5 for each of the 29 indicators compared to standard levels. The mean value of these scores was then used to evaluate the role of each parameter in the vulnerability of this neighborhood. Study findings indicate a high potential for the occurrence of natural and human-induced hazards in the study area. The abundance of unstable multistory buildings and derelict electricity and water networks, storage of flammables in warehouses, and lack of sewage network for half of the buildings were the most significant factors contributing to the vulnerability of this ancient fabric. Problems such as insecurity, drug abuse in public spaces, overcrowding and daytime congestion have also led to rapid relocation of neighborhood residents, who subsequently were replaced by commercial activities and warehouses. In conclusion, numerous problems are contributing to the vulnerability of historical fabric of this neighborhood and such problems are highly likely to be applied to other urban historical fabrics in Tehran.
Understanding the mechanism of the atmospheric anomalies governing the summer dust in northeast Iran
Ms. Tahmineh Chehreara, Miss Somayeh Hajivand Paydari,
Volume 10, Issue 4 (12-2023)
Volume 10, Issue 4 (12-2023)
Abstract
Identification of dust centers and, of course, the behavior of this phenomenon in different regions creates one of the problems of the last few decades, which is investigated as a hazard. To this end, statistics from 15 meteorological stations in the northeastern region of Iran, including North Khorasan, Razavi Khorasan, and South Khorasan provinces, were used over a 17-year period (2016-2000). To clarify the mechanisms governing dusty days, the meridional and zonal wind components and geopotential height were obtained by referring to the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR). HYSPLIT model and MODIS AOD values were used to track and identify dust centers. The results showed that during the warm season, due to the establishment of a strong quasi-stationary blocking system in the lower levels of the atmosphere, negative vorticity increased in the maximum air descent area, ultimately leading to the dominance of a northern flow for the region. Anomalies in geopotential height and vorticity were identified, and three dominant abnormal patterns were found in the occurrence of maximum dust storms in the region. An increase in geopotential height of more than 5 to 10 geopotential meters and an increase in negative vorticity are considered major conditions. By examining the tracking model and using satellite data, five main centers that affect over 90% of the region's dust storms were identified, among which Turkmenistan has a significant role with two separate centers and one common center with Uzbekistan in the occurrence of summer dust storms in northeastern Iran.
Gholam Hassan Jafari, Zeinab Karimi,
Volume 10, Issue 4 (12-2023)
Volume 10, Issue 4 (12-2023)
Abstract
Abstract
In geosciences, morphotectonic indicators are used to investigate the effectiveness of land surfaces from neotectonic activities. In this article, the results of morphotectonic indices by tectonic zones of Iran, according to the energy released from the earthquake of 1900-2009 and the position of the basins relative to the types of faults (young seismic faults), Quaternary and pre-Quaternary) were analyzed. For this purpose, 110 years old Iran seismic data was extracted from the geodatabase, and during the programming process in MATLAB, it was converted from point-vector to surface-raster. In addition the results of the evaluation of morphotectonic indices of 142 basins of different zones were used; 8 inactive basins, 40 semi- active basins, and 94 active basins. Inactive basins are located in Alborz, Zagros, and Central Iran. . The results indicate that the amount of energy released can't examine a significant role in evaluating the morphotectonic indices of the basins. Basin’s location in the area of Quaternary faults and young seismic is of great value in the tectonically active basin. The lie of semi-active basins adjacent to active basins, or the lie of inactive basins adjacent to semi-active and active basins; and it should be borne in mind that the thresholds used to estimate the tectonic activity status of basins cannot be used as a definite and mathematical criterion in estimating the tectonic status of basins.
Mrs Mozhgan Shahriyari, Dr Mostafa Karampoor, Dr Hoshang Ghaemi, Dr Dariush Yarahmadi, Dr Mohammad Moradi,
Volume 11, Issue 1 (5-2024)
Volume 11, Issue 1 (5-2024)
Abstract
Flash floods are one of the most dangerous natural events and often cause loss of life and damage to infrastructure and the environment. This research investigated the occurrence of the most intense continuous monthly floods (October-March) from 1989 to 2021. Precipitation data from 115 synoptic stations were selected. Then, the total rainfall of 1 to 9 days was sorted according to intensity. Using Minitab statistical software and the Andersen-Darling index, heavy rains were extracted based on the 95th percentile. Then, based on the criteria of the highest and lowest number of rainy days, the highest and lowest accumulated rainfall, the wettest and driest months were determined. Considering the three criteria of intensity, continuity, and rainfall coverage, the strongest storms in the wettest months were selected. The data used for synoptic analysis include the average sea level pressure data, the height and vertical component of the wind at 500 hPa, the wind and humidity field specific to the pressure levels 925, 850, and 700 hPa, and the horizontal moisture flux values specific to the pressure level 925, 850 and 700 hPa. The probability of the occurrence of atmospheric rivers was identified by the moisture flux extracted from the specific, meridional, and meridional wind components. The results showed that the storms of October 27-31, 2015, November 5-7, 1994, December 12-16, 1991, January 11-15, 2004, February 3-9, 1993, and March 13-15, 1996 were the strongest in the wettest months. During the storms of October, November, February, and March, moisture has been transported from the southwest of the Red Sea by atmospheric rivers to the western, southwestern, southern, and southeastern regions of Iran.
