Flood and drought are natural phenomena whose probability of occurrence increases with changing weather conditions. Climate change has affected the hydrologic cycle's parameters and led to changes in temperature and precipitation pattern, which may increase the probability of occurrence of floods and droughts. Arid and semi-arid areas are subject to extreme weather conditions and water resources scarcity. This study aims to assess drought and flood in Syria using remote sensing data. Monthly precipitation data have been collected from 10 land stations in the western part of Syria for the period (1991–2009) and satellite images for monthly precipitation from 1983 to 2020 were collected. The land stations data were used to correct the satellite images and correction equation was developed for each station. Standardized Precipitation Index (SPI) is used for analysis of drought and flood. Also, the main parameters for drought and flood, severity, intensity, duration, and the average return time were estimated. The results showed extreme flood events were recorded in 1988, 2002, 2012, and 2019 and extreme drought events were recorded in 1990, 2014, and 2016. The highest severity of drought and flood were recorded in 2014 and 1988 respectively. However, the highest intensity of droughts and floods was recorded in 2016 and 1988, respectively. If land station data are unavailable, as in the case of Syria owing to the protracted war, satellite images may be a useful source of data for drought and flood analysis after correction. This methodology can help in drought/flood analysis and estimate severity, intensity, duration, and the average return time of flood and drought in other locations of the world. The results proved that SPI is a useful tool to predict the time of occurrence of both flood and drought that could help decision-makers for putting efficient plans for flood and drought risk management that could mitigate the impacts of such risks.