وحید صفریان زنگیر

In the current research, based on the data of the satellite images of the MODIS sensor, located on the Terra and Aqua satellites and the GRACE gravimetric satellite, with the innovative approach of algorithm and coding in the web system of Google Earth Engine in the cities of the provinces (Golestan, Mazandaran and Gilan) and within the interval of years 2001 to 2022; Estimation and analysis of changes trend in snow surface area, snow depth, snow equivalent water and groundwater aquifer changes in the studied area were done. According to the obtained results, the highest surface area of snowfall with a value of 9496.01 Km2 occurred in 2005 and the lowest with a value of 2906.21 Km2 in 2010, while the maximum amount of snow depth with a value of 0.07 meters in 2008 and the highest water equivalent of snow was obtained with a value of 10 kg/m2 in 2008, and this shows the high correlation between snow depth and water equivalent of snow. The results of the investigation of the groundwater aquifer based on the three CSR, GFZ and JPL models in the studied years showed that the maximum volume of the groundwater aquifer with a value of 12.5 cm was in 2005 and the lowest with a value of -27.5 cm is in 2017. The findings of the research show the decreasing trend of the groundwater aquifer in 2017 with the value of -12.5 cm in connection with the decreasing trend of snow cover in 2017 with the amount of snow cover of 5432.56 Km2 in the study area. Based on the results obtained from the present research, it can be concluded that the process of snow cover changes had an effect on the volume of the groundwater aquifer in the studied area.

Introduction :

In the past fifty years, population and urbanization have led to Uninterrupted urban growth and expansion. In other words, it can be said that the urban population has increased. Still, the existing urban services have not been able to respond to the diverse needs of the people due to inadequate distribution and insufficient access. Therefore, the rapid growth of cities has exceeded the capacity of organizations and city managers to provide infrastructure and public services to citizens. Dispersion and proportional distribution of urban service use are some of the most important considerations in urban land use planning. There is a possibility of creating social crises and spatial problems due to the uneven distribution of urban service users. Inadequate spatial distribution of urban service cables requires more movement over longer distances to use the services provided by them, Which leads to additional costs, time wastage, increased crowding, traffic, air pollution, and insufficient access to services. For some, it also includes families. On the contrary, the proper distribution of urban services provides the possibility of optimal access to service uses and not only plays a significant role in improving the health, security, and peace of society but also acts as an important indicator in the direction of achieving social well-being. It can be inferred that optimal access and proper distribution of urban service users in all urban areas means providing the right services at the right time and place. In this regard, the measured action of urban management in the spatial distribution of urban service uses is necessary to improve the physical quality of the environment so that the quality of life of the people can improve and urban sustainability be achieved. For this purpose, it is very important to understand and analyze the current situation of the spatial distribution of urban services in which the pursuit of proper distribution and easy access to the services of these uses requires the allocation of resources with the most favorable combination. Ardabil City has seen rapid population and physical growth in recent decades. However, the distribution of different uses of urban services does not correspond to the growth and expansion of the population and the physical structure of the city. This imbalance in the distribution of urban service centers can not only lead to the promotion of intra-city travel and aggravation of pollution but also disrupt the population balance and expand urban spaces in conflict with social and economic dimensions. Therefore, by examining the distribution and access to the uses of urban services, it is possible to identify their spatial pattern in different urban areas. This, in turn, can lead to providing solutions that improve residents’ access to such uses and increase their quality of life. Laundry and dry-cleaning jobs, especially the subject of study in this research, are among the types of activities and services that operate in the category of special service trade unions in cities, and in a way, they respond to the needs of the majority of citizens for the services of these units. The current research focuses on laundry and dry-cleaning jobs as a specific example of service sectors in cities and it has analyzed the spatial distribution of these jobs in Ardabil city by relying on some spatial analysis capabilities in the ArcGIS environment. In this regard, the main question of the research is as follows: What is the state of accessibility and spatial distribution of laundry and dry-cleaning units in the neighborhoods of Ardabil city?

In terms of the type of research, the current research is applied-developmental and its method is descriptive-analytical based on graphic methods. The method of collecting information is library (documents) and field. In this way, first by using the library method; The introduction, background, and theoretical foundations of the research were compiled. Also, using the field survey method (GPS), the exact locations of laundry and dry-cleaning units in the neighborhoods of Ardabil city were identified and their coordinates were recorded. After correcting the errors and accurately coding the collected locations in the Google Earth software environment, the final data was entered into the ArcGIS software to form a geographic information database to be analyzed in this software environment. To analyze the information, spatial analysis models and spatial statistics in the ArcGIS environment such as spatial autocorrelation analysis and hot spot analysis were used.

In the current research, the accessibility and spatial distribution of urban services (in this research, laundry, and dry cleaning units) were investigated at the level of the neighborhoods of Ardabil city, and the obtained results showed that in terms of the weight of the abundance of the investigated units at the level of the neighborhoods of Ardabil city, Neighborhoods No. 1-10, 2-8, 3-5 and 4-4 each with 5 units with the highest frequency and neighborhoods 2-9, 3-2, 3-10, 4-1, 4-2, 4-5, 4-6 and 4-10 without any laundry and dry cleaning units are placed in the last classification in terms of the frequency of the mentioned units. The status of the number of laundry and dry-cleaning units by the neighborhoods of Ardabil Municipality and based on the ratio of the number of units investigated per 10 thousand people showed that in the neighborhoods 3-4, 3-3, and 4-4 per 10 thousand population. 4/58 laundry and dry cleaning units and in the neighborhoods 3-2, 3-10, 4-1, 4-2, 4-5, 4-6, and 4-10 per 10 thousand people, absolutely no laundry units and There is no laundry. The condition of the rest of the neighborhoods is in the range of these values. Also, based on the analysis of hot spots in the neighborhoods of Ardabil municipality, neighborhoods 1-7, 1-9, 1-10, 2-4, 2-6, 2-8, 2-10, 3-4, 3-5 and 4- 4 have the highest Z value and have a hotter situation in terms of access to the studied units. On the other hand, the neighborhoods 2-9, 3-2, 3-10, 4-1, 4-2, 4-5, 4-6, and 4-10 have the lowest Z value, so without any value Hot and cold spots are located among the urban neighborhoods of Ardabil. Finally, the result of the spatial autocorrelation analysis of the mentioned units based on the neighborhoods of Ardabil Municipality with Z:1/55 showed that their distribution is classified as a random pattern.

