Showing 7 results for Gandomkar
Ms Asieh Asgari Dastnaei, Dr Amir Gandomkar, Dr Morteza Khodagholi,
Volume 0, Issue 0 (3-1921)
Abstract
Teleconnection patterns represent large changes that occur in the pattern of atmospheric waves and tornadoes and affect temperature patterns in large areas and are also used to predict average weather conditions over time periods, usually several months or annually. In this study, the effects of 26 Teleconnection patterns with the average monthly maximum temperature on a quarterly and annual basis were investigated. In this study, 4 synoptic stations of Borujen, Shahrekord, Lordegan and Koohrang in Chaharmahal and Bakhtiari province were analyzed. Data were analyzed using descriptive statistics, correlation and Mann-Kendall test. The results showed that the patterns of PNA, WP, NAO, SOI, TNA, TSA, WHWP, Niño 4, NP, Trend, AO, AAO, AMO, AMM, NTA, CAR and GMLO have a positive relationship with all stations studied and The patterns of EA WR, Niño 3, ONI, MEI V2, Niño 1 + 2, Niño 3.4 and TNI had a negative relationship with all studied stations.
Mr Ebrahim Bairanvand, Dr Amir Gandomkar, Dr Alireza Abbasi, Dr Morteza Khodaghoi,
Volume 0, Issue 0 (3-1921)
Abstract
The occurrence of torrential rains in April 2017 in Lorestan province was a clear example of heavy rains that left very heavy damage to agricultural, urban, transportation and communications infrastructure. The purpose of this study is to investigate and reveal the relationship between the physical structure of clouds producing two waves of heavy rainfall in April 2017 in the Doroud catchment area of Boroujerd. In this regard, the statistical characteristics of two precipitation waves on March 25 and April 1, 2019 were analyzed. The supernatural properties of the clouds producing these two heavy rainfall waves were investigated using the Madis superconductor product, MOD06. 4 Microphysical factors of generating clouds These two waves of heavy rainfall in the Doroud-Borujerd basin, including cloud peak temperature (CTT), cloud peak pressure (CTO), optical cloud thickness (COT) and cloud cover ratio (CF) were analyzed. Statistics of these two waves of heavy rainfall showed that in the first wave of heavy rainfall, ie the wave of March 25, 2019, (5 April 1398) 15% of the total annual rainfall and in the second wave, the wave of April 1, 2019 (April 12, 1398) 20% of the total The total average annual rainfall of the region was recorded in these two days. The results of analyzing the microphysical structure of the generating clouds of these two precipitation waves using the MODSI cloud sensor product data showed that the four microphysical factors of the cloud showed a significant spatial correlation with the recorded precipitation values of these two heavy precipitation waves. The two factors of temperature and pressure of cloud peak, which show a vertical expansion of clouds in the area, showed a significant inverse relationship with the amount of precipitation in the basin, while the two factors of cloud ratio and cloud optical thickness have a direct and significant spatial correlation with values. Recorded rainfall showed. The results of this study showed that in these two events of heavy rainfall, a significant and strong relationship was established between the microphysical structure of the cloud and the amount of rainfall recorded in the region.
Saleh Ghorbani, Elham Nazemi, Amir Gandomkar, Zeynab Talebi,
Volume 0, Issue 0 (3-1921)
Abstract
Recognizing the benefits and advantages of tourism development has created a kind of competition to attract these benefits among cities. To achieve these benefits, urban policymakers have focused on new tools in their planning strategies and taken steps to use new concepts such as branding goals. Such conditions have made the position of destination branding as an influential factor in the development of urban tourism important and vital. Urban branding is a powerful tool in the hands of governments to attract visitors and investors and thus economic growth and prosperity. Of course, it should be noted that establishing an urban brand strategy is not an easy task. The most important problem in relation to tourism and urban branding is the tourism infrastructure and socio-cultural identity of today's cities, which affects tourism destinations. The purpose of this study is to develop the brand of Zanjan city with a focus on tourism destinations. In this regard, using a set of quantitative and qualitative tools and questionnaire and interview tools, an attempt was made to introduce a city brand appropriate to the identity and tradition of Zanjan. Based on this, the urban brand "Zanjan, the pristine city of culture and religion" was selected as the tourism brand of this city, and finally suggestions and policies were presented to promote tourism in Zanjan. The results and achievements of this research lead to providing a sustainable model for the establishment, promotion and protection of the tourism brand of Zanjan city and middle scale cities.
Dr Iran Salehvand, Dr Amir Gandomkar, Dr Ebrahim Fatahi,
Volume 20, Issue 59 (12-2020)
Abstract
Rainfall prediction plays an important role in flood management and flood alert. With rainfall information, it is possible to predict the occurrence of floods in a given area and take the necessary measures. Due to the fact that the three months of January, February and March are most floods and most precipitation is occurring this quarter, this study aimed to investigate the factors affecting precipitation and modeling of this quarter. For precipitation modeling, the monthly rainfall data of the Hamadid and Baranzadeh station in the statistical period (1984-2014) for 30 years as a dependent variable and climatic indexes, large-scale climatic signals including sea surface temperatures and 1000 millimeter temperatures Altitude of 500 milligrams, 200 milligrams of omega and climatic elements have been used as independent variables. Due to the nonlinear behavior of rainfall, artificial neural networks were used for modeling. Factor analysis was used to determine the best architecture for entering the neural network. For prediction of precipitation, the data that showed the most relationship with precipitation was used in four patterns, in January the fourth pattern with entropy error was 045/0, the number of input layers was 91, the best makeup was 15-1, and the correlation coefficient was 94% Was. In February, the third pattern with a correlation coefficient of 97%, entropy error, was 0.36. Percentage, number of input units was 8 units, and the best type of latency layout was 10-1. The precipitation of March with all patterns was high predictive coefficient. The first pattern with entropy error was 0.038, the number of input units was 67, the hidden layer arrangement was 17-1, the correlation coefficient was 98%.
