Abstarct: Abstract Floods cause a lot of damage to the country every year, both in terms of economy and destruction of the environment, natural and residential resources, as well as loss of life. In recent years, the growth of cities located on the banks of rivers, caused by an increase in population and capital, has put residents and properties in the region at risk of flooding. As a result, the flood phenomenon is one of the hydro-climatic events and one of the natural disasters that requires research into the causes of its occurrence and increase, as well as solutions to reduce its risks. Flooding is a problem in the kardeh river area due to its geographical location, abundant rainfall, and the development of gardens along the riverside. In this study, drone images and a fuzzy method and Boolean logic-baxsed map of the river's flood risk were employed to determine the river's flood zone. First, Landsat 8 and Sentinel 2 satellite images were analyzed for floods in the kardeh river area, and the NDWI and MNDWI indices were applied to the images. The study area image was captured along 12 kilometers of the river by a multirotor drone, and after processing the images, the DEM of the studied area was created. Following that, using the required geometric data, flood zoning for 25 years, 50 years, 100 years, and 200 years return periods was performed in HEC RAS software, and flood zones for different return periods were placed on drone images. Finally, using five main criteria (land use, distance from the river, CN coefficient, DEM and slope), the required laxyers were prepared, and a flood risk zoning map in the Kardeh River area was created using the fuzzy method and Boolean logic. The results show that flood risk is higher in gardens and agricultural fields, and floods with a return period of 200 years inundate approximately 27% of agricultural lands and 16% of gardens, according to flood zoning with HEC RAS software. Furthermore, given the high slope of the studied range, the flood does not differ significantly from the 25 years, 50 years, 100 years, and 200 years return periods in the flood zones. Furthermore, the 200-year flood along the 12 kilometers river has flooded 105.1237 hectares of land, and the area of flood zones in fuzzy maps is 113.014 hectares and 66.568 hectares in Boolean maps. Finally, when the fuzzy and Boolean images are compared to the 200 years flood, it is clear that the fuzzy output produced more accurate results, with a 93% correlation with the 200 years flood. Likewise, the flooded surface area in Boolean maps has a 63% correlation with the 200 years flood.