Urban planning requires the allocation and distribution of scarce resources among different areas of the city and relies on criteria such as social welfare. Otherwise, it can lead to more access in certain areas of the city to urban resources compared to other places. The basis of the distribution of urban services should take into account access and spatial distribution within the city. Considering the importance of the subject, the present research has investigated the accessibility and spatial distribution of laundry and dry cleaning units in the neighborhoods of Ardabil city. The results of the research showed that according to the type of urban fabric of Ardabil, the structural form of these fabrics has a significant effect on residents’ access to service facilities (in this research, laundry, and dry-cleaning units) and their spatial distribution in the city. The spatial distribution of the aforementioned service units in the neighborhoods of Ardabil city is more than that of the peripheral neighborhoods. The findings of this study are consistent with the research of Lee et al. who state that the structure of the urban fabric affects the residents’ access to service facilities and the distribution of services is not consistent with the distribution of the population. In addition, the results of Fatemi’s research showed; that Region 4 of Ardabil, which is considered as one of the peripheral areas, has a high dispersion of bakery units, which contradicts the findings of the above research. Also, the findings of the spatial distribution of laundry and dry-cleaning units in the neighborhoods of Ardabil show a random and inappropriate pattern, which indicates the concentration of these units in one or more specific neighborhoods of the city. This model leads to more access of some neighborhoods and their residents to relevant services, which helps to form inequality in the distribution of urban services in Ardabil. In this regard, the results of the above research are in line with the results of the research of Naimi and Babai Aghdam, which shows the inappropriate distribution of urban public services in different areas of Sanandaj City. Finally, considering the importance of the issue, it is suggested that a detailed survey of the per capita usage of services such as laundry and dry-cleaning units in the city is done and necessary measures are taken to solve their shortage in the city, and the ability of all residents to access city services is a priority for the managers. Take This means that the distribution of services in the city should be done in such a way that all residents of the city have proper access to city services. To achieve this, it is important to pay attention to urban facilities’ service radius and capacity.

The purpose of this research is to estimate and evaluate the future climate change of Iran using climatic elements (minimum temperature, maximum temperature and precipitation) until the year 2100 in Iran. For this purpose, in the current research, the innovative method and tools of the algorithm and coding and NASA data to evaluate and predict the aforementioned climate elements based on two intermediate scenario (RCP 4.5) and worst-case scenario (RCP 8.5) of the Canadian CanESM2 model from the system Google Earth Engine was used under the web. In order to better analyze, investigate and compare Iran's future climate changes, the studied period of 80 years, was divided into the first 40-year period (2021-2060) and the second 40-year period (2061-2100). The results of the current research based on the intermediate scenario (RCP 4.5) indicate that the minimum and maximum; minimum temperature of the second 40-year period compared to the first 40-year period is 2.69 and 0.62 degrees Celsius, respectively, and the minimum and maximum; maximum temperature The second 40-year period compared to the first 40-year period was 3.37 and 0.91 degrees Celsius respectively; Also, based on the worst-case scenario (RCP 8.5), the minimum and maximum; minimum temperature of the second 40-year period compared to the first 40-year period is 0.54 and 3.32 degrees Celsius, respectively, and the minimum and maximum; maximum temperature of the second 40-year period compared to the period An increasing trend was predicted for the first 40 years of 2.47 and 3.46 degrees Celsius respectively. Based on the results obtained from the present research, in the studied area, the frequency of rainfall decreases in the first 40-year period and increases in the second 40-year period.

One of the most important atmospheric challenges in recent decades in metropolitan areas is air pollution, which is caused by various natural and human factors and has harmful impacts on humans and the environment. Accordingly, investigating air pollution is important and necessary. For estimating the amount of carbon monoxide and nitrogen dioxide, as well as water vapor in the atmosphere in southern and southwestern provinces in 2018-2019, the data of Sentinel-5 satellite images was used. The findings showed the maximum concentration of Co with the value of 0.037 mol/m^2 in April 2019, the maximum concentration of H2O with the value of 3703 mol/m^2 in August 2019 and the maximum concentration of NO2 with the value of 0.000188 mol/m^2 in November 2018. The maximum daily LST value was 324.5 degrees Kelvin in June 2019 and the maximum nighttime LST value was 302.5 degrees Kelvin in June 2019. The maximum thickness of the optical depth of aerosols with a value of 13.79 μg/m^3 at a wavelength (0.47 μm) was in July 2019 and its lowest value with a value of 1.57 μg/m^3 in a wavelength of (55 /0 μm) was in November 2018. The results of temporal and spatial monitoring of CO, NO2, H2O, LST and AOD values give the possibility of a more concrete understanding of spatial and temporal changes of the examined components on a regional macro scale.

The aim of the current research is to study and predict hazardous extreme temperatures in some cities of central Iran, for this purpose the minimum and maximum temperature data of fifteen meteorological stations (Cities: Isfahan, Shahreza, Natanz, Nain, Ardestan, Semnan, Shahroud, Garmsar, Damghan, Yazd, Bafaq, Gariz, Meibod, Qom and Salafchagan) in the study area in the time period (1999 - 2019) using the innovative method of hybrid artificial neural network and ANFIS adaptive neural network models were used. And Finally, Topsis and Saw multi-variable decision-making models were used to prioritize more exposed areas of temperature increase. The results of this study showed that according to ANFIS modelling model for predicting station temperatures, the lowest mean educational error and the average error of validation for the minimum temperature, with a value of 0.010 for the station Yazd and 1.66% for Damghan station. And the lowest mean educational error and the mean error of validation for the maximum temperature curve were obtained for 0.016 for Garmsar station and 9.39% for Shahroud station, respectively. The maximum temperature fringe based on the Topsis model of two stations of Garmsar and Bafgh with a percentage of 1 and 0/96, will be in higher priority with increasing temperature. Based on the Saw model, Garmsar and Salafchegan stations with the highest percentages 1 and 0.98, respectively, were exposed to higher temperatures.

