k. omidvar

Fresh water availability and its shortage is one of the most important issues in the world today that some countries are facing. In the last two decades, Kabul province, Afghanistan, has seen a decrease in water resources under the influence of natural and human factors. The purpose of this research is to use satellite data and remote sensing techniques to investigate changes in surface and underground water resources in Kabul province. For this purpose, the satellite data and products available in the Google Earth Engine in the period 2000 to 2022 and the climate data of ground stations in the period 2006 to 2021 have been used, which include: evaporation data- Transpiration, Enhanced Vegetation Index (EVI), Global Product of Surface Water Areas (JRC), GRACE data, OLS Satellite Night Images, Sentinel 2 Satellite Image, Landsat 7 Satellite Image, Temperature, Humidity and Rainfall Data. The change process of the used data was analyzed through the Mann-Kendall test and the significance level of these data was checked. The supervised classification method was used on the two mentioned images to calculate the area of vegetation, water area, residential areas, and barren lands. The obtained results show the reduction of underground water resources (significant reduction trend of GRACE satellite data) and the reduction of the surface water area changes in Kabul province, under the influence of natural and human factors, which among these factors can reduce He pointed out the amount of rainfall, increase in temperature, increase in evaporation-transpiration, increase in the level of vegetation and physical development of Kabul city and increase in the population using water resources.

Aim of this research is to predict the fluctuations of winter (December-March) temperature and precipitation in central Iran using Tele-connection patterns. The applied data is included the Arctic Oscillation index and daily temperature (minimum , maximum and average) and precipitation values during 45 years ( 1965-2010) in 9 stations in central Iran. After averaging the data, seasonal time series was made separately for each variable.  The results of the correlation test revealed that winter temperature is decreased in central Iran in positive phase of Arctic Oscillation. Also, it was cleared that AO variations in autumn justify 25% of winter temperature variations in the under studying zone. Because of lack of significant correlation coefficients in the most under studying stations, we can conclude that there is not any relationship between Arctic Oscillation and winter precipitation in central Iran.