Evaporation is one of the important factors in the hydrological cycle and is one of the determinants of energy equilibrium at ground level and water balance, and its estimation is required in various fields such as hydrology, agriculture, forest management and pasture management, and water resource management. 44% of the precipitation is due to evaporation from the surface of the earth. In fact, evaporation is the cause of the relationship between the important elements of the planet and the atmosphere. However, one of the concerns of authorities in the water sector is the availability of evapotranspiration data that can properly monitor the conditions. But unfortunately, the access to experimental data of the Lysymeter device is very limited and its statistical period is negligible. Therefore, the present study, based on the Toronto White water bill, predicts the actual evaporation of the Haji Ghoshan watershed for two bases (1350 to 1390) and the future (1391 to 1428) using the results of the GISS general circulation model and the two scenarios of change The climate of RCP4.5 and RCP8.5 has been analyzed. To this end, we tried to simulate the current status and future condition of the four components of the temperature, and analyze the potential and probabilistic data in two basic periods of simulation. However, in the present study, the comparison with the RCP8.5 and RCP4.5 scenarios for the base period from baseline between 1351 to 1390 and the upcoming period between 1391 and 1430, in both scenarios in The future will have a significant decline compared to the actual evaporation base, and in spite of this, potential evaporation will increase dramatically in the studied area.

Accident black spots are places in the points many accidents due to environmental factors and human factors go hand in hand; and these traffic accidents cause loss of life, inability to work and produce in society and the physical and psychological traumas which are very unpleasant consequences. The purpose of this research is to identify black spots to help assess the diagnostic criteria of individuals who are in the open field. In this regard, according to the conditions existing in Golestan province due to the presence of tourists, traffic of passengers and the central province of Khorasan and transit of goods to central Asia and China communicating via the output shaft to the east of the axis Minoodasht- Tangrah with approximate length of 65.3 km from the boarder sample for this study was discussed. After obtaining the required information (such as the map road) open –axis frequency and intensity of random factors, time of occurrence and accident conditions, traffic levels and more in the last three years 92, 93 and 94 of the organizations were investigated including the police, the province, and the transport routes between the terminals and the general directorate of roads and urban development was received. Then, according to the characteristics of the track at various locations, it was a route to 21 points segmentation and action oriented measures to help traditional approach (frequency rate of accidents, critical rate of accidents, intensity and severity rate) and were evaluated to identify black spots. According to the 50 questions presented in the format of AHP, for experts in the field of road safety and accident to different criteria and weighing, the benchmark rate to detect the intensity of black spots on case studies was defined. Black is also to point whether or not other components of the model predicted in its accident- prone black spots is in black spots and the potential to improve model predictions were used. The eleven points were accident- prone to identify and prioritize.

Today, the role of climatology and the study of atmospheric conditions in human life has a great impact on tourism and biodiversity activities. Due to the shortcomings and problems can be managed properly to achieve sustainable development and appropriate steps in the field of land preparation, these problems Fix or minimize. The present study, based on the TCI Tourism Climate Index available in the province of Mazandaran for a 20-year statistical period from 1996 to 2016 and analyzed at 10 synoptic stations in Mazandaran province. The results of this study show that the eastern half of Mazandaran province is ideal for tourism climate and the central and western regions of the province are in acceptable class of TCI climate index. Also, in this study, the stations of White Bridge and Alasht had the highest and lowest frequency, respectively. According to the frequency, summer and July with index of 93 in east and southeast areas of Mazandaran province was the most ideal tourist climate. In winter, March with index of 58 in central and western regions of the study area, The most unsuitable place for climate comfort has been in the province during the 20-year period. Therefore, Mazandaran province has many potentials and attractions for tourism development, which is suitable for tourism development, which can be introduced as an area with high potential for attracting tourists. The climatic condition of the province has been considered due to the favorable climatic conditions.

Nowadays climate change and ecological sustainability are fundamental issues in any field of science and technology. Climate is more than any other factor influencing the type, function and conditions of human life. Today, forecasting meteorological data for future planning in natural areas, including tourism, is of great importance. The present study is a descriptive-analytical one with regard to the nature of the problem and the issue under study. This study is an applied study with emphasis on quantitative methods. Nervousness above 20 ° C and below 20 ° C and degree of comfort were determined by criteria such as (air temperature in degrees Fahrenheit, average relative humidity in percentage, mean minimum air temperature in degrees Celsius, wind speed in meters per second). Nerve Pressure Index from Weather Station Data Nasi of Gilan province was used and final output was calculated with thermal comfort factor in ArcGIS environment. All processes and data analysis in ArcGIS environment with geostatistical IDW model which predicts this unknown point’s technique based on autocorrelation between measured points and their spatial structure. At the end, to show the final map of the final outlet, placed in 7 separate floors for both temperature ranges. The results of the Neural Pressure Evaluation showed that most of the year's central parts of Guilan province are in ecological comfort condition for human health.