Global warming and temperature rise will have many effects on different sectors, including agriculture, the warming of the earth will increase the rate of evaporation, and consequently the increase in the demand for agricultural products will increase. In this study, in order to monitor the effect of global warming on Mughan Plain wheat, using the LARS-WG model as a relatively inexpensive and accurate instrument for producing climate multi-yearly climate change scenarios On a daily basis, In Ardabil province, Germi Station was selected as the representative of the three stations in the study area due to the data in the appropriate statistical period. In the present study, to monitor the effect of global warming on precipitation fluctuations, as well as in the production and cultivation of wheat crop in Moghan plain, the LARS-WG model and the HADCM3 climate model output under A1B scenario as well as climate data (minimum temperature, maximum temperature, precipitation and Daily Sunshine) The Germys station was used over a 14 year period (2004-2007).The results of the research show that by comparing the monthly mean of these parameters, this result was obtained that at confidence level 1 there is not a significant difference between the simulation data from the model and observational data in the base period and the mean The climatic parameters of the data obtained from the model and the actual data are similar and there is a high correlation between them. Finally, by comparing observational monthly meanings and modeling of climatic elements of precipitation, minimum and maximum temperatures and sunshine were shown using statistical parameters RMSE, MAE, NA and R2 The model (LARS-WG5) is used to accurately simulate daily data in the parameters of the Mughan Plain, Ardebil province. The results of this study showed that the average decrease in yield of irrigated wheat and the decrease of its production in the study area could be due to the decrease of precipitation and the increase of the regional temperature which is due to global warming.

Road accidents is the outcome of driver behavior, road condition, vehicle status, and environmental factors. Therefore, identification and assessment of effective parameters on road accidents can be considered as an appropriate way to reduce the accident events, driving violations and increase the road safety. Determining the effects of meteorological factors on the road accident events has gained more attention in recent years. The The main objective of this study was to investigate the relationship between the number of road accidents and the meteorological variables in the intercity road of Grmi-Ardabil in the Barzand route.

In this regard, the effects of climatic factors (including rainfall amount, the minimum absolute temperature, and the number of frost days) on the frequency of perilous events were analyzed. The data of accident events (in recent 4 years) were obtained from the trooper department of Ardabil Province along with the meteorological parameters of Germi station through a 11-year period. The statistical tests were performed using R programming software through statistical analysis.

The results showed that the majority of accidents were occurred in winter season which is in consistent with the frequency of frost days and also corresponded to the absolute minimum temperature. According to the results, the highest significant positive correlation at (R2= 0.43) was observed between the number of injured people and frost days. In addition, the relationship between the absolute minimum temperature and the number of were identified as significant negative correlation.

As a concluding remark, the poor road conditions caused by climate element can be considered increasing the frequency of accident events. Accordingly, the proper strategies related to behavior change could be considered in setting the rules and regulations to reduce the accidents and the number of injuries.

Tourism is one of the largest and high-yielding economic activity in the world, the development of which requires sufficient knowledge of the issues and economic factors, Social and cultural development in each region. One of the city's tourist areas in Khalkhal in Ardebil province, due to topographical and geological structure, is full of tourist sites in terms of ecotourism.

This research uses SWOT model and descriptive-analytical approach and field studies and libraries whose purpose is to assess the tourism potentials of Khalkhal city in Ardabil province.

Analysis of the above model in this study shows that in the matrix analysis, strengths are 1.61, weaknesses are 1.26, opportunities are equal to 1.77 and the amount of threat is equal to 1.19, tourism potentials of Khalkhal city, in the first priority aggressive strategies are the second priority in planning competitive strategies. For this purpose, first the initial strategies of SO with a value of 3.38 and then the strategies of OW with a value of 3.03 in the SWOT matrix are in the first and second priority, indicating the best strategies in sustainable tourism in Khalkhal region.

According to the results of the present study defensive strategies (WT) with a score of 2.45, conservative strategies (TS) with a score of 2.8, represents the weakest sustainable tourism strategy in the area known Khalkhal.

Today, drought is one of the most important natural hazards that has direct and indirect consequences in different parts of the planet (barqi et al., 2018: 141). Nevertheless, drought is one of the environmental events and an integral part of climate fluctuations. This phenomenon is one of the main characteristics and recurrence of different climates (Hejazizadeh and Javizadeh, 2019: 251 ) The purpose of this study was to analyze the temperature and precipitation data first, then, using ANFIS and RBF model model, a model-comparative model was developed and the new S.M.S drought index was designed. Finally, in order to better visibility of the drought situation for the future, in areas affected by drought in southern regions of Iran were predicted.

In this study, after the 29-year data on temperature and precipitation data for 28 stations in the drought areas of Iran, the data were first analyzed, then normalized and the stations with abnormal data were normalized. After normalizing the temperature and precipitation data, using two new and powerful applied models for modeling and forecasting in climateology, namely ANFIS and RBF neural network models, were modeled. Then, the two models were compared for accurate prediction for the future, and after training three SPI, MCZI, and SET data, they predicted a new drought index called SMS, for the coming years, and Finally, using the TOPSIS multivariate decision making model, the areas most involved with the drought risk phenomenon were prioritized and ArcGIS software delimited the output data.

Drought is a natural hazard, which is evident gradually over the long years due to climate change in its affected areas. Which effects itself on different parts of the living environment of living organisms. One of these areas in Southwest Asia is Iran, which in recent years has shown drought in its regions, especially the southern regions of high intensity. According to the comparisons of ANFIS and RBF neural network models, the two models were able to predict the drought. The results obtained from the training of the ANFIS neural network model were, at best, RMSE values equal to 9.64 and R2 values equal to 0.0681. But the results obtained from the training of the RBF neural network model were, at best, RMSE equal to 1.15 and the R2 value was 0.9961By comparing these two models, it was finally concluded that the performance of the RBF neural network model was better. According to the modeling and the results obtained from the comparison of the models, the accuracy and reliability of the RBF neural network model was confirmed for prediction. The prediction of the RBF neural network model was used. Modeling and predicting droughts in 28 synoptic stations in southern regions of Iran were compared using SMS fuzzy new index and ANFIS, RBF models. The methods used in this study, in most studies, Monitoring, Modeling and Comparison. Among these, studies have been done in Iran: Zeinali and Safarian-zengir (2017) by studying drought monitoring in the Lake Urmia basin using Fuzzy index; Babayan et al. (2018), the monthly forecast of drought in the southwestern basin of the country Using the CFSv.2 model, they confirmed the model's acceptable accuracy. However, with all the comparisons of different models and indices in these researches, the new SMS fuzzy index and two ANFIS and RBF models used in this study, namely, modeling and predicting the natural hazards of drought In the southern regions of Iran, it has an acceptable performance.

