Flooding in coastal cities is typically caused by a combination of extreme rainfall, storm surge, and other factors. Climate change will cause more severe compound flooding in coastal cities. Floods are one of the most common and deadly natural disasters in the world today. There are significant regional variances in hydrographic basins. Thus, more research is needed to understand how climate change may impact flooding. To minimize the damage of this disaster, flood models are essential tools for both post-flood crisis management and pre-flood prevention plans. Hydrodynamic models play a significant role in flood management by detecting flood risk zones. In this study, flood modeling for the Bafra district of Samsun province, located in the Black Sea Region, was carried out using Annual Instantaneous Maximum Flow (AIMF), EasyFit, and HEC-RAS software. AIMF data were fitted to many distributions in EasyFit software, and the most appropriate distribution was determined according to the Kolmogorov–Smirnov test. The recurrent flow rates obtained according to this distribution were modeled in the HEC-RAS software, flood maps were obtained for the region, and various suggestions were presented. According to the analysis, the most appropriate distribution for the data was log-normal (Type-3), and recurrent flow rates are Q25 = 431 m3/s, Q50 = 479.87 m3/s, Q100 = 531.75 m3/s, Q500 = 665.37 m3/s, respectively. Flood modeling has shown that the cross sections are insufficient for possible flood flows where the Kızılırmak River exits the Black Sea region. Additionally, the section cleaning process and suspended solids management should be taken into consideration to reduce flood risks in the region. The study can help reduce the probability of flooding in high-risk areas by designing and executing appropriate flood control measures.