Mousa Kamanroudi Kojouri, Habibolah Fashi, Sgahla Barati Sadeh,
Volume 11, Issue 2 (8-2024)
Volume 11, Issue 2 (8-2024)
Abstract
Developing roads and constructing new highway are urban policices contributing to solve transportation problems in cities. These projects often being passed through urban fabrics, so it is nessessery to buy and demolish buildings from their owners including individuals or governmental and public institutions to imply the projects. However, acquiring land is not an easy task and completing these projects may hit with long-term delays. This paper aimed to analyze the impacts of delaying in constructing Shoosh Highway in Tehran. The investigated impacts originate from land acquisition problems. The research data was obtained from many sources including documents and research reports, a survey, and interviews with Tehran Municipality managers. The One Sample T-Test in SPSS software was performed to analyze the data obtained form the survey. Findings indicate that the residents are often dissatisfied with the project because since the beginning of the project, social security decreased a lot and people are less likely to respect citizens' rights than before, recreational sites are often demolished, the value of residential buildings slowed down significantly, living costs incresed, and businesses were stagnant. In conclusion, if urban highways are not contributing to proper planning and site selection, they will disrupt the physical, social, and economic structures of urban neighborhoods and cause to many environmental problemes including air pollution. To avoid these adverse outcomes, it should be thought in advance about sufficient financial resources and possible practical methods to acquire land for projects. These consequences are reduced by studying and managing the risk of projects.
Kaveh Mohammadpour, , Gona Ahmadi,
Volume 11, Issue 2 (8-2024)
Volume 11, Issue 2 (8-2024)
Abstract
Abstract
Dust storm is a complex process that it was affected by relation between earth-atmophere system and point of veiw climatologist and meteorologist that they assessing atmospheric and climatic change, in general of world veiw, monitoring from dust cover is a need structures.
The western region of Iran is the study area. The data used in this study are divided into two categories: ground-based observations in 27 synoptic stations extracted from the Iran’s Meteorological Organization during period (1998-2010) and satellite MODIS images during the first to fourth days of July 2008. Finally, the aim has analyzed using Arc GIS and ENVI softwares and NDDI index.
According to results, interpolated map for the number of dusty days during the study period over the western half of Iran showed that extent of case study have not a equal system aspect quantity of occuring from dust phenomenon and how is it trend. The number of dust days increase from north toward south and sites located in northen proprotion of studied area have experienced a lower dust events. While, maximum hotspots are occuring over southwestern sites such as: Ahvaz, Ilam, Boushehr and Shiraz. Therefore, principle offspring of dust input has been out of country boundaries and arrived far way area. On based resultes obtined on satellite images using NDDI index also idicate that maximun of intense cover dust is observed over Fars, Ilam, Boushehr and Ahvaz provinces on the first, second, thrid and forth of July. But, the lowest rate of index situated in extent far such as: Eastern Azarbayjan, Western Azarbayjan provinces. Thus, parts located on the north of the study area experienced less dusty days and the maximum dust core was located in the southwestern (mostly ahvaz). The long-term result was consistent with the use of NDDI index and the daily average of NDDI index in the whole study area indicated the hotspot areas (Ilam, Ahvaz, Omidieh, Bushehr and Shiraz) during the first to fourth days July 2008. However, in the region has reduced the level of dust cover when a wet and cloudy synoptic system pass over the central and northwestern parts of the study area.