The purpose of this study was to model and investigate the possibility of drought prediction in the southern half of Iran. To do this, the fuzzyization of the SMS index, based on the three SPI, MCZI, SET, comparisons and the results of two new simulation models in Climatology, the ANFIS and RBF neural network models, as well as the TOPSIS multivariate decision making model. The results showed that the S.M.S index reflected the three SPI, MCZI, and SET indices. Comparing two models of ANFIS and RBF neural networks, the RBF model is more accurate than the ANFIS model. As a result, for prediction of drought, RBF model was used for future years. The results showed that the S.M.S index reflected the three SPI, MCZI, and SET indices. Comparing two models of ANFIS and RBF neural networks, the RBF model is more accurate than the ANFIS model. As a result, for prediction of drought, RBF model was used for future years. The accuracy of the RBF model at best was RMSE equal to 1.15 and the R2 value was 0.99 The results of the fuzzification of the SMS index showed that the central and western parts of the study areas such as Kerman, Yasuj and Abadan, with the SMS drought percentage (0.99, 0.97 and 0.89), respectively, were higher Exposed to the drought.

The aim of this study was to analyze rainfall drought indices to predict and reduce their negative effects in Ardebil province, which involved a descriptive-analytical study in terms of research type. Data were collected using documentary method. Accordingly, the information of mean rainfall and mean temperature on a monthly basis in synoptic stations of Ardebil, Germi, Parsabad, Meshkinshahr and Khalkhal were received from the Meteorological Organization in Ardebil province for the period (1996-1996). Dip and Dic software were used to analyze the SPI and CZI indices data in each of the 5 synoptic stations of the province. Drought zoning was then performed in two scales of 6 and 12 months, from IDW interpolation, in ArcGIS software. The innovation of the present study was the use of if-then rules in MATLAB software in combining drought indicators in the field of climatology. The results showed that very severe droughts at the 12-month scale were less than at the 6-month scale, and in all 5 stations studied, the number of moderate droughts was more than severe and very severe ones. Also, the highest frequency of drought was observed in Ardebil city and the lowest in Germi station. Similarly, a comparison of the two indicators displayed that their performance did not differ much; but it turned out that the SPI index, could reveal the number of droughts better than the CZI index.

The drought phenomenon is not specific to the region, affecting different parts of the world. One of these areas is Iran in Southwest Asia, suffering from this phenomenon in recent years. The purpose of this study was to model, analyze and predict the drought in Iran. So that, climatic parameters (precipitation, temperature, sunshine, minimum relative humidity and wind speed) were used at 30 stations during 29 years (1990-2018). For modelling the TIBI fuzzy index, at first, four indicators (SET, SPI, SEB, and MCZI) were been fuzzy in MATLAB software. Then the indices were compared and the TOPSIS model was used for prioritizing areas involved drought, followed by employing ANFIS adaptive artificial neural network model for predicting drought. Results showed that the new fuzzy index TIBI for classifying drought reflected four above indicators with high accuracy. Of these five climatic parameters used in this study, the temperature and precipitation exhibited the most impact on the fluctuation of drought severity. The severity of drought was more based on 6-month scale modelling than on 12-month one. The highest rate of drought occurrence was found at the Bandar Abbas station with 24.30% on a 12-month scale, and while the lowest was at the Shahrekord station with 0.36% on a six-month scale. Based on ANFIS model and TIBI fuzzy index, Bandar Abbas, Bushehr and Zahedan stations were more encountered ones to drought due to the TIBI index of 0.62, 0.96 and 0.97 respectively. According to the results in both 6- and 12-month scales, the southern regions of Iran were more severely affected by drought, which requires suitable water management in these areas.

At present, agriculture is one of the most important economic sectors of the country and that it can be said that economic growth is not possible without agricultural growth. Each agricultural product requires specific climatic and environmental conditions. This study was conducted to evaluate the environmental capabilities of East Azarbaijan province for growing sugar beet (ArcGis).

The data have been studied in consist of annual precipitation and raining of growth duration, temperature, evaporation, relative humidity, sunny hours, number days without freezing and hence height, slope, direction and depth of soil. The used of suitable ecological condition of sugar beet cultivation, production information layers and each series of data were valued and classificated that combined by GIS area and analysed with using Multi Criteria Decision Analysis (ranking, rating and analytic hierarchy process).

The results showed that the environmental capability of sugar beet cultivation plays an important role in the province of East Azarbaijan, and the factors affecting the climatic factors play an important role. It should be noted that in the overlapping method, temperature and precipitation factors play the most important role. Particularly, the role of precipitation is the highest.

The final results show the fact that climatic elements and factors
 Together, they play an effective role in the process of assessing the environmental capabilities of sugar beet cultivation. The share of each of the climatic elements and factors during the growing period of the studied crop is not the same. By adapting the effective layers in the sugar beet planting process in GIS environment, it is possible to identify suitable areas for planting this crop.

The limitations and boundaries of agricultural production is dependent on climatic conditions. Weather is one of the most important factors in human activities, especially agriculture. Corn cultivation in the country's food supply is essential.  Kermanshah province, with the potential favorable climate, optimum conditions for corn are cultivated. The aim of this study was to investigate the role of precipitation and temperature in determining the agricultural calendar and to determine suitable areas for planting corn. To do this, climate data from 10 synoptic stations during the period of 20 years (1390-1371) were used. Use, Hoteling test and test observational data were analyzed. According to research, the station is under study, corn crop water demand in the months of June, July, August and September not secure and High temperature areas due to reduced need frequent in the months of May and June and in the lowlands due to a sharp increase in flowering time, seed maintenance and handling problems during the growing season makes this crop. Based on the results of Hotelling test 62 percent of the land area suitable Kermanshah province, 24 percent and 14 percent for maize is unsuitable. And also based on the results of t-test found 47 percent good, 38 percent moderate and 15 percent are unsuitable for corn. As a result, the central area of moderate temperatures for planting, eastern and northern areas of the southern and western areas of the province due to tropical cold and not suitable for maize cultivation.

According to the importance of each criterion in relation to rice cultivation using AHP was valued. With overlay standards associated with methods to study the map of physiographic and climatic needs Lenjan city was prepared for rice cultivation. The results based on AHP shows that about 5 Lenjan city land without limitations, limitations average 44 percent, 26 percent and 25 percent in the low limits with intense limitations and also based on TOPSIS about 19 percent of the land without limitations, limitations average 32 percent, 26 percent and 23 percent with severely limited by low limitations for the cultivation of rice.