Mr Zahra Sadat Jalali Chimeh, Dr Amir Gandomkar, Dr Morteza Khodagholi, Dr Hossein Battoli,
Volume 21, Issue 62 (9-2021)
Abstract
Agriculture, as one of the most important human economic activities, is closely related to the climatic conditions, and any changes in the climatic conditions can have dramatic changes in agriculture. The main objective of this study is to investigate the spatial changes of the Agro Climatic Feasibility Rosa damascena mill Cultivation in Climate change Condition in northern part of Isfahan province including Kashan, Natanz, Ardestan and Aran Bidgol, under the four carbon dioxide emission pathways (RCPs)of 2050. Two groups of factors involved in agroclimatic feasibility of Rosa damascena mill cultivation including environmental factors (topography, soil) and climatic factors were extracted. Based on these factors, suitable zones of Rosa damascena mill cultivation, were identify using Fuzzy gamma function. In the next step, by simulating the climatic elements of the region in 2050, under the four carbon dioxide emission pathways, the fifth report of the IPCC, replacing the simulated climatic variables of 2050 under the four lines, by re-implementing the fuzzy gamma function, favorable areas of cultivation Rosa damascena mill was identified in each region in each scenario. In the next step, by simulating the climatic elements of the region in 2050, under the four carbon dioxide emission pathways, the fifth report of the IPCC, replacing the simulated climatic variables of 2050 under the four lines, by re-implementing the fuzzy gamma function, favorable areas of cultivation The Rosa damascena mill was identified in each region in each scenario. The results showed that in the base period climate, about 0.33% of the area (9025 km2) has a climate suitable for cultivating Rosa damascena mill and more than 67% of the area of the region has a weak talent. The results of the simulation of the climatic conditions of 2050 under four carbon dioxide emission lines indicate that, under all scenarios, favorable areas for cultivating Rosa damascena mill in the studied area have increased. In the trajectory of 8/8 release, the highest class of agro-colliery was the cultivation of the flowers of Mohammadi gardens
Mrs Shahrbanoo Ghanbari Adivi, Dr Morteza Khodagholi, Dr Amir Gandomkar,
Volume 22, Issue 66 (9-2022)
Abstract
The main purpose of this research is to test the agglium of Hormozgan province for the development and development of aloe vera plant cultivars in the base period and the period of change. In this regard, the influential data in the various stages of the aloe vera plant, including the minimum and maximum temperature and precipitation, as climatic agents and height variables, gradients, direction of gradient, soil, as stable elements in the evaluation of aloe vera cultivation areas were used. The multidimensional decision-making technique in the GIS environment was used using fuzzy gamma function for interruption and eventually identifying appropriate arenas for aloe vera plant. The role of climatic changes in two levels of alteration of B1 and A2 was investigated to evaluate changes in Aloe Vera cultivation agriculum in Hormozan province. The results of the implementation of the Fuzzy Gama integration function in Hormozgan province showed that in the base period, 0.35 of the area of the province has good and excellent culture for this plant. These areas are generally consistent with the lowlands of the southern sections of the southern province and are consistent with the soils with tissue and depth and drainage, namely, the arid soils of Sevil and anti-Seville, while in the northern parts of the province, the supply factor, supply The need for an aloe vera plant, tolerance in the year and nightly, the product performance is very weak and the development of aloe vera farms in these areas is not recommended. In the simulated climatic conditions for 2070 under the 2ndretic scenarios, aloe vera arenas will have relatively significant changes compared to the climate of the base period, so that the most variations related to the A2 scenario, in which poorly functional floors are lacking. And moderate culture capabilities have been exposed to an area of 30 to 40 percent, while the two floors of the agricultiva capability and good culture capabilities, under the same system, will show an increase of 20 to 40 percent.
Ms Akram Alinia, Dr Amir Gandomkar, Dr Alireza Abasi,
Volume 24, Issue 75 (12-2024)
Abstract
The main goal of this research is to analyze the time series trend of fire events in natural areas and reveal the relationship between these fire events and vegetation levels in Lorestan province. In this regard, the data of the fire product of the Madis sensor (MOD14A1) and the vegetation product (MOD13A3) of the Madis sensor were used during the statistical period of 2000-2020. The monthly and annual spatial distribution of fires in Lorestan province was investigated. Cross-information matrix analysis and spatial correlation matrix were used to reveal the relationship between fire occurrences and vegetation. The results showed that more than 70% of the total frequency of fire occurrences in natural resources fields (fires with code 2) in Lorestan province is related to June and then July. In terms of the long-term trend, the 21-year trend of the frequency of fire incidents in the province showed that the frequency of incidents in the natural resources areas of the province has generally increased with an annual slope of 3 incidents. The results of the correlation analysis between the monthly vegetation cover and the annual frequency of fire occurrences showed that the fire occurrences in the province showed a significant correlation with the vegetation cover changes in 4 months of the growing period, i.e. from May to August. Cross-matrix analysis between the spatial distribution of fire occurrence foci and NDVI index, both of which were products of MODIS measurement, indicated that, in general, the highest frequency of fire occurrences in Lorestan province in the period from May to August corresponds to Greenness range was 0.15 to 0.22. This range of vegetation generally corresponded to rainfed lands, weak pastures and low-density forest patches
