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Kermanshah province, especially Ravansar city is one of the important regions of the country in the agricultural and horticultural sector, most of the time the hail phenomenon causes significant damage to these sectors. One way to reduce this damage is to install an anti-hail system. To achieve this goal, 37 station hail data were clustered and three main clusters were obtained representing hail days; Each of the clusters has been plotted and analyzed in terms of geopotential height of 500 hPa, moisture level of 700, and map of 1000 to 500 hPa of temperature and omega. The results of the study of hail patterns show; A low-altitude system is essential in the Middle East; To direct hot and humid air from the southern offerings to the region; At the same time, it is necessary to have high instability and weak static stability in the atmosphere on the surface of the earth, as well as the presence of sufficient moisture that can provide showers. Hierarchical analysis (AHP) method was used for location in GIS environment and parameters such as (slope, slope direction, temperature, humidity ...) were evaluated. These criteria were classified as operating maps, each separately and were scored according to the degree of priority in establishing the device. The final map shows the location of the system: Parts of the northwest of the region (Mansour Aghaei and Ghori Qaleh) and northeast of the central part of Ravansar and parts of the southwest of the area due to the appropriate geographical conditions and appropriate to them, sufficient temperature and humidity and the direction of the southwest slope, and having Favorable conditions for severe instability followed by hail; Anti-hail system is very important for construction in these areas. In general, about 32.6 square kilometers have relatively favorable conditions and about 3 square kilometers have very favorable conditions for the construction of the system.

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Dust is a phenomenon that has many environmental effects in various parts of human life, including: agriculture, economy, health and so on. The purpose of this study is to investigate and predict the dust phenomenon in Kermanshah. Meteorological data with a resolution of 3 hours in the statistical period (2020-2000) of Kermanshah station was obtained from the Meteorological Organization. First, the dust data were normalized and then using ANN neural network models to predict dust concentration and ANFIS adaptive neural network to debug and predict the time series of dust occurrence in MATLAB software were debugged and predicted. Findings showed that the maximum predicted dust concentration related to the minimum fenugreek point with the highest Pearson correlation with dust was estimated to be 3451.23 μg / m3. Also, the results of time series prediction using ANFIS model showed that the linear bell membership function with grade 3, in the training and testing stages, has the most desirable input function among other membership functions. According to the forecasting models, the highest probability of maximum dust occurrence in the next 20 years in Kermanshah was 94%.

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Using Landsat satellite images taken in 2015/08/10 and also SEBAL and metric methods, surface albedo amounts for various land uses in the northern half of the Ardabil province was estimated. ENVI4.8 and ArcGIS10.3 softwares were also used. To determine the type of usage of different levels, the maximum likelihood algorithm classification method was used with Kappa coefficient of 86.14% and overall accuracy of 92.63%. The results indicated that the water levels with the mean value of 0.93 and 0.414, respectively, had the least amount of albedo in SEBAL and METRIC methods. Also, based on the results obtained from SEBAL and METRIC methods the city albedo is about 0.313 and 0.278 respectively.  These values are the highest levels of albedo among Land use levels. In this study, the amount of albedo in rangelands was determined to be between 0.183 to 0.266 in the SEBAL method and between 0.237 and 0.265 in METRIC method. The amount of albedo was also examined in agricultural (0.240 based on SEBAL method and 0.247 based on METRIC method) and forest lands (0.149 based on SEBAL method and 0.225 based on METRIC method). Finally, according to the results of Albedo values based on SEBAL and METRIC methods, it was concluded that due to the difference in net energy received at different levels, it is possible to estimate the level of albedo levels, which is very effective in estimating evapotranspiration by remote sensing methods.

 

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Today, with the expansion of urbanization and the increase in the population of cities, urban poverty is one of the important problems that it seems necessary to fight. In the 21st century, one of the indicators of urban progress is the issue of low urban poverty (Lemanski and Marx, 2015). In order to analyze and evaluate the indicators of urban poverty in Rasht city in different blocks and to cluster social poverty in this city (very poor, poor, average, wealthy, very wealthy), to analyze social poverty and extract spatial hot spots from Arc software. Gis was used. And the extraction of different areas of the city was calculated from the R software and by the multi-indicator Prometheus decision-making method, where the weight of the indicators was obtained by the ANP method from the raw data of the statistical blocks of Rasht city in the census of 2015. The findings of the research showed that comparatively, the central parts of the city are covered by medium blocks, and in the outer and peripheral parts of the city center, two hot spot areas are observed, which contain very prosperous blocks. Cold spots are also clearly visible on the outer edge of the city and they cover very poor and poor blocks, and except for the hot and cold spots, the city is mostly in the form of mild spots and most of the blocks are in poor condition. They are placed in average social poverty. Also, based on the findings of the research, most of the deprived areas in terms of social poverty in Rasht city are located in the north-west and north-east parts of the city.


 

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The aim of this study was to identify the epicenter and co-occurrence factors of dust storm wave from 1 to 3 November 2017 in Kermanshah. To investigate the synoptic conditions of the causes of this phenomenon, from the European Central Center (ESMWF) mid-term weather forecast data set with a resolution of 0.125 degrees of arc including, geopotential height, omega, sea level pressure, orbital and meridional components, humidity. The Lagrangian method of HYSPLIT model was used to orient the source of dust particles. in this study, dust storm WRF-chem was simulated using a paired numerical weather forecasting model. Finally, through the processing of MODIS satellite images, its scope was determined. Examination of HYSPLIT tracking maps shows that two general paths for dust transfer to the area can be identified. 1- The northwest-southeast route, which passes through dust cores formed in the deserts of Iraq and Syria, transports dust to the western half of Iran. 2- Southwest to west of Iran and Kermanshah, which is the main source of dust on November 2 and 3, The source of the particles is Kuwait, northern Saudi Arabia and part of Iraq. The spatial distribution of the dust interpreted by the MODIS sensor images is consistent with the spatial distribution of the dust concentration simulated by the WRF-chem model.

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