Dust in hazardous areas anywhere in the world is hazardous In different parts Life Organisms had. Dust Mineral Aerosols can significantly affect Earth's climate (Zhiyuan et al., 2019: 3). The prevalence of dust storms is devastating to human health and agricultural activities in Central Asia (Tiangang et al., 2019: 16). Dust it plays an important role in socio-economic development, but on the other hand, such supply can have a negative impact on the environment and the environment of the forest (Narayan et al, 2019: 4). According to the above studies, the importance of dust and the resulting hazard, in the case study, it can be admitted that the dust parameter is important for natural hazards. According to the studies, the existing methods for studying the dust that has been done so far have been general and have not adequately addressed the subject. Dust in the areas under its control anywhere in the world has had a dangers in various parts of life. Drought storms have also been growing in recent years (Mohammad Khan, 2017: 495). Drought phenomenon due to recent droughts has caused adverse biological effects and damages in agriculture, industry and transportation in the provinces of Khuzestan and other neighboring districts (Darvishi et al., 2017: 1). Today, dust is one of the common phenomena and is one of the major environmental problems in arid and semi-arid areas (Hejazi Zadeh et al., 2018: 108). The purpose of this study was to analyze the dust data first to address this issue Then, using ANFIS and RBF models, a modeling comparison was used and finally, for a better view of the dust situation for the future, in dusty regions of Iran, they were predicted.

In this study after analyzing 29-year-old dust data for 28 stations of dusty regions of Iran, they were first analyzed and then normalized, and non-normal stations were normalized. After normalizing the dust data using two new and powerful applied models for modeling and forecasting in climateology, the ANFIS and RBF models were modeled. and Then the two models were compared to accurate prediction for the future, and after training the dust data, they were predicted for the coming years. Finally, using the TOPSIS multivariate decision making model, regions are more involved with the priority hazardous dust hazard phenomenon and by utilizing ArcGIS software output data Zoned.RBF neural network model Neural networks with radial base function are widely used for nonparametric multi-dimensional functions through a limited set of educational information. Radial neural networks with a fast and comprehensive learning are very interesting and efficient, and they pay particular attention to it, Hartman et al. (1990). Gyrosy, Pogni, as well as Hartmann and Kepler, in the 1990s proved that radial-base grid networks are very powerful approximation devices, so that by having a sufficient number of hidden neurons, they can be able to approximate each function Continuously and accurately with every degree. These networks are often compared to the neural network back propagation error. The main architecture of the RBF consists of a two-tier network (Khanjani et al., 2016).ANFIS Neural Network Model In this step, it is possible to model and predict dust in the studied area using the ANFIS comparative neuro-fuzzy network model (Ansari, 2010: 29). In this study, the phenomenon of dust in a series of time of 276 months (23 × 12 276) in two ANFIS and RBF neural networks models in each station was considered. In a time series consisting of n examples x_1, 〖x〗 _ (2), ..., x_n is the next value of relation (6) of its previous value (Asghari Oskouei, 2002: 75). (6) x_k=f (〖 x〗_(k-1 ),〖 x〗_(k-2 ),…,x_(k-p ))The fuzzy system is a system based on the "conditional-result" logical rules that, using the concept of linguistic variables and fuzzy decision making process, depicts the space of input variables on the space of the output variables. The combination of fuzzy systems based on logical rules, and artificial neural network methods that enable the extraction of knowledge from numerical data, has led to the introduction of a comparative neural system inference. In Fig. 3, a sogeven fuzzy system with three inputs, one output and two laws and an equivalent ANFIS system were presented. This system has two inputs x and y and one f output.
Proximity to Ideal Mode (TOPSIS) Huang and Yun proposed TOPSIS in 1981. In this method, m options (A1, A2, ..., Am) were evaluated with n indices (C1, C2, ..., Cn) (Momeni, 2008). Solving this problem with this method was carried out in the following steps (Makvandi et al., 1391; Law and Order, 2014).

Comparison of two ANFIS and RBF neural network models According to comparisons of ANFIS and RBF neural network models, the two models were trained to predict dust. The results obtained from the training of the ANFIS neural network model at best, the RMSE value was 11.67 and the R2 value was 0/5879. But the results obtained from the training of the RBF neural network model, at best, were RMSE equal to 2.19 and the R2 value was 0.9854. By comparing these two models, it was finally concluded that the performance of the RBF neural network model was better. According to the modeling and the results obtained from the comparison of the models, the accuracy and reliability of the RBF neural network model was confirmed for prediction, then the prediction of the RBF neural network model was used.

The zoning of dust phenomena in dusty regions of Iran using TOPSIS The results of the implementation of the Topsis model, using the degree of importance of the criteria derived from the entropy method, indicate that, in terms of dust intensity, places more and less dusty for the next 14 years in dusty areas Iran, three stations of Abadan, Masjed Soleyman and Ahvaz were exposed to dust (1, 95%, and 81%), respectively, for simulated years. The northern stations of the study area including Khoy, Boroujen and Ahar showed a lower dust intensity with percentages (0.1, 0.4 and 0.6), respectively. According to TOPSIS model, south west and west of Iran were exposed to dust for simulated years.

In recent years, Iran in Southwest Asia it has been affected by drought. The purpose of the present study is to analyze and forecast drought in Iran. For this research at first, the precipitation and temperature climatic parameters over a 29 year period (1990- 2018) at 30 stations in Iran Collected. For modeling, the M.S.S fuzzy index, at first uses three indices (SET, SPI, MCZI) using fuzzy logic in Matlab software. Then the indicators are compared and compared with Topsis multivariate decision making model, For Prioritization Drought affected areas were used and finally to forecast the RBF artificial neural network model was used. The Research findings showed that the new M.S.S Index drought class fuzzy index reflected the above three indices with high accuracy and the accuracy of the M.S.S model was confirmed with high confidence. In the drought monitoring years, southern and southwestern stations of Iran such as Bandar Abbas and Ahvaz were more prone to drought (24.30 and 18.47%). In the years to forecast, the drought is expected to extend to the central parts of Iran. Including these stations Semnan and Yazd with drought frequency percent (0.86 and 0.91) are based on M.S.S fuzzy index, respectively.

Introduction :

Drought is one of the most important natural disasters affecting agriculture and water resources, and its abundance is extremely high in arid and semi-arid regions (Shamsenya et al., 2008: 165). Drought is a natural phenomenon that has a complex process due to the interactions of various meteorological factors and occurs in all climatic conditions and in all regions of the planet (Samandianfard & Asadi, 2017). According to the domestic and foreign studies, many researchers have conducted research on drought monitoring and prediction, but the research that can show the drought phenomenon more accurately with the future vision is not takenhas not been conducted if both do not cover the issue adequately. According to the researchers, this study was conducted to model, monitor and predict drought with the new method in Iran in this study.