Ms Vahideh Sayad, Doctor Bohloul Alijani, Doctor Zahra Hejazizadeh,
Volume 11, Issue 2 (8-2024)
Volume 11, Issue 2 (8-2024)
Abstract
Iran is a country with low rainfall and high-intensity rainfall that is affected by various synoptic systems, the most important of these systems is Sudan low pressure, Therefore, recognizing the low pressures of the Sudan region is of particular importance, The purpose of this study is to gather a complete and comprehensive knowledge of the set of studies conducted about this low pressure, structure and formation and its effects on the surrounding climate. The present study was conducted using the library method and a search for authoritative scientific and research sources in connection with research on low pressure in Sudan and no data processing was performed in it. Thus, it has studied and analyzed the temporal and spatial changes of Sudan's low pressure over several years and its effect on the climate of the surrounding areas, especially Iran. In general, the results of this study can be divided into several categories, including studies on the recognition and study of Sudan low pressure, its structure and formation over time, pressure patterns affecting it at different atmospheric levels, and its effects on the climate of surrounding areas, especially Iran. Has been studied, The effect of this low pressure on seasonal and spring rainfall in Iran, snow and hail, floods, thunderstorms and also the effect of remote connection patterns on this low-pressure system have been studied, and finally, the analysis of these findings has been studied. It can be concluded that the Sudanese low-pressure system is a Low-pressure reverse in the region of Northeast Africa and southwest of the Middle East, which is strengthened and displaced in the upper levels of the Mediterranean and Subtropical jet stream and in the lower surface moisture injection from the Arabian Sea and Oman through high pressure. Saudi Arabia is inwardly the cause of severe instability in Iran and a major cause of heavy rainfall in various parts of the country.
Dr. Hadi Darroudi, Dr. Mohammad Khosroshahi, Masoumeh Shahabi,
Volume 11, Issue 3 (12-2024)
Volume 11, Issue 3 (12-2024)
Abstract
Dust storms affect different regions of the globe countries and Iran. The dust storm events were considered as one of the climatic components in arid and semi-arid regions and it is called one of the most important environmental problems of these regions. Therefore, in this research, the activity class of sand dunes were investigated based on the Lancaster index in Iranshahr city in Sistan and Baluchistan province. The aim of this study is to investigate the climatic different conditions on the mobility of sand dunes in Iranshahr city. Meteorological data for synoptic station of Iranshahr were collected from the Iranian Meteorological Organization for 15 years (2003 to 2018). After examining the wind speed velocity in Iranshahr, and extracting the seasonal and annual Wind rose diagrams, Dust Storm Index (DSI) was calculated. Finally, the effects of possible changes in climatic elements on the mobility of sand dunes were predicted. The results showed a significant correlation between the Lancaster index and the amount of annual rainfall, wind and drought index. The results of the sensitivity analysis also showed that if the frequency of erosive winds and potential evaporation and transpiration increases to 30%, the activity of sand dunes in Iranshahr station increases by 25 and 23%, respectively, on the other hand, with a 30% increase in rainfall, the activity of sand dunes decreases by 30%.
Omid Ashkriz, Fatemeh Falahati, Amir Garakani,
Volume 11, Issue 3 (12-2024)
Volume 11, Issue 3 (12-2024)
Abstract
The growth of settlements and the increase of human activities in the floodplains, especially the banks of rivers and flood-prone places, have increased the amount of capital caused by this risk. Therefore, it is very important to determine the extent of the watershed in order to increase risk reduction planning, preparedness and response and reopening of this risk. The present study uses the common pattern of the machine and the classification of Sentinel 2 images to produce land cover maps, in order to construct sandy areas and determine land issues affected by the flood of March 2018 in Aqqla city. Also, in order to check and increase the accuracy of the algorithms, three software indices of vegetation cover (NDVI), water areas (MNDWI) and built-up land (NDBI) were used using images. The different sets of setting of each algorithm were evaluated by cross-validation method in order to determine their effect on the accuracy of the results and prevent the optimistic acquisition of spatial correlation from the training and test samples. The results show that the combination of different indices in order to increase the overall accuracy of the algorithms and to produce land cover maps, the forest algorithm is used with an accuracy of 83.08% due to the use of the collection method of higher accuracy and generalizability than compared to. Other algorithms of support vector machine and neural network with accuracy of 79.11% and 75.44% of attention respectively. After determining the most accurate algorithm, the map of flood zones was produced using the forest algorithm in two classes of irrigated and non-irrigated lands, and the overall accuracy of the algorithm in the most optimal models and by combining vegetation indices (MNDWI) was 93.40%. Then, with overlapping maps of land cover and flood plains, the surface of built-up land, agricultural land and green space covered by flood was 4.2008 and 41.0772 square kilometers, respectively.
