Floods are undoubtedly the most dangerous and widespread risks in all parts of the world. Floods have occurred every year in all regions of Ethiopia, resulting in property and lives losses. The downstream part of Mersa watershed which covers 45km 2 is one of the flood-prone areas due to flash floods coming from Mersa River. The purpose of this study is to develop flood inundation map of the study area at different return period flood magnitudes and calculate flood-related economic losses of farmlands for the chosen return periods. The catchment's digital terrain model and computational mesh of the floodplain were created using a 30m*30m digital elevation model of the study area and other data sets, such as stream centerlines, banks, flow pathways, and cross sections were extracted from 5km ground survey and edited in HEC -Geo RAS then imported in to HEC-RAS and simulate two-dimensional unsteady flow analysis in RAS Mapper/ Using daily time series data and easy fit tool the best fitted distribution model of the catchment was determined. The flood frequency analysis was computed using the best fitted distribution model and has a magnitude of 68, 87, 109, 121 and 132 (m3/s) floods which inundates 110, 185, 212, 223 and 232 (ha) areas at 2, 5, 25, 50 and 100 return periods respectively. Preparation of flood inundation map and hazard of the flooded area were done with two-dimensional unsteady flow analysis in HEC-RAS Mapper and the flood quintile was estimated at return periods of 2, 5, 25, 50 and 100. Finally, after having flood inundation areas the economic impact of the flood at the specified return periods were estimated to 1950, 3322, 3779, 3996and 4140 quintal outputs will count as losses. Therefore, to alleviate this problem, it is recommended to investigate the effect of climate and land use land cover changes of the catchment on stream flow, development of flood protection structures and soil conservation practices should be carried out in the upstream and downstream part of the catchment. Key words: Best Fit Distribution Model, Flood Inundation, Economic damage