In this study, drought modelling in Iran was carried out using climatic data of rainfall, temperature, sunshine, relative humidity and wind speed monthly (for 6 and 12 months scale) for the period of 29 years (1990-2018). At 30 stations using the new TIBI architecture model, a fuzzy set of four indicators (SET, SPI, SEB, and MCZI) valid in the World Meteorological Organization was used. For modelling the new TIBI index, the climatic data were first normalized, then four indices (SET, SPI, SEB, and MCZI) were calculated separately and the fuzzy modelling of the four indices was performed in the Matlab software and eventually to prioritize the drought-affected areas, the multivariate decision-making model, TOPSIS was used.

In order to investigate the effect of drought fluctuations in drought conditions of stations, it is possible to determine the changes in the indicators (SET, SPI, SEB, and MCZI) in the TIBI index analysis. Considering the large number of stations studied, For better understanding, only the drought series diagrams were presented at Bojnourd station on two 6 and 12 month scales (Figures 7 and 8),, (in the mentioned figures, the red arrow shows the drought margin at a 6-month scale with a value of 0.44 and greater, and a value of 0.76 and greater within the 12-month scale. The analysis of these forms shows that at the 6-year and 12-month scale at Bojnourd station, the amount of evapotranspiration was similar in drought conditions, which decreased from April 1994 to February 1999, and after this month an increase was observed if the impact of rainfall on a 6-month scale is weaker than the 12-month scale. It means that from May 1993 to November 1997, an increasing trend followed by the same pattern, and the indicators (SET, SPI, SEB, and MCZI) affect the TIBI index and show some trends, indicating that the new TIBI fuzzy index reflects the four indicators well. The T.I.B.I index at the 6-month scale shows a sharper shape than the scale 12.Prioritization of the stations involved in drought in Iran was analyzed using the TOPSIS model. The results of the TOPSIS model implementation using the degree of importance of the criteria derived from the entropy method indicate that, in terms of drought, more and fewer places are involved with drought by combining the two 6 and 12-month scale. According to the TOPSIS multivariate decision-making model, it was determined that the three stations most affected by drought based on the TOPSIS model were Bandar Abbas, Ahvaz and Bushehr, respectively, in the south and southwest regions of Iran with priority points of score (1, 0.78, and 0.62 respectively), and the three stations of Gorgan, Shahrekord and Orumieh in the northern and western parts of Iran with the scores of 0.026, 0.033 and 0.035 had lower priorities for drought response, respectively (Table 6) and (Figure 11).

Drought is a natural disaster that is gradually evolving under the influence of climatic anomalies over a long period of time. In recent years, various parts of the Middle East have faced drought, including those regions of Iran in Southwest Asia. In this study, drought phenomenon was assessed at 6 and 12 months using the new fuzzy index T.I.B.I. The results of the research showed that the total frequency of droughts in the 12-month scale was more than 6 months but the severity of a 6-month-old drought is more than 12 months old. On a 12-month scale, the number of drought repetitions is more than 6 months. Drought persistence was higher at 12-month scale, droughts were shorter at short-term and affected by temperature parameter. However, the intensity of drought over a long period of time had a slower response to rainfall changes. The highest percentage of drought incidence in scale of 6 months; Bandar Abbas, Bushehr, Ahvaz and Zahedan stations in the southern half of the study area respectively with the of drought (16.62, 11.24, 14.13 and 62.6 and the lowest in the 6-month scale were Urmia and Ardebil stations, with the percentages of 1.10 and 1.88, Ilam and Yasuj with the drought frequency of 1.61 and 2.01, Rasht and Gorgan, with a high percentage of drought frequency (1.26 and 0.87) in the northern and western part of Iran. The highest percentage of drought occurrence in scale 12; Bandar Abbas and Bushehr stations respectively with drought frequency of 24.30 and 14.83, Ahvaz with drought severity of 18.47, Kerman with 6.74 percent of drought frequencies in the south and southwest of Iran and the lowest in the 6-month scale; stations of Birjand (1.70), Bojnurd (66.6), Urmia (1.17), and Tabriz (66.2) in the northwest of Iran, Rasht (0.58), Sari (0.78) in the northern part of Iran.

 Introduction:

 Drought is one of the natural hazards, which during its occurrence has damages and effects of irreparable damage in various sectors of agriculture, economics, and so on. In recent years, different regions of the world have experienced more severe drought (Mirzai et al., 2015: 98). Also, drought is one of the most important natural disasters affecting agriculture and water resources, which is abundant especially in arid and semi-arid regions (Shamsenya et al., 2008: 165).Drought changes are well-suited for optimal management of water resources utilization (Alizadeh, 2017: 169). Drought is also referred to as a climate phenomenon with a lack of humidity and rainfall relative to normal conditions. This phenomenon strongly affects all aspects of human activity (Zeinali and Safarian Zangier, 2017). Regarding the studies done inside and outside of the country, this study attempted to model and monitor the drought phenomenon in southwest of Iran using a new index. 

Material and method:

 In this study, drought modeling in southwest of Iran was carried out using climatic data of rainfall, temperature, sunshine, minimum relative humidity and wind speed monthly (6 and 12 months scale) for the period of 31 years (1987 - 2018) in five provinces of Khuzestan, Lorestan, Ilam, Kermanshah and Hamedan in 15 stations using a new index modeling called the TIBI Architectural Index, fuzzyized from four indices (SET, SPI, SEB, MCZI) The World Meteorological Organization was used. Fuzzy index T.I.B.I The fuzzy index (T.I.B.I) is presented to resolve some of the disadvantages of the SPEI index. The index T.I.B.I was derived from the integration of the indicators (SET, SPI, SEB, MCZI), which is the result of drought fuzzy modeling architecture that is designed using fuzzy logic in a fuzzy inference system. 

Conclusion:

 Monitoring of drought fluctuations based on four integrated indicators in T.I.B.I In order to investigate the effect of drought fluctuations in drought conditions of stations, it is possible to find changes in the parameters (SET, SPI, SEB, MCZI) in the TIBI index, Checked. Considering the large number of stations studied, for the sake of better understanding, only the drought series chart, East Islamabad station at two 6 and 12-month scale was presented in Figures 7 and 8 (Figures 7 and 8). The above-mentioned red dot indicates a 6-month drought margin with a value of 0.44 and more, and represents a 0.44 and a magnitude 12-month scale. The analysis of these forms shows that at Islamabad-West station at 6 and 12-month scale, the temperature was different in the drought environment, which was decreasing in the 6-month scale from April 1994 to August 1997, and after This month has been gaining momentum, from July 1996 through 2003, an incremental increase. If the impact of rainfall on a 12-month scale is weaker than the 6-month scale. Between May 1994 and November 1997, the declining trend followed by a 12-month-long drought after June 1997 to December 2002, followed by a similar pattern. And the indicators (SET, SPI, SEB, MCZI) affect the TIBI index and show some trends, indicating that the new TIBI fuzzy index reflects the four indicators well and the scale Drought classes were presented in Table 5. The T.I.B.I index on a 12-month scale shows a sharper shape than scale 6.