Spatial and Temporal Analysis of Precipitation Concentration and Its Zonation in Mazandaran Province
Dr. Mohammad Hossein Nasserzadeh, Dr. Ali Reza Karbalaee, A Master's Student Maryam Ghaderi Rastaghi,
Volume 11, Issue 4 (2-2025)
Volume 11, Issue 4 (2-2025)
Abstract
Precipitation concentration denotes the temporal and spatial distribution of precipitation within a watershed, and has a substantial influence on hydrology and water resource management. This study examines the spatial and temporal patterns of precipitation concentrations in Mazandaran Province. Precipitation data from eight meteorological stations covering the period from 2002 to 2021 were used, and the Precipitation Concentration Index (PCI) was employed for data analysis. The findings revealed that the precipitation concentration in this province exhibited significant spatial and temporal variation. The highest PCI values were recorded in the western regions, particularly in Babolsar and Nowshahr, indicating high concentrations of precipitation during specific seasons. Conversely, the eastern region displayed a more uniform precipitation distribution. Seasonal analyses confirmed that spring was the least rainy season and autumn was the wettest. Additionally, Inter-annual variations in PCI indicated an increasing trend at some stations, suggesting a growing concentration of precipitation in recent years. Spatial analysis of PCI patterns also indicated that the southwestern and eastern regions of the province, influenced by topographic factors and distance from the Caspian Sea, experienced relative precipitation concentration during specific months. In contrast, the northern and northwestern regions, which are affected by Mediterranean weather systems and recent climate change, demonstrate an irregular and seasonal distribution of precipitation. The findings of this study underscore the necessity of considering spatial and temporal variations in precipitation concentrations in the management of water resources and hydrological processes in Mazandaran Province. The observed increasing trend in PCI highlights the need to develop adaptive strategies to address the challenges posed by extreme precipitation events and prolonged dry periods.
Mr. Amir Azmoon, Dr. Habibollah Fasihi, Dr. Farzaneh Sasanpour, Dr. Taher Parizadi, Dr. Ali Shamaei,
Volume 11, Issue 4 (2-2025)
Volume 11, Issue 4 (2-2025)
Abstract
Human health depends on living in a healthy environment. Various factors determine environmental health, which should be explored to be able to improve them. The purpose of this research is to analyze the factors affecting the health level of urban environment in district 20 of Tehran municipality and to find out their spatial inequality. This is a descriptive-analytical research based on documentary data of 6 indicators and survey data of 26 indicators. For the analysis, various tools of the GIS, especially the spatial analysis tool of Interpolation, are used. Quantitative analyzes are carried out by calculating statistical parameters in attribute tables. Findings show that the score of 2.29 out of 5 in the evaluation range of 1 to 5, indicates a poor situation of environmental health. Higher weakness belongs to the 6 indicators of the economic dimension including saving, sufficient income for buying cultural goods or going to recreational journeys, and residential home per capita. Access to urban parks and green spaces with scores of 4.55 and 3.43 respectively, show a superiority compared to other indicators. In the outskirts, the environmental health condition is much weaker than in the interior areas. Despite the vastness of worn-out fabric and informal constructions and abandoned spaces, what is more effective are the impacts of external factors, 3 sides of the district are limited to fringe lands, where the establishment of polluting industries, the passage of sewage canals and the replacement of foreign and the population involved in informal and illegal jobs are affected the health level of the urban environment.
Fatemeh Gheysvandi, Jafar Masoompour Samakosh, Firouz Mojarrad, Aminallah Ghahramani,
Volume 12, Issue 1 (8-2025)
Volume 12, Issue 1 (8-2025)
Abstract
The occurrence of persistent rainfall, resulting from the integration of multi-scale cyclonic systems, is prone to producing heavy to severe precipitation. Therefore, it is highly significant due to its potential to cause disasters such as floods and landslides, as well as its importance in water resource management for agricultural purposes. In this study, persistent rainfall refers to rainfall events lasting at least three consecutive days with a total precipitation of more than 1 millimeter. The aim of this research is to identify and classify these types of rainfall for the western region of Iran over a 30-year statistical period (1993 to 2022) for the first time using the Lamb-Jenkinson method. In this method, the central coordinates of the study area are used as the reference point in the calculations. Sixteen additional points are also determined around the reference point. With the availability of instantaneous standard sea-level pressure data for these points, it becomes possible to calculate the values of geostrophic wind and vorticity. By comparing these two quantities, the types of weather patterns in the L-J method—which include four types: directional, cyclonic, hybrid, and undefined—are identified and categorized. Disregarding the undefined category, it was ultimately determined that the provinces of Kermanshah, Kurdistan, Hamedan, Lorestan, and Ilam each had 50, 50, 50, 40, and 39 occurrences of the directional state, respectively. Moreover, the frequencies of the cyclonic state for these provinces were 69, 94, 65, 66, and 38, respectively, with cyclonic rotation percentages of 100%, 98%, 97%, 95%, and 97%, respectively. As for the hybrid state, the frequencies obtained for each province were 49, 53, 43, 41, and 38, respectively.
