Showing 6 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.
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
Mr Ebrahim Bairanvand, Dr Amir Gandomkar, Dr Alireza Abbasi, Dr Morteza Khodaghoi,
Volume 25, Issue 79 (12-2025)
Abstract
The torrential rains that occurred in April 2017 in Lorestan Province exemplified severe precipitation that inflicted substantial damage on agricultural, urban, transportation, and communication infrastructures. This study aims to investigate and elucidate the relationship between the physical structure of clouds responsible for two waves of heavy rainfall in April 2017 within the Doroud catchment area of Boroujerd. In this context, the statistical characteristics of two precipitation events on March 25 and April 1, 2019, were analyzed. The microphysical properties of the clouds generating these two heavy rainfall events were examined utilizing the Madis superconductor product and MOD06. Four microphysical factors contributing to the formation of clouds during these two rainfall waves in the Doroud-Borujerd basin—including cloud top temperature (CTT), cloud top pressure (CTP), optical cloud thickness (OCT), and cloud cover ratio (CFR)—were analyzed. Statistical assessments indicated that the first wave of heavy rainfall, occurring on March 25, 2019 (5 April 1398), accounted for 15% of the total annual rainfall, while the second wave on April 1, 2019 (12 April 1398) contributed 20% of the region's average annual rainfall within these two days. The findings from the analysis of the microphysical structure of the clouds producing these two precipitation waves, based on data from the MODIS cloud sensor product, revealed a significant spatial correlation between the four microphysical factors and the recorded precipitation values of these two heavy rainfall events. Specifically, the cloud top temperature and pressure, indicative of vertical cloud expansion in the area, exhibited a significant inverse relationship with the precipitation amounts in the basin. Conversely, the cloud cover ratio and optical thickness demonstrated a direct and significant spatial correlation with the recorded rainfall values. The results of this study thus establish a significant and robust relationship between the microphysical structure of clouds and the precipitation amounts recorded in the region during these two heavy rainfall events.