Results:

One of the natural hazards that has affected the country in recent years is the dangers of drought. One of these areas affected by drought was the southeastern part of Iran, where researchers conducted many studies to monitor drought in Southwest Iran with different models but did not adequately address the issue. Is The purpose of this study is to model and monitor the drought phenomenon in southwest of Iran using a new fuzzy index in the 6 and 12-month scale. In the study area, the intensity and frequency of drought are more than 6 months on a 12-month scale. Drought persistence is more than 12 months old. Short-term droughts were less sustained and affected by rainfall and temperature parameters. While the severity of drought in the long periods of time was less responsive to temperature and precipitation variations.The trend of drought in the south-west of Iran was increasing and the temperature trend was more rapid, increasing and increasing trend. The highest frequency of drought occurrence was at the 6th and 12th month scale, Islamabad-West station and the lowest rate was 6 Hamadan airport scale and 12-month scale Khorram Abad station. The percentage of drought frequency in Hamedan Nogheh, Islamabad and Zarapulzahab stations was higher than the 6-month scale in the 12-month scale.

Dust is a phenomenon that has many destructive environmental impacts in different parts of human life, including: agriculture, economics, health and Etc. The country of Iran, especially its western and southwestern regions, is suffering a lot of damage due to its presence in the area affected by the dust phenomenon every year. So pay attention to this issue and reducing the resulting damage, It is a priority. The purpose of this Research is to investigate and predict the dust phenomenon in southwest of Iran. For this Research, 27-year-old dust data were used at 14 synoptic stations in southwest of Iran during the period (1990-2017). In this Research, dust data was first normalized in 14 stations Then, by using the hybrid-panel data model, the ANFIS-compatible neural network in MATLAB software was falsified and predicted. and finally, to prioritize more stations, Dust was exposed to TOPSIS and SAW multivariate decision making models. The findings of the study showed that the reliability of the lira faction models (neural network of the hybrid panel compared to the ANFIS comparative neural network) was higher. Based on prediction models, the maximum probability of occurrence, the maximum dust in the next 23 years in the studied area at two stations, Sarpol Zahab and Abadan are respectively (120.709, 128.917). According to the SAW model, the probability of occurrence of dust in the next 23 years is estimated at Abadan station with 0.99% and Based on the TOPSIS model, Islamabad Gharb station with a value of 0.97%. According to the results of this study, in order to reduce the damage caused by the dust phenomenon in the study area, in addition to domestic measures, such as inter-organizational cooperation, it should be addressed by concluding an international agreement with the neighboring countries.

Drought is one of the natural hazards which can cause an irreparable damage in various sectors of agriculture, economics, and so on. In recent years, different regions of the world have experienced more severe drought (Mirzai et al., 2015). Also, drought is one of the most important natural disasters affecting agriculture and water resources which is abundant especially in arid and semi-arid regions (Shamsenya et al., 2008). Drought changes are well-suited for optimal management of water resources utilization (Alizadeh, 2017). Drought is also referred to as a climate phenomenon with a lack of humidity and rainfall relative to normal conditions. This phenomenon strongly affects all aspects of human activity (Zeinali & Safarian Zangir, 2017). Regarding the studies done inside and outside of the country, this study attempted to model and monitor the drought phenomenon in northwest of Iran using a new index.

In this study, drought modeling in northwest of Iran was carried out using climatic data of rainfall, temperature, sunshine, relative humidity, and wind speed monthly (6 and 12 months scale) for the period of 32 years (1987-2018) in five provinces of Ardebil, East Azarbaijan, West Azarbaijan, Zanjan, and Kordestan in 21 stations using a new index modeling called TIBI architecture, fuzzyized from four indicators (SET, SPI, SEB, MCZI) Valid in World Meteorological Organization. The position of the studied areas are shown in Fig. 1 and the coordinates of the stations are presented in Table (1).

Monitoring of drought fluctuations based on four integrated indicators in T.I.B.I
In order to investigate the effect of drought fluctuations in drought conditions of stations, it is possible to find changes in the parameters (SET, SPI, SEB, & MCZI) within the TIBI index. Considering the large number of stations studied, for the sake of better understanding, only the drought series chart of Tabriz station was presented on two 6-and 12-month scale. (In the above-mentioned Station diagram, the Flash line Red shows a 6-month-old drought margin with a value of 0.44 and more, and a 12-month scale with a value of 0.98 and more). The analysis of these forms shows that at the 6 and 12-month scale of Tabriz station, the amount of evapotranspiration was similar to drought conditions, which decreased from March 1993 to July 1998, while after this month an increase was observed. The impact of rainfall on a 6-month scale is weaker than the 12-month scale. From April 1996 to December 2004, it has grown steadily, and then followed the same pattern. The indicators (SET, SPI, SEB, & MCZI) affect the TIBI index and show some trends indicating that the new TIBI fuzzy index is well reflected in the four indicators. Its drought classes scale was presented in Table 5. The T.I.B.I index on a 12-month scale shows a sharper shape compared to a six-month scale.

In recent years, drought is one of the most important damaging issues in different sectors such as agriculture, economics, etc. In different parts of Iran including Northwest of Iran, Researchers have done a lot of research on drought monitoring. They presented different models but did not adequately cover the subject. The purpose of this study was to model and investigate drought in northwest of Iran during the 6 and 12-month scale. At stations, the intensity of the 12-month scale and the frequency of droughts are more than 6 months. Drought persistence is more than 12 months old. Drought had a lower continuity in the short-run time scale and was influenced by the temperature parameter. The severity of drought in the long periods of time was less responsive to rainfall variations. The trend of drought in the northwest of Iran increased and the temperature trend was mildly increasing. The most frequent occurrence of drought occurred at the 6th and 12th month scale in Orumiyeh station, while the lowest in both the 6 and 12-month scale in Sanandaj station. The percentage of drought frequency in Jolfa, Maku, and Uromieh stations was 12 months higher than the 6-month scale.