Mehranjani Mohammad Soleimani, Tahereh Nemati, Tajeddin Karami, Ahmad Zanganeh, Taher Parizadi,
Volume 12, Issue 1 (8-2025)
Volume 12, Issue 1 (8-2025)
Abstract
Aging is one of the most prominent indicators of demographic decline that most modern societies experience. At this stage of demographic decline, alongside a decrease and stabilization of mortality rates, birth rates also sharply decline. The development of technology and the mechanization of tasks, the improvement of quality of life and health-related indicators, individual-centered lifestyles, and increased economic inflation are significant factors in this issue. Iran is also among the countries on the verge of entering the stage of demographic decline. However, the intensity of this trend varies in different regions of the country. This article examines and analyzes the state of aging in the neighborhoods of the metropolis of Tehran. This research falls into the category of applied research in terms of purpose and is descriptive-analytical in terms of method. The research is based on the census data from 2016 and utilizes spatial statistical analyses. The positive values of Moran's autocorrelation analysis for each of the indices: aging (0.664), old-age dependency ratio (0.644), youth ratio (0.653), aging ratio (0.664), and aging index (0.665) in the neighborhoods of Tehran indicate a clustered pattern. This means that the issue of aging is more acute in some neighborhoods and areas of Tehran. Accordingly, the density of the elderly population is higher in most neighborhoods of the central and northern parts of the city. The final result shows that the distribution of the elderly space follows the logic of the social macro-ecology of Tehran and is relatively consistent with its natural-social topography. Furthermore, the spatial analysis of aging in the neighborhoods of this city shows that although all neighborhoods generally grapple with the issue of aging, planning and management should be based on the patterns and nature of the spatial distribution of this issue.
Enayat Asdalahi, Mehry Akbary, Zahra Hejazizadeh,
Volume 12, Issue 46 (9-2025)
Volume 12, Issue 46 (9-2025)
Abstract
Objective: The main goal of this research is to identify and analyze the seasonality of the most widespread Torrential rains in Iran during the years 1940 to 2023.
Methods: To achieve this goal, precipitation data was obtained from the ECMWF database with a spatial resolution of 0.25 by 0.25 degrees of arc for the Iranian region during the study period. The next step was to calculate the threshold of torrential precipitation for each cell seasonally using the 95th percentile, and days with torrential precipitation were identified. By applying the condition of the highest spatial spread of the 95th percentile, the days with the most widespread precipitation above the threshold were identified for each season. Finally, the prevailing atmospheric conditions were examined.
Results: Analysis shows that the highest precipitation of 146.85 mm occurs in winter and the lowest of 85 mm occurs in summer. The highest spatial coverage of total precipitation occurs in spring (41.9), winter (40.69), autumn (32.55) and summer (16.84), respectively.The analysis of sea level pressure indicates that during widespread precipitation in the summer, a low-pressure belt extended from the westernmost to the easternmost regions of the upper atmosphere map, encompassing Iran. In contrast, during other seasons, a high-pressure belt was present in the same area. At the 500 hectopascal level in summer, a closed high-pressure dynamic cell was observed over Iran, while at the 850 hectopascal level, two low-pressure centers over Saudi Arabia and Pakistan intensified instability over Iran. Consequently, it is evident that at lower levels, the conditions for atmospheric precipitation were stable, and even the omega level at 500 hectopascals over Iran on that day indicated a weak upward movement of air. However, in other seasons, a trough consistently positioned over western Iran, with active band patterns in spring and winter, facilitated the slowing and diversion of currents toward moisture sources, thereby enabling the transfer of more moisture than normal conditions to Iran. The precipitation study revealed that, except for the summer season, wind dominated over Iran. The presence of wind intensified instability at lower levels. A study of the Atmospheric River reveals that during widespread rainfall across all seasons, the Atmospheric River, which originates from the Red Sea and the Persian Gulf, has consistently been present. However, in the fall and winter seasons, a branch from the Mediterranean Sea also contributes, resulting in increased rainfall.
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