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Showing 5 results for fatahi

Zeinab Mokhayeri, Ebrahim Fatahi, Reza Borna,
Volume 0, Issue 0 (3-1921)
Abstract

To conduct this research, first, the data of monthly observations of synoptic and hydrometric precipitation from the National Meteorological Organization and the Ministry of Energy during the 30-year period (2006-2005) were obtained. To examine the prospect of future rainfall changes, the historical data of the period (1976-2005) and the simulated climate data of the period (2050-2021) using two models of CM3), (CSIRO-Mk3.6 from the series) Models (CMIP5) and according to 4 scenarios RCP2.6, RCP4.5, RCP6 and RCP8.5) that are available with a spatial resolution of 0.5 x 0.5 with the BCSD method have been used.Mean-based (MB) strategy has been used to correct the bias in the output of these models. The results of the AOGCM models showed that the CSIRO-Mk3.6 error coefficient was less than the GFDL-CM3 model for simulating precipitation in the case of Large Karun.The average future rainfall (2021-2050) in the whole basin compared to the average observed rainfall during the statistical period of 1976-2005 shows, in both models and scenarios in both basins in terms of amount and area of ​​precipitation is decreasing significantly.Heavy rains in the Greater Karun Basin have been concentrated in all scenarios and models east of the basin. The highest rainfall was in the central foothills. The lowest rainfall is in the southwest and southeast. The final results of the present study are expected to be 83-116 mm. Both models are expected to have the highest rainfall in the Greater Karun Basin, with two scenarios: rcp4.5 and rcp2.6.

 
Zahra Hejazizadeh, Parisa Sadat Ashofteh, Ebrahim Fatahi, Zahra Gholampour,
Volume 15, Issue 38 (4-2015)
Abstract

Abstract

In this study, the predicted monthly temperature and rainfall data from HadCM3 model (base period, ۱۹۷۲-۲۰۰۱) and next period (۲۰۱۱-۲۰۴۰) under A2emission scenario were used to investigate the impacts of climate change on runoff variations in the Kor river basin. HadCM3 model output was downscaled based on a temporal downscaling approach (Change Factor) and spatial downscaling approach (Proportional) for the basin. The time series of monthly temperature and precipitation were produced in future period. The results showed that temperature and rainfall will increase and decrease in the future period relative to the base period, respectively. Then, the calibrated IHACRES model was used to model rainfall-runoff relationships in the Kor river basin. Then, the downscaled monthly temperature and rainfall time series in next period were employed to rainfall-runoff model and the monthly runoff time series were simulated for period ۲۰۱۱- ۲۰۴۰. The comparison of future period runoff relative to observed period showed that the annual runoff in the basin for period ۲۰۱۱-۲۰۴۰ will decrease about ۹٫۴۳% with respect to base period.


Dr Iran Salehvand, Dr Amir Gandomkar, Dr Ebrahim Fatahi,
Volume 20, Issue 59 (1-2021)
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%.
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Ahadollah Fatahi, Afsaneh Ahmadi, Vahid Riahi, Hamid Jalalian,
Volume 22, Issue 64 (4-2022)
Abstract

The diversification of economic activities in rural areas is considered as a strategy where rural households increase their income sources. The villages of Saqez city, despite having high environmental potential and capacity in different sectors, such as agriculture, have a poor livelihood and economic status. Therefore, the present article seeks to answer the following questions: What are the appropriate strategies for diversifying economic activities in the villages of Saqiz? The present study was conducted through descriptive-analytic method. In a survey method, SWOC analysis model and QSPM evaluation matrix, we presented appropriate strategies. To design a strategic model and determine the ranking of factors 20 from experts and also to factor out the factors of 300 villagers in the area. The study sample is selected as sample. The results of the SWOC model show that the existence of an appropriate ecosystem in the region for tourism development, the existence of four climates in the region and the possibility of cultivation in each season, as well as the presence of the leading farmers in the region, are the most important strengths against the weakness of the financial and economic context of many Villagers and traditional exploitation are the most important internal weaknesses for diversifying economic activities in the study area. Also, the results of this model indicate that in the external environment 34 opportunities have been identified, the attention of the authorities to the conversion and complementary industries, the border area and the suitable field for exporting agricultural products to the Iraqi countries, are the most important external opportunities and in contrast to 36 challenges and limitations. The key factors of the migration and exodus of elite educated to Tehran and neighboring provinces, climate change and increasing natural hazards such as floods and droughts are the most important external barriers affecting the diversification of economic activities in the villages of the study area. Also, the results indicate It gives diversification of the activities of the economy The studied villages should be focused on strengths and opportunities.
Dr Elham Mobarak Hassan, Dr Ebrahim Fatahi, Dr Abass Ranjbar Saadat Abadi, Dr Nasim Hossein Hamzeh‎,
Volume 23, Issue 71 (1-2024)
Abstract

The Great Khorasan in northeast Iran has a variety of surface structures and plains and high peaks, but due to its vicinity to the deserts of Afghanistan and Turkmenistan, it is affected by dust all the time, especially in summer. The purpose of this study was to simulate summer dust in this region by RegCM model. For this purpose, during the period 2000 to 2017, three extreme dust events were selected. The satellite image used to confirmed dust mass presence and then the synoptic structure was analyzed. Finally, the simulation results of RegCM 4.6 model were compared with the observational data including the horizontal visibility and aerosol optical depth (AOD) of Aqua satellite. The synoptic analysis showed that during the summer, low thermal pressures form in the southern Afghanistan and high pressure in the north. This structure lead to the development of north and northeast winds with speeds of 12 to 21 m / s and dust emission on the eastern border of Iran and western Afghanistan. Investigation of RegCM accuracy done by visibility, Aquas’s AOD showed that model performance in South Khorasan is better as Razavi Khorasan. The highest correlation coefficients of AOD of model and horizontal visibility were obtained at Khorasan central stations including Gonabad, Ferdows, Nahaband and Ghaen at -0.82, -0.77 and -0.44 respectively. RegCM model performed a better dust simulation in severe dust with a horizontal visibility down to less than 1000 m, high continuity and horizontal extension. Overall, the RegCM model underestimates the AOD value for the Aqua satellite algorithm.


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