Abstract Recognizing the climatic potentias, as a basis for human activities, provides the predominant foundation for environmental and land use plannning. Most of the tourists follow climate considerations to choose the destination. The aim of this study was to evaluate and render the zoning of seasonal tourism at the northwest of Iran using tourism climatic index (T.C.I). In this study, to assess the climatic conditions from the tourism perspective, the climatic data from 22 synoptic stations in the northwest Iran for a period of 20 years (1990-2010) were collected. In this model, a 7-parameter system was used. These parameters included mean maximum temperature, average temperature, average minimum relative humidity, mean relative humidity, total monthly precipitation, sunshine hours and daily average wind speed. The TCI index was used for data analysis and the tourism climate maps were drawn for four seasons using GIS. The results show that the TCI index has a large variety of topography in the northwest because of conflicts over the years. Summer with the conditions as infinite ideal: 7, ideal condition: 10, excellent quality: 3, acceptable: 1 and very good condition: 1 ranked the first among other three seasons. Autumn with the conditions as perfect: 4, very good: 11, good: 3 and acceptable: 4 ranked the second. Spring season with the spesifications as very good: 2, good: 2, acceptable: 11 and insignifcant: 7 ranked. Winter with the conditions as acceptable: 1, insignificant: 14, poor: 5 and very poor: 2 ranked the fourth place and the most unfavorable condition among the other seasons. Discussion and Northwest of Iran with great tourist attraction can be pioneer in local and foreign tourism. Beautiful scenery and unique and varied climate conditions in all seasons can greatly contribute to the development of this industry and lead to great benefits.

Thunderstorms rainfalls are a kind of unstable storms that are caused by an extremely strong abnormal state of atmospheric displacement and are one of the most important climatic phenomena in the northwest of the country.The aim of this study was to determine the spatial distribution of thunderstorms rainfalls in Ardabil province by using satellite images and Estimation of perceptible water. In this study, synoptic stations data, satellite imagery and MODIS bands 17 and 18 for Estimation of perceptible water were used. Images of thunderstorms rainfalls on 05.10.2010 and 18.06.2012 in ENVI4.4 software was processed and then they were interpolated in ArcGIS. Also, the results of interpolated field data revealed that the highest thunderstorms rainfalls are at Khalkhal station and lowest occurs in Meshkinshar station. In addition, thunderstorms rainfalls in the province in the spring and early summer lightning occurs. The results of the analysis of ground data and satellite imagery indicated this fact that the thunderstorms rainfalls derived from satellite imagery is far more accurate than data that obtained from the harvest of the earth. Also, maps of thunderstorms rainfalls can be extracted quickly and accurately, as well as using in the prediction of atmospheric hazards and optimal water resources planning in Ardabil province.

y in Ardabil province analyzed the precipitation data of 30 years from 1987 to 2016. Most of the precipitation occurred on 09/12/1991.Synoptic atmospheric maps of this date at a level of 500 Millibars were prepared by sea level elevation maps, geopotential heights, wind speed and direction, humidity, temperature, perceptible water on ground level and blocking (omega), using satellite images from NCEP/NCAR databases which Affiliating to the National Oceanographic Organization of the United States. The research method is a circular environmental approach. The results showed that in addition to the ground and climate conditions that have been effective in causing heavy rainfall during this history, the internal situation with the external pattern, such as the seas around and adjacent to Iran like the Black Sea and the Mediterranean has been affected. The monthly precipitation of Khalkhal station as a region that is more prevalent in the south of Ardebil province and southwest of the Caspian Sea in the three months of the spring season is more than February (1321/8 mm), March (1716.7 mm) and April (1448 mm). The most natural atmospheric hazards affected by heavy rainfall and flood damage in Khalkhal, inland, village, river and agricultural damages occurred during these months.

Introduction Changes, although low in temperature, change the occurrence of extreme phenomena such as droughts, heavy rainfall and storms (Varshavian et al., 2011: 169). Reducing the daily temperature variation has led to a reduction in the frequency of occurrence of temperature minima, especially in winter (Schiffinger et al., 2003, p. 51-41). Material and method The purpose of the present study was to investigate and predict the risk of monthly rainfed temperatures on horticultural and agricultural products in northern Iran. For this purpose, first, the data of the temperature of the whole station were obtained at a time interval of 30 years. Then, using Anfis's adaptive neural network model, data were collected for prediction and prediction for the next 6 years. Then, to measure the land suitability of the northern strip Iran was used for cultivating according to the predicted data using two models of Vikor and Topsis. In recent years, damage to agricultural and horticultural products has been increased due to temperature fluctuations. Accordingly, in this research, the prediction of the risk of monthly rainfed temperatures on horticultural and agricultural products in northern Iran has been investigated. Based on the predicted data, the minimum temperature of the Gorgan station was the lowest educational error with a value of 0.10 and at the maximum temperature, the lowest error was 0.015. Finally, in Golestan province, the maximum temperature And at least both are weak in the incremental state. Minimum and maximum temperature of Bandar Anzali station was the lowest educational error with the value (0.013, 0.10). In Gilan province, the maximum temperature peaks and at least both are in incremental conditions and the maximum temperature has a higher intensity. Be The minimum temperature of the Babolsar station was the lowest educational error with the value of 0.019 and at Ramsar maximum temperature, the lowest error was 0.016, and Mazandaran province exhibited maximum and minimum temperatures at both incremental and minimum levels Temperature showed greater intensity. According to the findings of the study, with respect to the friction frain modeling, the maximum temperature showed the lowest defect compared to the minimum temperature. In Golestan province, the maximum temperature peaks and at least both are in weak increment, but in Gilan province, the maximum temperature peaks and at least both the maximum and maximum temperatures are higher. Mazandaran province showed maximum temperature and minimum temperature in both incremental and minimum temperature conditions.

The extent of the human need for energy resources has always been the basic issues important in human lifeand strive to achieve an inexhaustible source of energy has been mankind's oldest dreams.Increased use of fossil fuels and the increasing need to be intensified with the increase in population, and have alternative energy in the fuel must be found.Determine the proper location for the construction of wind turbines attention to the criteria and different factors.In this study of the climatic data were collected for the period specified Meteorological OrganizationAnd meteorological data required for weighting the unit accordingly then IDW and methods in ArcGIS that is suitable for mountainous areas,Zoning was used for the analysis and geographical elements,The results of the study for the establishment of wind turbines 2.5 MW to 4 stations Ardabil Province Samen AV 928 (Meshkinshar, Pars Abad, Khalkhal and Ardabil) allocated priorities excellent potential for the Ardabil station.